Method and system for operating a comminution process in a ball mill

Abstract

A method of operating a comminution process in a ball mill (10) comprising a rotatable shell (20) having an internal shell surface (22) having protrusions (310) configured to engage a material (30) charge for grinding received solid material feed particles (115) to generate product particles (95; 96) by tumbling the material in the rotating shell (20) to cause vibrations. The method comprises: rotating the shell (20); providing a solid material feed rate setpoint value for setting a solid material feed rate; analyzing product particles (96); generating at least one product measurement value based on said product particle analysis indicative of product particle size; receiving a vibration signal indicative of said vibrations; receiving a position signal indicative of a rotational position of said rotating shell; generating at least one state parameter value indicative of said internal state comprising a toe position value based on said vibration signal and said position signal; controlling said product particle size via a regulator based on said at least one state parameter reference value, said at least one state parameter value and a correlation data set indicative of a causal relationship between a particular internal state and product particle size.

Description

Technical Field

[0001] This invention relates to the field of tumbling mills, and specifically to the monitoring of tumbling mills. The invention also relates to a method for generating information related to the internal state of a tumbling mill, and to the control of tumbling mills. Furthermore, the invention relates to a method for operating a pulverizing process in a tumbling mill, and to apparatus for monitoring the internal state of a tumbling mill. The invention further relates to apparatus for controlling the internal state of a tumbling mill. The invention also relates to a computer program for monitoring the internal state of a tumbling mill. Finally, the invention relates to a computer program for controlling the internal state of a tumbling mill. Background Technology

[0002] In some industries, such as mining, it is necessary to grind large pieces of material to reduce the size of individual blocks of the received material. A tumbling mill can achieve this grinding.

[0003] A tumbling mill includes a housing containing a feed material to be tumbling and grinding when the housing rotates. US2017 / 0225172 A1 discloses that grinding in a tumbling mill can be inefficient, particularly when energy is wasted on the impact of unbroken particles, and that autogenous (AG) and semi-autogenous (SAG) mills sometimes operate in unstable conditions because it is difficult to balance the feed rate of large particles entering the tumbling mill with the consumption of the feed material. According to US2017 / 0225172 A1, in order to control the process, it is necessary to provide real-time information about the current state of the feed material in the tumbling mill. US2017 / 0225172 A1 discloses the use of rotor dynamics to determine the characteristics of the moving feed material within the tumbling mill. According to US2017 / 0225172 A1, a monitoring device for monitoring a tumbling mill is provided. The device includes vibration sensors mounted on two main bearings of the tumbling mill and on the thrust bearing of the mill, generating vibration signals corresponding to the bearings on which the sensors are mounted. These vibration signals are transmitted to an analyzer, which analyzes the signals and displays the operating status of the roller mill digitally or graphically.

[0004] In US 2017 / 0225172 A1 Figure 5 The document discloses two trajectory diagrams, one generated at time 1 and the other at time 2. According to US 2017 / 0225172 A1, by observing the changes in the trajectory diagrams from time 1 to time 2, the mill operator will observe a significant reduction in the amplitude of vibration, and similarly significant reductions in trajectory parameters, frequencies, phases, processes, or other characteristics within the trajectory diagrams. According to US 2017 / 0225172 A1, this information will inform the operator that significant changes have occurred in the overall operation of the mill rotor and the processing of the composite material being loaded. Summary of the Invention

[0005] Given the existing technology, the problem to be solved is how to generate improved information related to the internal state of the tumbler mill and / or how to obtain improved methods for operating the crushing process in the tumbler mill.

[0006] This problem is solved by the example presented in this article. Attached Figure Description

[0007] To provide a simple understanding of the invention, it will be described by way of example and with reference to the accompanying drawings, in which:

[0008] Figure 1A A schematic diagram and a side view of the system including the tumbling mill are shown.

[0009] Figure 1B Another schematic diagram of a system including a tumbling mill is shown.

[0010] Figure 1C This is a block diagram showing a tumbling mill as a block that receives multiple inputs and generates multiple outputs.

[0011] Figure 2 It shows along Figure 1A Another example of a cross-sectional view taken by line AA.

[0012] Figure 3 This is a schematic block diagram of an example of the analysis device shown in Figure 1.

[0013] Figure 4 It is a simplified diagram of the program memory and its contents.

[0014] Figure 5 This is a block diagram illustrating an example of an analysis device.

[0015] Figure 6A This is a diagram of the signal pairs S(i) and P(i) transmitted by the A / D converter.

[0016] Figure 6B This is a diagram of the sequence of signal pairs S(i) and P(i) transmitted by the A / D converter.

[0017] Figure 7 This is a block diagram illustrating a portion of a state parameter extractor.

[0018] Figure 8 is a simplified illustration of an example of a memory and its contents.

[0019] Figure 9 This shows the operation. Figure 7 A flowchart illustrating an example of a method for a state parameter extractor.

[0020] Figure 10 This shows the execution Figure 9The flowchart is an example of the method in step S#40.

[0021] Figure 11 This is a flowchart illustrating another example of the method.

[0022] Figure 12 This shows the execution Figure 9 The flowchart is another example of the method in step S#40.

[0023] Figure 13 It is a graph showing a series of time-series position signals P1, P2, P3, ..., where each position signal P indicates a complete circle of the monitored housing.

[0024] Figure 14A Another example is shown: a cross-sectional view of the middle portion 98 of the rotating mill housing during operation.

[0025] Figure 15 This is a block diagram illustrating an example of a state parameter extractor.

[0026] Figure 16 This is an example illustration of a visual representation of the analysis results.

[0027] Figure 17 This is another example of a visual indication of the analysis results.

[0028] Figure 18 This is another example of a visual indication of the analysis results.

[0029] Figure 19A and Figure 19B This is another example of a visual indication based on the analysis results of the internal state of the tumbling mill.

[0030] Figure 20 This is a block diagram of an example of a compensation extractor.

[0031] Figure 21 This shows the operation. Figure 20 A flowchart of an embodiment of the method for a compensation extractor.

[0032] Figure 22A , Figure 22B and Figure 22C The operation is shown Figure 20 A flowchart of an embodiment of the method for a compensation extractor.

[0033] Figure 23 Another example is shown: a cross-sectional view of the middle section of the rotating mill housing during operation.

[0034] Figure 24 A sketch and schematic top view of another system, including a tumbling mill, are shown.

[0035] Figure 25 A schematic diagram and top view of another embodiment of a system including a tumbling mill are shown.

[0036] Figure 26 A schematic diagram and top view of another embodiment of a system including a tumbling mill are shown.

[0037] Figure 27 A schematic diagram and top view of another embodiment of a system including a tumbling mill are shown.

[0038] Figure 28 A schematic diagram and top view of another embodiment of a system including a tumbling mill are shown.

[0039] Figure 29 A schematic diagram and top view of another embodiment of a system including a tumbling mill are shown.

[0040] Figure 30 Another example is shown: a cross-sectional view of the middle section of the rotating mill housing during operation.

[0041] Figure 31 This is a block diagram illustrating another example of a state parameter extractor.

[0042] Figure 32 It is a block diagram of a rolling mill system, illustrated as a block that receives multiple inputs and generates multiple outputs.

[0043] Figure 33 This is a block diagram of another system including a tumbling mill, which is shown as a block that receives multiple inputs and generates multiple outputs.

[0044] Figure 34 Another schematic diagram of a system including a tumbling mill is shown.

[0045] Figure 35 It can be made by Figure 34 A general schematic diagram of the information transmitted through the input / output interface.

[0046] Figure 36 This is a cross-sectional view of the ball mill casing during operation at a certain speed.

[0047] Figure 37 This applies to ball mills operating at a constant or nearly constant speed (such as...). Figure 36 The graph shows a large number of continuous pairs of vectors X1 and Y2 of the ball mill shown.

[0048] Figure 38 This is a graph of the generated linear regression results.

[0049] Figure 39This is a block diagram of a system used to monitor the internal condition of the mill and to provide the mill operator with information for improvement.

[0050] Figure 40 This is a block diagram of a system used to monitor the internal state X of the mill and enable improvements to the control of the grinding process occurring in the mill. Detailed Implementation

[0051] In the following text, similar features in different examples will be indicated by the same reference numerals.

[0052] Figure 1A A schematic diagram and a side view of a system 5 including a tumbling mill 10 are shown. For example, the tumbling mill 10 may be an autogenous (AG) mill. Alternatively, the tumbling mill 10 may be, for example, a semi-autogenous (SAG) mill. Another example of a tumbling mill 10 is a ball mill 10.

[0053] Figure 1A A cross-sectional view of section AA is also shown. Section AA is also indicated by reference numeral 15. The tumbling mill 10 includes a housing 20 having an inner housing surface 22, which forms a chamber 25 for grinding materials. Figure 1A In the cross-sectional view indicated by reference numeral 15 in the accompanying drawing, the housing 20 is shown rotating counterclockwise at a rotational speed f. ROT Rotate, like a curved arrow f ROT As shown.

[0054] In operation, the grinding chamber 25 contains a charge 30 of material to be tumbled and ground. The charge material has a material surface 33, which is the boundary between the air in the rotating housing 20 and the material 30 (see [link]). Figure 2 The purpose of grinding in a tumbling mill is to reduce the size of solid material particles. This can be achieved, for example, by causing blocks of solid material to fall onto other blocks of solid material. Therefore, the tumbling mill utilizes natural forces, namely gravity, to accelerate the impact of the loaded particles against other particles in the load. According to some embodiments, the walls of the housing 20 comprise a robust material, such as steel, to withstand the impact of heavy particles, such as large blocks of ore being tumbled in the chamber 25. According to some embodiments, the walls of the housing 20 comprise an elastic material to reduce wear on the walls. According to some embodiments, the elastic material comprises rubber. According to some embodiments, the elastic material comprises a polymer, such as polyurethane. According to some embodiments, the inner housing surface 22 comprises a surface coating of an elastic material, such as rubber or polyurethane.

[0055] According to some embodiments, housing 10 is supported on at least two bearings 40 and 50. Housing 20 is rotatable about a rotation axis 60. It should be noted that the axis is an imaginary line around which the object rotates (axis of rotation). The rotation of the housing is used to lift a portion of the load, including particles of solid material, so that some of the solid particles can fall back onto another portion of the load under the influence of gravity. Therefore, it is desirable to increase the rotational speed f of housing 20. ROT Choose an appropriate value to achieve a balance between the lifting and lowering motions of the charge 30. (Reference) Figure 1A cross section Figure 15 Arrow 62 indicates the direction of gravity g associated with the rotating housing 20 and its charge 30. Therefore, the internal state of the tumbling mill 10 depends in part on the balance between gravity 62 and centripetal force 65, which presses the portion of the charge 30 that is stationary relative to the inner housing surface 22 from the center (i.e., from the rotation axis 60) in the radial direction. In other words, during operation of the tumbling mill 10, centripetal force is used to press a portion of the charge 30 against the inner surface 22 of the housing; the centripetal force depends on the rotational speed f of the housing 20. ROT In this regard, it should be noted that the centripetal force acting on a solid material in contact with the inner shell surface 22 depends on the inner diameter of the shell 20. When the gravity 62 acting on a particular solid material block 68 is greater than a portion 69 of the centripetal force acting on the solid material block 68 in the opposite direction to gravity, the solid material block 68 will fall.

[0056] A vibration sensor 70 can be provided to generate a measurement signal S EA Measurement signal S EA It can depend on the mechanical vibration or impact pulse generated when the housing 20 rotates.

[0057] One example of system 5 is operable when the vibration sensor 70 is securely mounted on or at a measuring point on the tumbling mill 10. The measuring point may include a connecting coupling to which the sensor 70 is securely or detachably connected. Figure 1A In the example shown, sensor 70 is mounted on bearing 40. Alternatively, sensor 70 can be mounted elsewhere on the tumbling mill, wherein sensor 70 is capable of generating a measurement signal S based on mechanical vibrations or impact pulses generated when housing 20 rotates. EA .

[0058] The tumbling mill 10 has an input side 80 for receiving solid material blocks and an output side 90 for conveying output material 95 that has passed through the tumbling mill 10.

[0059] The housing 20 may have a generally cylindrical intermediate portion 98, and the chamber 25 in the intermediate portion has an inner radius R. MIC For example, the inner radius RMIC It can exceed 0.5 meters. Alternatively, the inner radius R MIC For example, it can exceed 3 meters. The tumbling mill 10 can alternatively have a chamber with a central inner diameter R exceeding 8 meters. MIC The middle portion of housing 20 has a length L from the input side 80 to the output side 90. MIC For example, the length L of the middle shell section. MIC It can exceed 1 meter. According to one embodiment, the length L of the middle portion of the shell... MIC It can exceed 8 meters. It should be noted that any inner radius R in this example... MIC It can be used with any housing length L in this example MIC Combined.

[0060] Furthermore, it should be noted that the housing 20 may have a polygonal intermediate portion 98. An example of such a polygonal housing shape is a housing having at least three housing wall portions that connect to form the chamber 25 of the tumbling mill. In this case, it should be noted that, for the purposes of this disclosure, the tumbling mill housing having the intermediate portion 98 can be considered to have a generally cylindrical shape, with at least six housing wall portions that connect to form the chamber 25a.

[0061] Therefore, for the purposes of this disclosure, the mill housing having a hexagonal central portion 98 can be considered to have a generally cylindrical shape.

[0062] exist Figure 1A In the example shown, input side 80 includes a first input terminal 100 for solid material blocks 110. Solid material 110, also referred to as feed material 110, may include rock and ore blocks 115 of various sizes. However, the solid material 110 supplied to the first input terminal 100 may have been processed such that a maximum solid material particle size exists. In other words, feed material 110 may include rock and ore blocks 115 with a feed particle size distribution. For example, the feed particle size distribution may result in a specific maximum input solid particle volume V. ISPM And / or a specific maximum input solid particle diameter D ISPM Therefore, the maximum solid particle size in the feed material can be a specific maximum input solid particle volume V. ISPM Solid material 110 may, for example, comprise ore blocks 115 with particle volumes up to ten (10) cubic decimeters, i.e., a single input solid particle 115 has a maximum input solid particle volume V of less than or at most ten (10) cubic decimeters. ISP Alternatively, the maximum solid material particle size can be a specific maximum input solid particle diameter D. ISPM .

[0063] Therefore, a single input solid particle 115 has a maximum input solid particle diameter D of less than or at most 250 mm. ISP .

[0064] The feed particles 115 may include useful minerals as well as minerals considered less useful. Less useful minerals may be referred to as waste minerals. To separate the useful minerals from the waste minerals, the solid feed material 110 is ground in a tumbling mill 10. The ground output material 95 conveyed from the tumbling mill 10 may include particles 96 with a diameter of approximately 0.1 mm or less. The particles 96 conveyed from the tumbling mill 10 may be referred to as product particles 96.

[0065] According to some embodiments, the tumbling mill 10 operates to perform dry grinding. According to one embodiment, the tumbling mill 10 is a ball mill that operates to perform dry grinding. The ball mill 10 includes a plurality of balls 117 for enhancing the grinding of feed particles of solid feed material 110 into ground solid product particles 96. According to one embodiment, the balls 117 of the ball mill include steel balls. According to one embodiment, the tumbling mill 10 is a ball mill used to grind feed particles 115 of hard materials into powder 95 known as cement. In this regard, it should be noted that Portland cement (a type of hydraulic cement) is made by heating limestone (i.e., calcium carbonate) and other materials (e.g., clay) during a process called calcination. Calcination releases carbon dioxide molecules from the calcium carbonate to form calcium oxide or quicklime, which then chemically combines with other materials in the mixture to form calcium silicate and other binding compounds. According to one embodiment, the resulting hard material is then ground into powder together with a certain amount of gypsum using the ball mill 10 described above for dry grinding, in order to manufacture cement.

[0066] According to some embodiments, the tumbling mill 10 operates to perform grinding of solid material 110. An example of a grinding process employing a tumbling mill 10 operated to perform grinding of solid material 110 is a tumbling mill 10 used in the mining industry. According to some embodiments, the mining tumbling mill 10 operates to perform grinding of solid material 110, which comprises a mixture of useful minerals and minerals considered less useful. According to some embodiments, the mining tumbling mill 10 is an autogenous (AG) mill. Alternatively, the mining tumbling mill 10 is a semi-autogenous (SAG) mill. According to some embodiments, the mining tumbling mill 10 is a ball mill 10.

[0067] According to some embodiments, solid material 110 is an ore with a metal content. The average metal content in solid material 110 may, for example, be higher than 0.1%. According to some embodiments, solid material 110 has an average metal content of more than 5% of a desired metal.

[0068] Alternatively, the average metal content in solid material 110 may be, for example, 50%. According to some embodiments, solid material 110 has a content of more than 40% of the desired metal. According to some embodiments, solid material 110 has a content of more than 40% of the desired metal, which is iron. In this case, it should be noted that the content of the desired metal in solid material 110 affects the charge density in the tumbling mill 10. Therefore, according to some embodiments, the charge density in the tumbling mill 10 can indicate the relationship between the desired metal and the waste minerals in the charge of the tumbling mill 10.

[0069] According to some embodiments, the grinding process can be facilitated by providing liquid 120. An example of facilitating the grinding process by providing liquid 120 is a tumbling mill used in the mining industry. According to some embodiments, liquid 120 enters the tumbling mill 10 at a second input terminal 130 on the input side 80 of the tumbling mill 10.

[0070] In the rotating housing 20, the input block of solid material 110 is mixed with the input liquid 120 to form the charge 30.

[0071] When the density of the input liquid 120 is different from the density of the input solid material 110, the density of the charge 30 can be controlled by controlling the ratio of the input liquid 120 to the input solid material 110. Therefore, when the density of the input liquid 120 is lower than the density of the input solid material 110, the density of the charge 30 can be reduced by increasing the amount of input liquid 120.

[0072] Input liquid 120 may include water. The density of water is approximately 997 kg per cubic meter. Input solid material blocks typically have a higher density than input liquids. Input solid material blocks typically have a density exceeding 1500 kg per cubic meter. Input solid material 110 may include ore containing useful minerals mixed with other minerals.

[0073] An example of useful minerals is those containing metals, such as aluminum or iron. Aluminum has a density of approximately 2700 kg / m³. Iron has a density of approximately 7870 kg / m³. The aforementioned "other minerals" can include, for example, granite or other rock formations. Granite has a density of approximately 2700 kg / m³.

[0074] Table 1 provides some examples of solid materials and their corresponding material properties.

[0075] Table 1

[0076]

[0077] In the field of mineralogy, the term toughness describes a mineral's resistance to fracture, beading, cutting, or other forms of deformation.

[0078] If a material fractures under stress with only a small amount of elastic deformation and no significant plastic deformation, then that material is brittle. Brittle materials absorb relatively little energy before fracturing, even high-strength materials.

[0079] A malleable material can be stretched or shaped by striking or applying pressure. A soft material can be pulled or stretched by mechanical forces without breaking.

[0080] Compressive strength is the ability of a material or structure to withstand a load that tends to reduce its size. In contrast, tensile strength is the ability of a material or structure to withstand a load that tends to elongate. In other words, compressive strength resists compression (being pushed together), while tensile strength resists stretching (being pulled apart).

[0081] It should be noted that gold has a density of 19,320 kg per cubic meter, which is significantly higher than that of the other solid materials listed in Table 1 above. In this regard, it should also be noted that the gold content in some gold ores is generally low compared to the content of other solids used as feed material 110 for the tumbling mill.

[0082] The output side 90 of the tumbling mill 10 may include a separator for conveying output material 95 to the output end 200 and for retaining material clumps with particle sizes exceeding a certain limit. The separator may include a screen configured to screen out material clumps with particle sizes smaller than a specific limit, to be conveyed as output material 95 to the output end 200. The ground output material 95 conveyed from the tumbling mill 10 may include particles with a diameter smaller than a certain limit output particle diameter. The limit output particle diameter may be 0.1 mm.

[0083] A measure of the production quality of the tumbling mill 10 can be the proportion of output particles with a diameter less than 45 μm (where μm represents micrometers), or the amount of output particles with a diameter less than 45 μm per hour.

[0084] Furthermore, a highly efficient grinding process is desired. One aspect of grinding process efficiency is the amount of grinding material per unit time. Therefore, it is desirable to increase or optimize the rate at which kilograms / hour of grinding solid material with particle sizes smaller than the limit value is achieved. However, this value is typically the metric tons / hour of solid material fed into the tumbling mill 10.

[0085] Another aspect of grinding process efficiency is the amount of grinding material per unit of energy used to minimize energy consumption during the grinding process. Therefore, it is desirable to increase or optimize the yield, expressed in kg / kWh of grinding solids, with the particle size of the grinding solids being smaller than a limit. In this case, it should be noted that tumbling mills can typically have a power consumption exceeding 4 MW. Some tumbling mills have an average power consumption of 10 MW, while some may have a peak power consumption of 20 MW. In this case, it should be noted that when a tumbling mill has an average power consumption of 10 MW, the energy consumption is 10,000 kWh per hour. Therefore, when the tumbling mill operates 24 hours a day, year-round, even a small increase in the energy efficiency of the grinding process (e.g., a one percent (1%) increase) could result in an annual energy saving of 6 million kWh.

[0086] The efficiency of the grinding process in the tumbling mill 10 depends on several variables that affect the internal state of the tumbling mill 10. One variable affecting the efficiency of the grinding process in the tumbling mill 10 is the filling degree of the tumbling mill 10. Therefore, it is desirable to control the inflow of the input solid material 110 in order to achieve the optimal filling degree.

[0087] To maximize the amount of output material 95 from the tumbling mill 10, it is desirable to control the inflow of input material 110 to maintain the optimal state of the tumbling process. The optimal internal state of the tumbling process may include a certain degree of filling of the housing 20, i.e., a certain feed volume. Therefore, one variable affecting the efficiency of the grinding process in the tumbling mill 10 is the solid feed rate R. s That is, the amount of solid material particles supplied to the tumbling mill 10 per unit time.

[0088] Another variable affecting the efficiency of the grinding process in the tumbler mill 10 is the mineralogical properties of the input solid material particles 110. In this regard, it should be noted that mineralogical science is a branch of geology that specifically studies the physical properties of minerals as well as their chemical and crystal structures. Furthermore, the mineralogical properties of the particles in the charge 30 are not constant over time, as the composition of the solid material 110 (e.g., ore from a mine) typically changes over time. Changes in the mineralogical properties of the particles in the charge 30 affect the efficiency of the grinding process in the tumbler mill 10. Therefore, the efficiency of the grinding process may vary over time due to changes in the mineralogical properties of the particles in the material charge 30. Thus, if the material feed remains constant, a decrease in the efficiency of the grinding process over a given time span will lead to an increase in the charge volume in the mill 10. Therefore, unless the operator of the tumbler mill is fully informed of the current charge volume in the mill 10, there is a risk of overload, which in the worst case could lead to a complete halt in the grinding process.

[0089] Another variable affecting the efficiency of the grinding process is the size distribution of the solid material particles 110 supplied to the tumbling mill 10. According to some embodiments, controlling the feed of the solid material particles 110 such that a certain proportion of the solid material particles 110 supplied at the first input end 100 have an individual volume greater than one cubic decimeter improves the efficiency of the grinding process. It has been concluded that controlling the feed of the solid material particles 110 such that a certain proportion of the solid material particles 110 supplied at the first input end 100 have an individual volume greater than one cubic decimeter increases the efficiency of the grinding process, particularly when the tumbling mill is an AG mill or a SAG mill.

[0090] The housing 20 is typically opaque, meaning that visual inspection of the contents within the housing is not possible during operation of the tumbling mill 10. Furthermore, the movement of the heavy ore being tumbled during operation of the tumbling mill 10 prevents the placement of cameras or other sensitive detectors inside the housing 20.

[0091] One objective of this document is to describe methods and systems for improving the monitoring of the internal state of a tumbling mill during operation. Another objective is to describe methods and systems for improving a human-machine interface (HCI) that relates to the internal state of the tumbling mill during operation. A further objective is to describe methods and systems for improving a graphical user interface associated with the grinding process in the tumbling mill 10.

[0092] The inventors realized that mechanical vibration V might occur during the operation of the tumbling mill 10. IMP This refers to the impact between a protrusion (e.g., an elevator) on the inner surface of the rotating housing 20 and at least one particle in the toe 205 of the material loading 30. The inventors have also considered this mechanical vibration V. IMP It can indicate the current internal state of the tumbling mill 10 and / or the current state of the grinding process. Mechanical vibrations V are generated when the protrusions (e.g., elevators) interact with particles in the toe 205 of the material charge 30 in the chamber 25. IMP The impact force F generated by the interaction between the rotating elevator and the material loading 30. IMP This causes at least one particle in the toe 205 of the material charge 30 to accelerate, and the impact causes a mechanical impact vibration V. IMP In fact, the impact force F IMP It can cause mechanical shock vibration V IMP It indicates the current internal state of the tumbling mill 10 and / or the current state of the grinding process.

[0093] A sensor 70, placed outside chamber 25, can detect vibrations caused by the interaction of particles in the charge 30 within chamber 25 during operation of the tumbling mill 10. Therefore, reference... Figure 1AThe sensor 70 can generate a measurement signal S based on the mechanical vibration or impact pulses generated when the housing 20 rotates. EA Therefore, the measured signal S EA The impact force F can be determined and indicated by the impact force between at least one particle in the protrusion (e.g., elevator) and the toe 205 of the material feed 30 during operation of the tumbling mill 10. IMP .

[0094] Sensor 70 may be, for example, an accelerometer 70, which is configured to generate a measurement signal S. EA The amplitude of the measured signal depends on the impact force F. IMP The inventors concluded that there may be mechanical vibrations V that indicate the current internal state of the tumbling mill 10 and / or the current state of the grinding process. IMP However, traditional methods used to measure vibration and / or to analyze and / or visualize such vibration may have been inadequate to date.

[0095] An analysis device 150 is provided for monitoring the tumbling process. The analysis device 150 may also be referred to as a monitoring module 150A.

[0096] Analysis device 150 can be based on measurement signal S EA Generate information indicating the internal state of the grinding process. Generate measurement signal S. EA The sensor 70 is coupled to the input terminal 140 of the analysis device 150 so as to transmit the measurement signal S EA The signal is transmitted to the analysis device 150. The analysis device 150 also has a second input terminal 160 for receiving a position signal E based on the rotational position of the housing 20. P .

[0097] A position sensor 170 is provided to generate a position signal E based on the rotational position of the housing 20. P As described above, the housing 20 is rotatable about the rotation axis 60, so the position sensor 170 can generate a series of housing position signal values ​​P. S Position signal E P The position mark 180 is used to indicate the instantaneous rotational position of the housing 20. The position mark 180 can be disposed on the outer surface of the housing 20, such that when the housing 20 rotates around the rotation axis 60, the position mark 180 passes the position sensor 170 once per revolution, thereby causing the position sensor 170 to generate a rotation mark signal P. S This rotational marker signal P S It can take the form of an electrical pulse, which has an edge that can be precisely detected and indicates a specific rotational position of the monitored housing 20. The analysis device 150 can then analyze the position signal E. P Generates the rotational speed f of the indicator housing 20 ROTInformation, for example, is obtained by detecting the duration between rotation mark signals PS. When the position sensor 170 is an optical device (e.g., a laser transceiver), the position mark 180 can be, for example, an optical device 180 (e.g., a reflector 180) configured to generate a rotation mark signal P when the intensity of laser reflection changes due to the laser beam irradiating the reflector 180. S Alternatively, when the position sensor 170 is a device 170 configured to detect a changing magnetic field, the position marker 180 can be, for example, a magnetic device 180, such as a strong magnet 180. An example of a device configured to detect a changing magnetic field is a device including an induction coil that generates an electric current in response to the changing magnetic field. Therefore, the device 170 configured to detect a changing magnetic field is configured to generate a rotational marker signal P when passing the magnetic device 180. S Alternatively, the position sensor 170 can be implemented by an encoder 170, which is mechanically coupled to the rotary mill housing 20 such that the encoder generates, for example, a marker signal P for each revolution of the rotary mill housing 20. S .

[0098] System 5 may include a control room 220, which allows mill operator 230 to operate the tumbling mill 10. Analysis device 150 may be configured to generate information indicating the internal state of the tumbling mill 10. Analysis device 150 also includes a human-machine interface (HCI) 210 for user input and output. HCI 210 may include a display or screen 210S for providing visual indications of the analysis results. The displayed analysis results may include information indicating the internal state of the tumbling process, enabling operator 230 to control the tumbling mill.

[0099] The tumbling mill controller 240 is configured to convey the solid material feed rate setpoint R. SSP It can also optionally transmit the liquid feed rate setpoint R. LSP According to some embodiments, the set point value R is... SSP Set by operator 230. According to some embodiments, the setpoint value R... LSP It is also set by operator 230. Therefore, the roller mill controller 240 may include a mill user input / output interface 250, enabling the operator to adjust the solid material feed rate R. S and / or liquid feed rate R L .

[0100] As described above, the input side 80 of the tumbling mill includes a first input end 100 for a solid material block 110, and optionally, the input side 80 may also have a second input end 130 for a liquid 120 (e.g., water) to enter the chamber 25. The solid material 110 can be conveyed to the first input end 100 via a conveyor belt 260. The conveyor belt 260 operates at a conveyor belt speed at a solid material feed rate R. S Solid material 110 is transferred to the first input terminal 100.

[0101] During the operation of the tumbling mill 10, under specific internal conditions of the tumbling mill 10, the solid material feed rate R S This could be, for example, 10,000 kg per minute. Similarly, during the operation of the tumbling mill 10, under specific internal conditions of the tumbling mill 10, the liquid feed rate R... L For example, it could be 1000 kilograms per minute.

[0102] exist Figure 1A and / or Figure 1B The symbol for controllable valve 270 schematically indicates the liquid feed rate R. L The controllable valve receives the liquid feed rate setpoint R from the tumbling mill controller 240. LSP Similarly, in Figure 1A and / or Figure 1B The symbol for the controllable valve 280 schematically illustrates the feed rate R of the solid material. SF The controllable valve receives the solid material feed rate setpoint R from the tumbling mill controller 240. SSP .

[0103] According to some embodiments, the tumbling mill controller 240 can also set the rotational speed f of the mill housing. ROT Generate setpoint value f ROT_SP Speed ​​setpoint value f ROT_SP It can also be called U1 SP The speed setpoint value f can be generated via user input from operator 230 through user input / output interface 250. ROT_SP Also known as U1 SP ,like Figure 1B As shown.

[0104] like Figure 1B As shown, the tumbling mill controller 240 can also generate a setpoint value U2. SP and U3 SP Among them, U2 SP The above R SSP U3 SP The above R LSP .

[0105] In addition, the tumbling mill controller 240 can also generate the ball feed rate setpoint value U4. SP R BFSP Used to set the ball feed rate U4, R BF Ball feed rate U4, R BF This refers to the number of grinding balls fed into the ball mill per unit time to enhance the grinding process. Therefore, when mill 10 is a ball mill, it includes grinding balls 1168 (see...). Figure 36 When using a tumbling mill, this setpoint value may be relevant.

[0106] The balls used in ball mills can be made of chrome steel or stainless steel. Alternatively, ball mills can use balls made of ceramic materials. In some examples, ball mills can use balls that include rubber materials.

[0107] exist Figure 1A In the example shown, the mill user input / output interface 250 is coupled to the regulator 240, and the HCI 210 is coupled to the analysis device 150 or monitoring module 150A, which is configured to generate information indicating the internal state of the tumbler mill 10. Therefore, when... Figure 1A When coupled only to the monitoring module 150A, the HCI 210 can be advantageously added to the control room 220 without requiring any modification to the existing input / output interface 250 and the regulator 240 used by the mill operator 230 to operate the tumbler mill 10.

[0108] The solutions and examples disclosed in this document aim to describe methods and systems for improving the monitoring of the internal state X of the tumbling mill 10 during operation. Another objective of the solutions and examples disclosed in this document is to describe methods and systems for improving the control of the internal state X of the tumbling mill 10 during operation. Furthermore, the solutions and examples disclosed in this document aim to describe methods and systems for improving a human-machine interface (HCI) that involves conveying useful information about the internal state X of the tumbling mill during operation. Another objective of this document is to describe methods and systems for improving a graphical user interface related to the grinding process in the tumbling mill 10.

[0109] Another objective of the solutions and examples disclosed in this document is to describe methods and systems for improving the control of the output Y of the tumbling mill 10 during operation. Yet another objective of the solutions and examples disclosed in this document is to describe methods and systems for improving a human-machine interface (HCI) that involves transmitting useful information about the output Y of the tumbling mill 10 during operation and / or also transmitting useful information about the corresponding internal state X of the tumbling mill during operation.

[0110] Figure 1B Another schematic diagram of a system 320 including a tumbler mill 10 is shown. Therefore, reference numeral 320 refers to a system including a mill 10 having a rotatable housing 20, as described herein. Figure 1B System 320 may include the above-mentioned Figure 1A and Figure 2 The parts described and / or as described elsewhere in this document and configured.

[0111] Despite Figure 1A In the example shown, the mill user input / output interface 250 is coupled to the regulator 240, and the HCI 210 is a separate input / output interface coupled to the analysis device 150 or the monitoring module 150A, but Figure 1B The system shown can provide integrated HCI 210, 250, and 210S. Therefore, Figure 1B The input / output interface 210 can be configured to enable all the inputs and / or outputs described above in combination with interfaces 210 and 250.

[0112] Figure 1C This is a block diagram showing a tumbling mill, block 10B, that receives multiple inputs U1, ... Uk and generates multiple outputs Y1, ... Yn. (Reference) Figure 1C It should be noted that, for analytical purposes, the tumbling mill 10 can be considered as a black box 10B with multiple input variables, referred to as input parameters U1, U2, U3, ..., Uk, where the index k is a positive integer. During the operation of the black box tumbling mill 10B, the black box tumbling mill 10B has an internal state X and produces multiple output variables, also referred to as output parameters Y1, Y2, Y3, ..., Yn, where the index n is a positive integer.

[0113] The internal state X of the mill can be described or indicated by multiple internal state parameters X1, X2, X3, ..., Xm, where the index m is a positive integer.

[0114] Using linear algebra terminology, the input variables U1, U2, U3, ... Uk can be collectively referred to as the input vector U; the internal state parameters X1, X2, X3, ... Xm can be collectively referred to as the internal state vector X; and the output parameters Y1, Y2, Y3, ... Yn can be collectively referred to as the output vector Y.

[0115] At a time point called r, the internal state X of the mill 10 can be referred to as X(r). This internal state X(r) can be described or indicated by multiple parameter values ​​that define different aspects of the internal state X(r) of the mill 10 at time r.

[0116] The internal state X(r) of the black-box tumbling mill 10B depends on the input vector U(r), and the output vector Y(r) depends on the internal state vector X(r). One aspect of the internal state X is the total amount of material 30 in the housing 20, and this total amount does not change immediately. Therefore, during the operation of the mill 10, the internal state X(r) can be considered as a function of the earlier internal state X(r-1) and the input U(r):

[0117] X(r) = f1(X(r-1), U(r)), where X(r-1) indicates the internal state X of mill 10 at a time point before time point r.

[0118] Similarly, the output Y of black box 10B can be considered as a function of its internal state X:

[0119] Y(r) = f2(X(r))

[0120] Figure 2 It is along Figure 1A Another example of a cross-sectional view taken by line AA shows a more detailed example of the middle portion 98 of housing 20. Housing 20 has an inner housing surface 22 facing the chamber 25, said inner housing surface 22 including a plurality of protrusions 310. According to some embodiments, at least two protrusions 310 are provided. Figure 2 The example housing 20 shown includes 12 protrusions 310, which are equidistantly positioned on the inner housing surface 22 of the housing 20. The protrusions 310 can be configured to engage and lift the material 30 as the housing rotates about the axis 60. Thus, the protrusions 310 can be referred to as elevators 310. The loading material has a material surface 33 that serves as the boundary between the air and the material 30 within the rotating housing 20.

[0121] exist Figure 2 In the middle, at a rotational speed f in the clockwise direction ROT The housing 20 is shown during rotation. The lift 310 includes structures projecting from the inner surface 22 of the housing towards the center of the housing 20, such as internal structures, textures, stripes, protrusions, etc. The lift 310 (also referred to as protrusion 310) has a leading edge 312 that engages and lifts the material load 30 as the mill 10 rotates about axis 60, causing the material to fall spontaneously within the inner chamber 25. In one example, the lift 310 includes an elongated rod mounted on the inner housing surface wall 22 to at least partially line the inner housing surface 22 of the mill 10. In other examples, the lift 310 is integrally formed with the inner housing surface wall 22 as a single unit. According to some embodiments, the leading edges 312 of the protrusion 310 are equidistant. Therefore, refer to... Figure 2The example housing 20 shown includes twelve protrusions 310, each protrusion 310 having a leading edge 312, and the angular distance between any two adjacent leading edges 312 is 30 degrees. In this case, it should be noted that when there are L protrusions 310 on the inner housing surface 22, and the L protrusions 310 are positioned such that the leading edges 312 of the protrusions 310 are equidistant, then the angular distance between any two adjacent leading edges 312 is 360 / L degrees. Therefore, when there are L protrusions 310 at angular positions on the inner housing surface 22, and the L protrusions 310 are positioned equidistantly, the angular distance between any two adjacent protrusions 310 is 360 / L degrees.

[0122] exist Figure 2 In the example shown, the position sensor 170 is mounted in a fixed manner, such that a position signal E is generated having a series of position signal values ​​PS. P The position marking device 180 is used to indicate the instantaneous rotational position of the housing 20. The position marking device 180 can be disposed on the outer surface of the housing 20, such that when the housing 20 rotates about the rotation axis 60, the position marking 180 passes the position sensor 170 once per revolution, thereby causing the position sensor 170 to generate a rotation marking signal value PS. The position sensor 170 may include a tachometer 170, which, for example, transmits a position signal pulse Ep per revolution.

[0123] The position marking device 180 may include a metal object. For example, the metal object may be a bolt or a metal bracket.

[0124] refer to Figure 1B Solid material particles 115 enter the mill housing 20 through the material inlet 100 and are broken during operation of the mill 10 due to collisions with other particles 115, 30 and / or the internal housing surface 22 and / or balls. The breakage produces solid material product particles 96, also referred to as solid material product or product particles 96. The solid material product exits the mill housing 20 through the outlet 200.

[0125] An important aspect of the grinding process is the breakage rate. The breakage rate depends on, for example, the frequency of impacts experienced by solid feed material particles 115 after entering the rotating housing 20.

[0126] Another important aspect of the grinding process is the particle size distribution of the solid material product particles generated by the collision. Particle size distribution can also be referred to as the appearance distribution function.

[0127] Another important aspect of the grinding process is the flow rate of solid material product particles 96 exiting the mill housing 20. The particle conveying outside the mill housing 20 can also be referred to as the product discharge rate.

[0128] Therefore, in summary: the solid feed particles 115 are fed at a solid material feed rate R. S The feed material enters the chamber 25 of the mill 10. The feed particles 115 have a first particle size distribution, also referred to as the feed particle size distribution. This distribution can be measured as the solid feed material is fed into the mill 10. A feed material analyzer 325 can be provided to generate measurements indicating at least one feed material characteristic U4. At least one feed material characteristic U4 may include the solid feed material particle size distribution. Therefore, the feed material particle size distribution can be estimated, for example, by measurement. Alternatively, the solid feed material particle size distribution U4 can be predetermined. In some examples, the solid feed material particle size distribution U4 is known due to processing and / or sorting prior to conveying the solid feed material 110 to the conveyor belt 260.

[0129] Once received in the grinding chamber 25, the received particles can be collectively referred to as the feed material 30. While in the grinding chamber 25, the solid material particles 30 break down, causing solid product particles 96 to be discharged from the chamber 25 via the output end 200. The breakage results in a change in the particle size distribution.

[0130] Solid material product particles 96 at product discharge rate R SDis The product flows out of the grinding chamber at 25°. The product discharge rate R can be measured. SDis And it can be regarded as the output parameter Y1.

[0131] The discharged solid product particles 96 have a second particle size distribution, also known as the product particle size distribution. The product particle size distribution can be measured, and values ​​indicating the product particle size distribution can be provided, for example, as output parameter values ​​Y2, Y3, etc.

[0132] Therefore, the feed particles 115 having the first particle size distribution or feed particle size distribution U4 feed at a solid material feed rate R S Product particles 96, which are fed into mill 10 and have a product particle size distribution Y2 or a second particle size distribution Y2, are discharged at a product discharge rate Y1=R. SDis Discharged from mill 10.

[0133] During the process of conveying the feed particles 115 from the inlet 100 to the outlet 200, the feed particles 115 are transformed into multiple smaller product particles 96. This transformation is due to the pulverization process that occurs during the operation of the tumbler mill 10.

[0134] It is believed that the particle size distribution of the product depends on the following:

[0135] -Feed particle size distribution, and

[0136] -The internal state X of the mill 10 during the period from the feed input 100 to the discharge of the output material 95 as solid product particles 96 from the mill output 200.

[0137] Therefore, the amount of solid feed material particles 115 that are broken down depends on the aforementioned breakage rate and the internal state X of the mill 10. The internal state X of the mill 10 determines the duration T from when the received feed particles 115 are conveyed from the feed inlet 100 until the output material 95 is discharged from the mill outlet 200. C The average time it takes for the feed to travel from the inlet 100 to the outlet 200 of the mill can be referred to as the duration T. C .

[0138] refer to Figure 1B The diagram illustrates a Cartesian coordinate system with three mutually perpendicular axes x, y, and z. It should be understood that during the operation of the mill 10, the material 30 travels from the input side 80 to the output side 90 of the mill in the positive x-axis direction. Therefore, although the material 30 is tumbled within the mill 10, it also gradually travels from the input side to the output side of the mill in a direction parallel to the mill's axis of rotation. However, different individual particles may travel this distance at different speeds. A large number of small feed particles can be transported from the input side to the output side of the mill and then discharged relatively quickly via the mill output end 200, for example, because they are small enough to pass through the outlet grid in a short time, while the largest feed particles require more time to be ground into product particles small enough to pass through the same outlet grid. Therefore, a certain proportion of large feed particles will remain in the mill for a longer time than a correspondingly larger proportion of small feed particles.

[0139] However, during steady-state operating conditions, the mass flow rates into, through, and out of mill 10 will be constant or substantially constant. Therefore, the delivery of material 30 through mill 10 can be discussed in terms of mass per unit time, for example, measured in kilograms per minute or metric tons per hour.

[0140] In this regard, it should be noted that the average duration for conveying the feed particles 115 from the feed inlet 100 to the mill outlet 200 and for these feed particles 115 to simultaneously transform into multiple smaller product particles 96 depends on the average flow velocity v along the x-axis in the mill chamber 25. xA Therefore, at least under steady-state conditions of the grinding process, the average time it takes for particles to be conveyed from the feed inlet 100 to the grinding outlet 200 depends on the length of the grinding chamber 25 in the x-direction and the average flow velocity v. xA .

[0141] Figure 3This is a schematic block diagram of an example of the analysis device 150 shown in Figure 1. The analysis device 150 has features for receiving analog vibration signals S from the vibration sensor 70. EA Input terminal 140. Input terminal 140 is connected to analog-to-digital (A / D) converter 330. A / D converter 330 operates at a specific sampling frequency f. S For the received analog vibration signal S EA Sampling is performed in order to transmit data at the specified sampling frequency f. S Digital measurement data signal S MD Furthermore, the amplitude of each sample depends on the amplitude of the analog signal received at the sampling time. Digital measurement data signal S is transmitted at the digital output terminal 340 coupled to the data processing device 350. MD .

[0142] refer to Figure 3 The data processing device 350 is coupled to a computer-readable medium 360 for storing program code. The computer-readable medium 360 may also be referred to as memory 360. The program memory 360 is preferably non-volatile memory. The memory 360 may be a read / write memory, i.e., capable of reading data from memory and writing new data to memory 360. According to one example, the program memory 360 is implemented using flash memory. The program memory 360 may include a first storage segment 370 for storing a first set of executable program code 380 to control the analysis device 150 to perform basic operations. The program memory 360 may also include a second storage segment 390 for storing a second set of program code 394. The second set of program code in the second storage segment 390 may include program code for causing the analysis device 150 to process detection signals. Signal processing may include processing for generating information indicating the internal state of the tumbling mill, as discussed elsewhere in this document. Furthermore, signal processing may include control of the internal state of the tumbling mill, as discussed elsewhere in this document. Therefore, signal processing may include generating data indicating the internal state of the rolling mill, such as combining, for example... Figure 5 , Figure 15 and / or Figure 24 The embodiment of the state parameter extractor 450 is disclosed.

[0143] The memory 360 may further include a third memory segment 400 for storing a third set of program code 410. The program code 410 in the third memory segment 400 may include program code for causing the analysis device to perform a selected analysis function. When the analysis function is performed, the analysis device may display the corresponding analysis results on the user interface 210, 210S, or transmit the analysis results on the port 420.

[0144] The data processing device 350 is also coupled to a read / write memory 430 for data storage. Therefore, the analysis device 150 includes a data processor 350 and program code for causing the data processor 350 to perform certain functions, including digital signal processing functions. When it is stated in this document that the device 150 performs a function or method, that statement may mean that a computer program runs in the data processing device 350 to cause the device 150 to perform the method or function described in this document.

[0145] Processor 350 may be a digital signal processor (DSP). DSP 350 may also be referred to as a DSP. Alternatively, processor 350 may be a field-programmable gate array (FPGA). Therefore, a computer program can be executed by the FPGA. Alternatively, processor 350 may include a combination of a processor and an FPGA. Therefore, the processor can be configured to control the operation of the FPGA.

[0146] Figure 4 This is a simplified diagram of the program memory 360 and its contents. The simplified diagram is intended to convey an understanding of the general idea of ​​storing different program functions in memory 360, and is not necessarily a correct technical instruction on how programs will be stored in actual memory circuitry. The first memory segment 370 stores program code used to control the analysis device 150 to perform basic operations. Although... Figure 4 The simplified illustration shows the pseudocode, but it should be understood that the program code can be machine code or can be generated by the data processing device 350 ( Figure 3 Any level of program code that is executed or interpreted.

[0147] Figure 4 The second memory segment 390, as shown, stores a second set of program code 394. When run on the data processing device 350, the program code 394 in segment 390 will cause the analysis device 150 to perform functions, such as digital signal processing functions. These functions may include digital measurement data signals S. MD Advanced mathematical processing.

[0148] A computer program for controlling the functions of the analysis device 150 can be downloaded from a server computer. This means transmitting the downloaded program over a communication network. This can be achieved by transmitting the program over the communication network via a modulated carrier wave. Therefore, the downloaded program can be loaded into a digital memory, such as memory 360 (see...). Figure 3 and Figure 4 Therefore, program 380 and / or signal processing program 394 and / or analysis function program 410 can be transmitted via, for example, port 420 ( Figure 1A and / or Figure 1B and Figure 3The program receives data through communication ports such as 360 and loads it into the program memory 360.

[0149] Therefore, this document also relates to a computer program product, such as program code 380 and / or program code 394 and / or program code 410, which can be loaded into the digital memory of a device. The computer program product includes software code portions that, when the product is run on the data processing unit 350 of the device 150, are used to perform signal processing methods and / or analysis functions. The term "run on the data processing unit" means that the computer program, in addition to the data processing unit 350, performs the methods described in this document.

[0150] The phrase "computer program product loadable into the digital memory of an analysis device" means that a computer program can be incorporated into the digital memory of the analysis device 150 to enable the analysis device 150 to be programmed to perform or be adapted to perform the methods described herein. The term "loaded into the digital memory of a device" means that a device programmed in this manner is capable of or adapted to perform the functions and / or methods described herein. The aforementioned computer program product may also be programs 380, 394, 410 loadable onto a computer-readable medium (e.g., an optical disc or DVD). Such a computer-readable medium can be used to transmit programs 380, 394, 410 to a client. Alternatively, as described above, the computer program product may include a carrier wave, which is modulated to transmit computer programs 380, 394, 410 over a communication network. Therefore, computer programs 380, 394, 410 can be downloaded from a vendor server to a client having the analysis device 150 via the Internet.

[0151] Figure 5 This is a block diagram illustrating an example of an analysis device 150. Figure 5 In the example, some function blocks represent hardware, and some function blocks can represent hardware, or they can represent functions implemented by running program code on the data processing device 350, such as in combination. Figure 3 and Figure 4 The subject of discussion.

[0152] Figure 5 Device 150 in the middle shows Figure 1A and / or Figure 1B and / or Figure 3 The example shown is of the analytical device 150. For ease of understanding, Figure 5 Some peripheral devices coupled to device 150 are also shown. Vibration sensor 70 is coupled to input 140 of analysis device 150 to convert analog measurement signal S EA (also known as vibration signal S) EA The data is transmitted to analysis device 150.

[0153] Furthermore, position sensor 170 is coupled to the second input terminal 160. Therefore, position sensor 170 will depend on the position signal E that depends on the rotational position of housing 20. P The data is transmitted to the second input terminal 160 of the analysis device 150.

[0154] Input terminal 140 is connected to analog-to-digital (A / D) converter 330. A / D converter 330 operates at a specific sampling frequency f. S The received analog vibration signal SEA is sampled in order to transmit the signal at the specific sampling frequency f. S Digital measurement data signal S MD Furthermore, the amplitude of each sample depends on the amplitude of the analog signal received at the sampling time. Digital measurement data signal S is transmitted on the digital output terminal 340. MD The digital output is coupled to the data processing unit 440. The data processing unit 440 includes function blocks indicating the functions performed. In terms of hardware, the data processing unit 440 may include a data processing unit 350, a program memory 360, and a read / write memory 430, as described above. Figure 3 and Figure 4 As described. Therefore. Figure 5 The analysis device 150 may include a data processing unit 440 and program code for enabling the analysis device 150 to perform certain functions.

[0155] Digital measurement data signal S MD With position signal E P Parallel processing. Therefore, the A / D converter 330 can be configured to sample the analog vibration signal S. EA Simultaneous sampling of position signal E P Position signal E P The sampling can use the same sampling frequency f S To execute in order to generate digital position signal E PD The amplitude of each sample P(i) depends on the received analog position signal E at the sampling time. P The range.

[0156] As described above, the analog position signal E P It can have a marker signal value P S For example, in the form of an electrical pulse, the marker signal value has an amplitude edge that can be accurately detected and indicates a specific rotational position of the monitored housing 20. Therefore, although the analog position marker signal P... S It has amplitude edges that can be accurately detected, but the digital position signal E PD The value will switch from the first value (e.g., "0" (zero)) to the second value (e.g., "1" (one)) at different times.

[0157] Therefore, the A / D converter 330 can be configured to transmit a series of measurement pairs S(i) associated with the corresponding position signal value P(i). The letter "i" in S(i) and P(i) represents a time point, i.e., a sample number. Thus, by analyzing the time series of the position signal value P(i), the indicative digital position signal E can be identified. PD The occurrence time of the rotational reference position of the rotating shell is detected by the sample P(i) that has switched from the first value (e.g., "0" (zero)) to the second value (e.g., "1" (one)).

[0158] Figure 6A This is a diagram of the signal pairs S(i) and P(i) transmitted by the A / D converter 330.

[0159] Figure 6B This is a diagram illustrating the sequence of signal pairs S(i) and P(i) transmitted by the A / D converter 330. The first signal pair includes a first vibration signal amplitude value S(n) associated with sampling time "n", which is transmitted simultaneously with a first position signal value P(n) associated with sampling time "n". This is followed by a second signal pair, which includes a second vibration signal amplitude value S(n+1) associated with sampling time "n+1", which is transmitted simultaneously with a second position signal value P(n+1) associated with sampling time "n+1", and so on.

[0160] refer to Figure 5 The signal pairs S(i) and P(i) are transmitted to the state parameter extractor 450. The state parameter extractor 450 is configured to generate amplitude peak S based on the time series of the measured sample value S(i). P (r). Peak amplitude S P (r) can depend on the impact force F generated when the protrusion 310 on the inner surface of the rotating shell interacts with the toe 205 of the material loading 30. IMP (See) Figure 2 Regarding this point, it should be noted that when the shell 20 rotates, due to the combination of centrifugal force and gravity, the surface 33 of the material 30 will deviate from the horizontal direction. (As...) Figure 2 As shown, the toe 205 of the filling material 30 is located at the lower edge of the surface 33.

[0161] The state parameter extractor 450 is also configured to be based on the amplitude peak S P The time duration (T) between the occurrence time of (r) and the occurrence time of the rotation reference position of the rotating housing. D To generate the time relationship value R T (j), also known as R T(r). As described above, the time series of the position signal value P(i) can be analyzed to identify the indicator digital position signal E. PD The time of occurrence of the rotational reference position of the rotating housing has been detected by switching from a first value (e.g., "0" (zero)) to a second value (e.g., "1" (one)).

[0162] Figure 7 This is a block diagram illustrating an example of a portion of a state parameter extractor 450. According to one example, the state parameter extractor 450 includes a memory 460. The state parameter extractor 450 is adapted to receive a sequence of measured values ​​S(i) and a signal sequence of positions P(i), as well as the temporal relationship between them, and the state parameter extractor 450 is adapted to provide a time-coupled value sequence S(i), f ROT (i) and P(i). Therefore, a single measurement value S(i) corresponds to the velocity value f. ROT (i) Related, velocity value f ROT (i) indicates the rotational speed of housing 20 when the associated single measurement value S(i) is detected. This will be described in detail below with reference to Figures 8-13.

[0163] Figure 8 is a simplified illustration of an example of memory 460 and its contents, and columns #01, #02, #03, #04 and #05 on the left side of the illustration of memory 460 provide illustrative images intended to show the temporal relationship between the detection time of the encoder pulse signal P(i) (see column #02) and the corresponding vibration measurement value S(i) (see column #03).

[0164] As described above, the analog-to-digital converter 330 operates at an initial sampling frequency f S For analog electrical measurement signal S EA Sampling is performed to generate a digital measurement data signal S MD It can also have essentially the same initial time resolution f. S The encoder signal P is detected, as shown in column #02 of Figure 8.

[0165] Column #01 illustrates the time progression as a series of time slots, each with a duration dt = l / f. Sample ;where f Sample It is related to the analog electrical measurement signal S EA The initial sampling frequency f for sampling S Sampling frequencies that have an integer relationship. According to a preferred example, the sampling frequency f... Sample It is the initial sampling frequency f S According to another example, the sampling frequency f Sample The first reduced sampling frequency f SR1 , with the initial sampling frequency f S In comparison, it reduces M by an integer multiple.

[0166] In column #02 of Figure 8, each positive edge of the encoder signal P is represented by a "1". In this example, positive edges of the encoder signal P are detected in slots 3, 45, 78, and 98, as shown in column #02. According to another example, negative edges of the position signal are detected, which provides an equivalent result to detecting positive edges. According to yet another example, both positive and negative edges of the position signal are detected to obtain redundancy by allowing for later selection of whether to use positive or negative edges.

[0167] Column #03 shows the sequence of vibration sample values ​​S(i). Column #05 shows the corresponding sequence of vibration sample values ​​S(j) when integer decimation is performed. Therefore, when integer decimation is performed by this level, it can be set, for example, to provide an integer decimation factor M=10, and as shown in Figure 8, a vibration sample value S(j) will be provided for every ten samples S(i) (see column #03 in Figure 8) (see column #05 in Figure 8). According to one example, very precise position and time information PT associated with the decimated vibration sample value S(j) is maintained by setting the PositionTime signal in column #04 to the value PT=3, so as to indicate the detection of a positive edge in time slot #03 (see column #02). Therefore, the value of the PositionTime signal after integer decimation indicates the detection time of the position signal edge P relative to the sample value S(l).

[0168] In the example in Figure 8, the amplitude value of the position time signal at sample i=3 is PT=3, and because the decimation factor M=10, sample S(l) is transmitted in time slot 10. This means that the edge is detected in M-PT=10-3=7 time slots before the time slot of sample S(l).

[0169] Therefore, device 150 can operate to process information about the positive edges of encoder signal P(i) in parallel with vibration sample S(i), in order to establish velocity value f from detecting analog signal. ROT The above signal processing maintains the time relationship between the positive edge of the encoder signal P(i) and the corresponding vibration sample value S(i) and / or the integer extracted vibration sample value S(j).

[0170] Figure 9 This shows the operation. Figure 7 A flowchart illustrating an example of the method for the state parameter extractor 450.

[0171] According to one example, the state parameter extractor 450 analyzes (step S#10) the temporal relationship between three consecutively received position signals to determine whether the monitored rotating housing 20 is in a constant speed phase or an acceleration phase. As mentioned above, this analysis can be performed based on information in memory 460 (see Figure 8).

[0172] If the analysis shows that there are the same number of time slots between the position signals, the state parameter extractor 450 determines (in step #20) that the speed is constant, and in this case, proceeds to step S#30.

[0173] In step S#30, the state parameter extractor 450 can calculate the duration between two consecutive position signals by multiplying the duration of the time slot dt = 1 / fs by the number of time slots between the two consecutive position signals. The rotational speed can be calculated as follows: [Formula omitted for brevity]

[0174] V=1 / (n diff dt),

[0175] Where, n diff = The number of time slots between two consecutive position signals. During the constant velocity phase, all sample values ​​S(j) associated with the three analyzed position signals (see column #05 in Figure 8) can be assigned the same velocity value f. ROT =V=1 / (n) diff dt), as described above. Thereafter, step S#10 can be performed again for the next three consecutively received position signals. Alternatively, when repeating step S#10, the previous third position signal P3 will be used as the first position signal P1 (i.e., P1:=P3) to determine whether the speed is about to change.

[0176] If the analysis (step S#10) shows that the number of time slots between the first and second position signals is different from the number of time slots between the second and third position signals, then the state parameter extractor 450 determines (in step S#20) that the monitored rotating housing 20 is in an acceleration phase. Acceleration can be positive, i.e., an increase in rotational speed, or negative, i.e., a decrease in rotational speed, also known as deceleration.

[0177] In the next step S#40, the state parameter extractor 450 operates to establish instantaneous velocity values ​​during the acceleration phase and associates each measured data value S(j) with an instantaneous velocity value Vp, which indicates the detection of a sensor signal (Sj) corresponding to that data value S(j). EA The value is the rotational speed of the mill casing being monitored.

[0178] According to one example, the state parameter extractor 450 operates to establish instantaneous velocity values ​​through linear interpolation. According to another example, the state parameter extractor 450 operates to establish instantaneous velocity values ​​through nonlinear interpolation.

[0179] Figure 10 This shows the execution Figure 9 A flowchart illustrating an example of the method in step 40. According to one example, it is assumed that the acceleration has a constant value for the duration between two mutually adjacent position indicators P (see column #02 in Figure 8). Therefore, when

[0180] • The position indicator P is transmitted once every time the rotation is completed, and

[0181] If the gear ratio is 1 / 1, then

[0182] - The angular distance traveled by the rotating housing 20 between two adjacent position indicators P is one (1) revolution, which can also be expressed as 360 degrees, and

[0183] - Duration is T=n diff dt,

[0184] ■wherein, n diff It is the number of time slots for the duration dt between two adjacent position indicators P.

[0185] Referring to Figure 8, the first position indicator P is detected in time slot i1=#03, and the next position indicator P is detected in time slot i2=#45. Therefore, the duration is n. diff1 =i2-i1=45-3=42 time slots.

[0186] Therefore, in step S#60 (see Figure 8) Figure 10 The state parameter extractor 450 operates to establish a first number of time slots n between the initial two consecutive position signals P1 and P2, i.e., between position signal P (i=3) and position signal P (i=45). diff1 .

[0187] In step S#70, the state parameter extractor 450 operates to calculate the first rotational speed value VT1. The first rotational speed value VT1 can be calculated as follows:

[0188] VT1=1 / (n) diff1 dt),

[0189] VT1 is a speed expressed in revolutions per second.

[0190] n diff1 = The number of time slots between two consecutive position signals; and

[0191] dt is the duration of a time slot, expressed in seconds.

[0192] Since it is assumed that the acceleration has a constant value over the duration between two adjacent position indicators P, the calculated first velocity value VT1 is assigned to the intermediate time slot between the two consecutive position signals (step S#80).

[0193] Therefore, in this example, where, in time slot i P1 =#03 detected the first position indicator P1, and in time slot i P2 The next position indicator P2 was detected in #45; the first intermediate time slot is:

[0194] Time slot i P1-2 =i P1 +(i P2 -i P1 ) / 2=3+(45-3) / 2=3+21)=24.

[0195] Therefore, in step S#80, the first rotational speed value VT1 can be assigned to a time slot (e.g., time slot i=24), which represents a time point earlier than the time point at which the second position signal edge P (i=45) is detected, see Figure 8.

[0196] Assigning the speed value retrospectively to the time slot representing the time point between two consecutive position signals advantageously reduces the inaccuracy of the speed value significantly. While existing methods for obtaining the instantaneous rotational speed of the tumbling mill housing 20 may be satisfactory for establishing a constant speed value at several different rotational speeds, the existing solution appears unsatisfactory when used to establish the speed value of the rotating tumbling mill housing 20 during the acceleration phase.

[0197] In contrast, the method described in the example in the document enables the establishment of speed values ​​with a favorable small degree of inaccuracy, even during the acceleration phase.

[0198] In the subsequent step S#90, the state parameter extractor 450 operates to establish a second number of time slots n between the next two consecutive position signals. diff2 In the example in Figure 8, this is the number of time slots n between time slot 45 and time slot 78. diff2 That is, n diff2 =78-45=33.

[0199] In step S#100, the state parameter extractor 450 calculates the second rotational speed value VT2. The second rotational speed value VT2 can be calculated as:

[0200] VT2=Vp61=1 / (ndiff2 dt),

[0201] Where, n diff2 = The number of time slots between the next two consecutive position signals P2 and P3. Therefore, in the example in Figure 8, n diff2 =33, which is the number of time slots between time slot 45 and time slot 78.

[0202] Since it can be assumed that the acceleration has a constant value over the duration between two adjacent position indicators P, the calculated second velocity value VT2 is assigned (step S#110) to the intermediate time slot between the two consecutive position signals.

[0203] Therefore, in the example of Figure 8, the calculated second velocity value VT2 is assigned to time slot 61 because 45 + (78 - 45) / 2 = 61,5. Thus, the velocity at time slot 61 is set as follows:

[0204] V(61):=VT2.

[0205] Therefore, in this example, where a position indicator P is detected in time slot i2=#45 and the next position indicator P is detected in time slot i3=#78; the second intermediate time slot is the integer part of the following:

[0206] i P2-3 =i P2 +(i P3 -i P2 ) / 2=45+(78-45) / 2=45+33 / 2=61.5

[0207] Therefore, time slot 61 is the second intermediate time slot i P2-3 .

[0208] Therefore, in step S#110, the second speed value VT2 can advantageously be assigned to a time slot (e.g., time slot i=61) that represents a time point earlier than the time point at which the third position signal edge P (i=78) is detected, see Figure 8. This feature enables real-time monitoring of the rotational speed with a slight delay, while achieving higher accuracy in speed detection.

[0209] In the next step S#120, the first acceleration value for the relevant time period is calculated. The first acceleration value can be calculated as:

[0210] a12 = (VT2 - VT1) / ((i VT2 -i VT1 ) dt)

[0211] In the example in Figure 8, the second velocity value VT2 is assigned to time slot 61, therefore i VT2 =61, the first velocity value VT1 is assigned to time slot 24, therefore i VT1 =24.

[0212] Therefore, since dt = 1 / fs, the acceleration value can be set as:

[0213] a12=fs (VT2-VT1) / (i VT2 -i VT1 )

[0214] The time period used between time slot 24 and time slot 60, as shown in the example in Figure 8.

[0215] In the next step S#130, the state parameter extractor 450 operates to associate the established first acceleration value a11 with the valid time slots of the established acceleration value a12. This can be all time slots between the time slot of the first velocity value VT1 and the time slot of the second velocity value VT2. Therefore, the established first acceleration value a12 can be associated with each time slot of the duration between the time slot of the first velocity value VT1 and the time slot of the second velocity value VT2. In the example of Figure 8, these are time slots 25 to 60. This is shown in column #07 of Figure 8.

[0216] In the next step S#140, the state parameter extractor 450 operates to establish a velocity value s(j) associated with the duration for which the established acceleration value is valid. Therefore, a velocity value is established for each time slot.

[0217] Associated with the measured value s(j), and

[0218] It is associated with the first acceleration value a12 established.

[0219] During linear acceleration, i.e., when the acceleration a is constant, the velocity at any given time point is given by the following formula:

[0220] V(i) = V(i-1) + a dt,

[0221] in,

[0222] V(i) is the instantaneous velocity at time slot i.

[0223] V(i-1) is the instantaneous velocity at the time point immediately preceding time slot i.

[0224] 'a' represents acceleration.

[0225] dt is the duration of the time slot.

[0226] According to one example, the velocity can be calculated continuously in this way from time slot 25 to time slot 60, as shown in column #08 of Figure 8. Thus, the instantaneous velocity value Vp associated with the detected measurements Se(25), Se(26), Se(27)... Se(59) and Se(60) can be established in this way, with the detected measurements associated with the acceleration value a12 (see column #08 in Figure 8 along with columns #03 and columns #07 for time slots 25 to 60).

[0227] Therefore, an instantaneous velocity value S(j) [see column #05] associated with the detected measurements S(3), S(4), S(5) and S(6) can be established in this way, which are associated with the acceleration value a12.

[0228] According to another example, the instantaneous velocity of time slot 30 associated with the first measurement s(j) = S(3) can be calculated as:

[0229] V(i=30) = Vp30 = VT1 + a (30-24) dt = Vp24 + a 6 dt

[0230] The instantaneous velocity of time slot 40 associated with the first measured value s(j)=S(4) can be calculated as:

[0231] V(i=40) = Vp40 = VT1 + a (40-24) dt = Vp40 + a 16 dt

[0232] Or it can be calculated as:

[0233] V(i=40) = Vp40 = V(30) + (40-30) dt = Vp30 + a 10 dt

[0234] The instantaneous velocity of time slot 50, which is associated with the first measured value s(j) = S(5), can then be calculated as:

[0235] V(i=50) = Vp50 = V(40) + (50-40) dt = Vp40 + a 10 dt

[0236] Furthermore, the instantaneous velocity of time slot 60 associated with the first measured value s(j) = S(6) can subsequently be calculated as:

[0237] V(i=60) = Vp50 + a 10 dt

[0238] As described above, when the measured sample value S(i) [see column #03 in Figure 8] associated with the established acceleration value has been associated with the instantaneous velocity value, a data array including the time series of the measured sample value S(i), each value associated with the velocity value V(i), can be transmitted at the output of the state parameter extractor 450. ROT (i) Related.

[0239] Alternatively, if a sampling rate is desired, it can be done as follows: As described above, when the measured sample value S(j) [see column #05 in Figure 8] associated with the established acceleration value has been associated with the instantaneous velocity value, a data array including the time series of the measured sample value S(j), each value associated with the velocity value V(j), f ROT (j) Related.

[0240] refer to Figure 11 This describes another example of the method. According to this example, the state parameter extractor 450 operates to record (see...). Figure 11 The position signal (E) in step S#160) P The time series of position signal values ​​P(i) of a given location, such that a first temporal relationship exists between at least some recorded position signal values ​​(P(i)), for example, between a first position signal value P1(i) and a second position signal value P2(i). diff1 According to one example, the second position signal value P2(i) is received and recorded in time slot (i), which arrives ndiffl time slots after the first position signal value P1(i) is received (see [reference]). Figure 11 Step S#160 in the document. Then, the third position signal value P3(i) is received and recorded (see step S#160 in the document). Figure 11 In step S#170), in time slot (i), the second position signal value P2(i) arrives ndiff2 time slots later.

[0241] like Figure 11 As shown in step S#180, the state parameter extractor 450 can operate to calculate the relational value.

[0242] a12 = ndiff1 / ndiff2

[0243] If the relation value a12 is equal to one (unity) or approximately equal to one, the state parameter extractor 450 operates to determine that the speed is constant, and the speed can continue to be calculated according to the constant speed phase method.

[0244] If the relation value a12 is greater than one, then the relation value indicates a percentage increase in speed.

[0245] If the relation value a12 is less than one, then the relation value indicates a percentage decrease in speed.

[0246] The relation value a12 can be used to calculate the velocity V2 at the end of the time series based on the velocity VI at the beginning of the time series, for example, as...

[0247] V2=a12 V1

[0248] Figure 12 This shows the execution Figure 9 The flowchart illustrates an example of the method in step S#40. According to one example, it is assumed that the acceleration has a constant value over the duration between two adjacent position indicators P (see column #02 in Figure 8). Therefore, when

[0249] • The position indicator P is transmitted once every time the rotation is completed, and

[0250] If the gear ratio is 1 / 1, then

[0251] - The angular distance between two adjacent position indicators P is one revolution, which can also be expressed as 360 degrees.

[0252] - The duration is T=n dt,

[0253] ■ Where n is the number of time slots for the duration dt between the first two adjacent position indicators P1 and P2.

[0254] In step S#200, the first rotational speed value VT1 can be calculated as:

[0255] VT1 = 1 / (n diff1 dt),

[0256] VT1 is a speed expressed in revolutions per second.

[0257] ndiff1 = the number of time slots between two consecutive position signals; and

[0258] dt is the duration of the time slot, expressed in seconds. The value of dt can be, for example, the initial sampling frequency f. S The reciprocal of.

[0259] Since it is assumed that the acceleration has a constant value over the duration between two adjacent position indicators P, the calculated first velocity value VT1 is assigned to the intermediate value between the two consecutive position signals P(i) and P(i+ndiff1). First intermediate time slot .

[0260] In step S#210, the second velocity value VT2 can be calculated as:

[0261] VT2 = 1 / (ndiff2) dt),

[0262] VT2 is a speed expressed in revolutions per second.

[0263] ndiff2 = the number of time slots between two consecutive position signals; and

[0264] dt is the duration of the time slot, expressed in seconds. The value of dt can be, for example, the initial sampling frequency f. S The reciprocal of.

[0265] Since it is assumed that the acceleration has a constant value over the duration between two adjacent position indicators P, the calculated second velocity value VT2 is assigned to the intermediate value between the two consecutive position signals P(i+ndiff1) and P(i+ndiff1+ndiff2). Second intermediate time slot .

[0266] After that, the speed difference V Delta It can be calculated as:

[0267] V Delta =VT2 - VT1

[0268] The speed difference V Delta The value can be divided by the number of time slots between the second and first intermediate time slots. The resulting value indicates the velocity difference dV between adjacent time slots. Of course, as mentioned above, this assumes that the acceleration is constant.

[0269] The instantaneous speed value associated with the selected time slot can then be calculated based on the first rotational speed value VT1 and the value indicating the speed difference between adjacent time slots.

[0270] As described above, when the measured sample value S(i) associated with the time slot between the first and second intermediate time slots has been associated with the instantaneous velocity value, a data array including the time series of the measured sample values ​​S(i) is transmitted at the output of the state parameter extractor 450, each value being associated with a velocity value V(i). The instantaneous velocity value V(i) can also be referred to as f ROT (i).

[0271] In summary, based on some examples, the first instantaneous velocity value VT1 can be established based on the following factors:

[0272] The angular distance δ-FI between the first position signal P1 and the second position signal P2 p1-p2 And depends on:

[0273] The corresponding duration δ-T p1-p2 =t P2 -t P1 .

[0274] Subsequently, the second instantaneous velocity value VT2 can be established based on the following factors:

[0275] The angular distance δ-FI between the second position signal P2 and the third position signal P3 P2-P3 And depends on:

[0276] The corresponding duration δ-T p2-p3 =t P2 -t P1 .

[0277] Subsequently, the instantaneous velocity value of the rotating shell 20 can be established by interpolation between the first instantaneous velocity value VT1 and the second instantaneous velocity value VT2.

[0278] In other words, based on the example, it can be based on the angular distance δ-FI p1-p2 δ-FI P2-P3 Two instantaneous velocity values ​​VT1 and VT2 are established by the corresponding duration between the three consecutive position signals, and thereafter, the instantaneous velocity value of the rotating housing 20 can be established by interpolation between the first instantaneous velocity value VT1 and the second instantaneous velocity value VT2.

[0279] Figure 13 This is a diagram showing a series of time-sequential position signals P1, P2, P3, ..., where each position signal P indicates a complete revolution of the monitored housing 20. Therefore, the time value, in seconds, increases to the right along the horizontal axis.

[0280] The vertical axis indicates the rotational speed, graded in revolutions per minute (RPM).

[0281] refer to Figure 13 This illustrates the effect of a method based on an example. The first instantaneous velocity value V(t1) = VT1 can be established according to the following formula:

[0282] The angular distance δ-FI between the first position signal p1 and the second position signal P2 p1-p2 And depends on:

[0283] The corresponding duration δ-T p1-p2 =tP2 -t P1 By using the angular distance δ-FI p1-p2 Divide by the corresponding duration (t) P2 -t P1 The obtained velocity value represents the velocity V(t1) of the rotating shell 20 at the first intermediate time point t1, also known as mtp (intermediate time point), such as... Figure 13 As shown.

[0284] Subsequently, the second instantaneous velocity value V(t2) = VT2 can be established according to the following formula:

[0285] The angular distance δ-FI between the second position signal P2 and the third position signal P3 depends on:

[0286] The corresponding duration is δ-T2-3=t P3 -t P2 .

[0287] like Figure 13 As shown, by dividing the angular distance δ-FI by the corresponding duration (t) P3 -t P2 The obtained velocity value represents the velocity V(t2) of the rotating shell 20 at the second intermediate time point t2 (second mtp).

[0288] Subsequently, the instantaneous velocity value between the first instantaneous velocity value VT1 and the second instantaneous velocity value VT2 can be established by interpolation between the first intermediate time point and the second intermediate time point, as shown by curve f. ROTint As shown.

[0289] In mathematics, this can be expressed by the following formula:

[0290] V(t12) = V(t1) + a (t12 – t1)

[0291] Therefore, if the velocity of the shell 20 can be detected at two time points (t1 and t2), and the acceleration a is constant, the instantaneous velocity at any time point can be calculated. Specifically, the shell velocity V(t12) at time T12 (the time point after t1 and before t2) can be calculated using the following formula:

[0292] V(t12) = V(t1) + a (t12 – t1)

[0293] in,

[0294] a is acceleration, and

[0295] t1 is the first intermediate time point t1 (see Figure 13 ).

[0296] The speed value described above can be established and referenced by executing the corresponding methods and steps. Figure 20 , Figure 21 The compensation extraction is as described in Figure 22, and this can be implemented by a computer program 94 stored in memory 60, as described above. The computer program can be executed by DSP 50. Alternatively, the computer program can be executed by a field-programmable gate array (FPGA).

[0297] When processor 350 executes the corresponding program codes 380, 394, and 410, the speed value f as described above... ROT (i) can be established by the analysis device 150, as described above. Figure 4 The data processor 350 may include a central processing unit 350 for controlling the operation of the analysis device 14. Alternatively, the processor 50 may include a digital signal processor (DSP) 350. According to another example, the processor 350 includes a field-programmable gate array (FPGA). The operation of the FPGA may be controlled by the central processing unit 350, which may include the DSP 350.

[0298] Identification of data related to the toe of the feed in the tumbling mill

[0299] As described above, the tumbling mill housing 20 has an inner housing surface 22 facing the chamber 25, the inner housing surface 22 including a plurality of protrusions 310, also referred to as lifters, which can be configured to engage and lift the material 30 when the housing rotates about the axis 60 (see, for example, see...). Figure 2 The number of protrusions 310 provided on the inner shell surface 22 facing the chamber 25 is represented by the variable L in this document. Although Figure 2 The example shown has twelve protrusions 310, i.e., L=12, but the number L of protrusions 310 can be higher or lower. According to some embodiments, the number L of protrusions 310 can be at least one, i.e., the number L of protrusions 310 can be L=1. According to some embodiments, the number L of protrusions 310 can be any number greater than L=1. According to some embodiments, the number L of protrusions 310 can be any value in the range of L=2 to L=60. According to some embodiments, the number L of protrusions 310 can be any value in the range of L=2 to L=35.

[0300] The number L of protrusions 310 is an important factor related to the analysis of vibrations caused by the rotation of the mill housing 20. The inventors recognized that the interaction between the protrusions 310 and the toe of the feed material forces the feed material to accelerate in the direction of movement of the protrusions 310, thereby causing mechanical vibration V. IMPThe inventors also recognized that this mechanical vibration V caused by the interaction between the protrusion 310 and the toe of the filling material... IMP It will be repetitive, that is, there exists a repetition frequency f. R . refer to Figure 2 It should be noted that this illustrates the rotary mill housing 20 when the protrusion 310C impacts the toe 205 of the material charge 30. The impact of the protrusion 310C on a large amount of material in the toe 205 causes a large amount of material in the toe to move in the direction A of the protrusion 310C. ACC The upward acceleration results in a force F on the leading edge surface of the protrusion 310C. IMP By the way, this impact force F IMP It can be estimated to be on the order of magnitude:

[0301] F IMP =m 205 a 205

[0302] in,

[0303] m 205 It is the mass of the accelerated toe.

[0304] a 205 It is the amount of acceleration of the toes.

[0305] Therefore, the measured signal S MD (For example, see) Figure 5 It may include at least one vibration signal feature S of the vibration motion of the mill housing 20, which depends on the rotational motion. FIMP The vibration signal feature S FIMP With repetition frequency f R The repetition frequency depends on the rotational speed f of the rotating mill housing 20. ROT .

[0306] In addition, vibration signal characteristics S FIMP The magnitude of the peak amplitude appears to depend on the impact force F. IMP Size.

[0307] Therefore, the inventors concluded that the vibration signal characteristic S FIMP The measured value of energy or amplitude seems to indicate the impact force F IMP Size.

[0308] Vibration signal characteristics S depending on the vibration motion of the mill casing 20 due to its rotational motion FIMP The presence of this information can therefore provide an indication of the loading toe 205 of the monitored mill housing 20. In fact, the vibration signal characteristics S depend on the vibrational motion of the mill housing 20 due to its rotational movement. FIMPIt can provide an indication of the position of the loading toe 205 of the monitored tumbler housing 20, indicating the position relative to a reference position value.

[0309] The inventors concluded that the mechanical vibration V caused by the interaction between the protrusion 310 and the loading toe is IMP repetition frequency f R The number L of protrusions 310 provided on the inner housing surface 22 and the rotational speed f of the housing 20 depend on the number of protrusions 310 provided on the inner housing surface 22. ROT .

[0310] When the monitored tumbling mill housing 20 constant When rotating at a certain speed, this repetition frequency f R It can be discussed based on repetition per unit of time or repetition per revolution of the monitored housing, without distinguishing between the two. However, if the mill housing 20 is... variable With increasing rotational speed, things become more complicated, as discussed elsewhere in this disclosure, for example, by combining... Figure 20 , Figure 21 , Figure 22A , Figure 22B and Figure 22C In fact, regarding the ambiguity of the detected vibration signal, it seems that even a very small change in the rotational speed of the mill casing can have a significant adverse effect on the quality of the detected signal. Therefore, the rotational speed f of the mill casing 20... ROT Highly accurate detection is therefore crucial.

[0311] Furthermore, the inventors recognized that not only mechanical vibration V IMP The amplitude, and mechanical vibration V IMP The timing of the occurrence of the signal S can indicate data related to the loading toe 205 in the tumbling mill. Therefore, the measurement signal S MD (For example, see) Figure 5 It may include at least one vibration signal amplitude component S of the vibration motion of the mill housing 20, which depends on the rotational motion. FIMP ;

[0312] Wherein, the vibration signal amplitude component S FIMP With repetition frequency f R The repetition frequency is:

[0313] The rotational speed f of the mill housing 20 depends on the rotational motion. ROT And also

[0314] The number L of protrusions 310 provided on the inner shell surface 22 of the mill housing 20 depends on; and

[0315] There is a temporal relationship among the following items:

[0316] The amplitude component S of the repetitive vibration signal FIMP The emergence of, and

[0317] Having a second repetition frequency f P The position signal P(i) appears, the frequency of which depends on the rotational speed f of the rotating mill housing 20. ROT .

[0318] Regarding a constant rotational speed, the inventors concluded that if the rotational speed f ROT If it is constant, then the digital measurement signal S includes the time series of vibration sample values ​​S(i). MD With repetition frequency f R The repetition frequency depends on the number L of protrusions 310 provided on the inner housing surface 22.

[0319] The state parameter extractor 450 may optionally include components coupled to receive digital measurement signals S. MD Or it depends on the digital measurement signal S MD (See) Figure 15 The Fast Fourier Transform (FFT) of the signal is performed. The analysis of the tumbling mill with rotating housing 20 is conducted at rotational frequencies f higher than those of the rotating housing 20. ROT The signal frequency may be of interest. In this case, the rotational frequency f of the housing 20 is... ROT This can be referred to as "first order". If the signal of interest appears ten times per revolution of the casing, then this frequency can be called the 10th order, i.e., the repetition frequency f. R (Measured in Hz) Divide by rotational speed f ROT (Measured in revolutions per second rps) equals 10Hz / rps, i.e., Oi = fR / f ROT =10th order.

[0320] Let the maximum order be Y, and the total number of frequency bins in the FFT be Z. The inventors conclude, based on an example, that the following formula applies:

[0321] Oi Z=X Y.

[0322] In contrast, X=Oi Z / Y, where

[0323] Y is the maximum order; and

[0324] Z is the number of frequency regions in the spectrum generated by the FFT, and

[0325] Oi is the number L of protrusions 310 in the monitored tumbling mill housing.

[0326] The variables Y, Z, and Oi should be set so that variable X is a positive integer. Referring to the example above, it should be noted that the FFT analyzer is configured to receive a reference signal, i.e., the position marker signal value PS, once per revolution of the rotating housing 20. (As in...) Figure 2 The position marking device 180 can be disposed on the outer wall surface of the housing 20, so that when the housing 20 rotates around the rotation axis 60, the position marking 180 passes the position sensor 170 once for each rotation of the housing, thereby causing the position sensor 170 to generate a rotation mark signal value PS.

[0327] Incidentally, referring to the example of the FFT analyzer setup above, the resulting integer X can indicate the number of revolutions of the monitored mill housing 20 during the analysis of the digital signal S. MD According to one example, the variables Y, Z, and Oi mentioned above can be set via the HCI 210, 210S (see, for example, Figure 1 and / or...). Figure 5 and / or Figure 15 ).

[0328] As mentioned above, the protrusion 310 can also be referred to as the elevator 310. Consider when the digital measurement signal S... MD When transmitted to the FFT analyzer: In this case, when the FFT analyzer is set up for 10 spikes (L=10) and Z=160 frequency bins, and the user is interested in analyzing frequencies up to Y=100, then the value of X becomes X=Oi. Z / Y=10 160 / 100=16.

[0329] Therefore, when Z=160 frequency bins are required, measurements need to be performed over 16 housing rotations (X=16), with the number of protrusions being L=10; and the user is interested in analyzing frequencies up to Y=100. Combined with the settings of the FFT analyzer, the order value Y can indicate the digital measurement signal S. MD The highest frequency to be analyzed.

[0330] According to some embodiments, when the FFT analyzer is configured to receive a reference signal, i.e., the position marker signal value PS, once per revolution of the rotating housing 20, the settings of the FFT analyzer should meet the following criteria:

[0331] The integer value Oi is set to equal L, which is the number of protrusions in the housing 20, and

[0332] Choose settable variables Y and Z to make the mathematical expression Oi Z / Y become positive integers. In other words: when the integer value Oi is set to equal L, then the settable variables Y and Z should be set to integer values ​​so that variable X is a positive integer.

[0333] Where X=Oi Z / Y.

[0334] As an example, the number of bins Z can be set by selecting a value Z from a set of values. The optional value set for the frequency resolution Z can include:

[0335] Z=200

[0336] Z=400

[0337] Z=800

[0338] Z=1600

[0339] Z=3200

[0340] An example of the constant speed phase

[0341] Such as combination Figure 9 As described in step S#30, the state parameter extractor 450 can identify the constant speed phase, i.e., the constant rotational speed f of the housing 20. ROT The state.

[0342] Figure 14A and Figure 14B Another example is shown: a cross-sectional view of the intermediate portion 98 of the rotary mill housing 20 during operation. This view can be, for example, along... Figure 1A The line AA is cut off. According to... Figure 14A For example, the tumbling mill housing 20 has six protrusions 310, which are configured to engage material loading 30 when the housing rotates about the shaft 60, i.e., the quantity L=6.

[0343] The inner diameter of housing 20 can be, for example, 600 cm, and the rotational speed can be constant, for example, 13.6 revolutions per minute. For the purposes of this example, the sampling frequency is such that there are n = 7680 samples per revolution, and the rotational speed of housing 20 is f. ROT .

[0344] As described above, the housing 20 can rotate about the rotation axis 60, so the position sensor 170 can generate a position signal Ep to indicate the instantaneous rotational position of the housing 20. A position mark 180 can be disposed on the outer surface of the housing 20, such that when the housing 20 rotates about the rotation axis 60, the position mark 180 passes the position sensor 170 once for each revolution of the housing, thereby causing the position signal Ep to exhibit the position mark signal value P. S Each such location is marked with a signal value P. S Indicates the stationary position, that is, the position of the stationary stator.

[0345] Figure 14AThe rotational position of the rotating housing 20 is shown, wherein the position mark 180 is located at the same rotational position as the static position sensor 170, and the protrusion 310A has passed through the toe 205. The protrusion 310A is followed by the adjacent protrusion 310B.

[0346] Figure 14B Another rotational position of the rotating housing 20 is shown, compared to Figure 14A The location shown is a little later. Figure 14B In the middle, the adjacent protrusion 310B is located at the point of impact with the toe 205. The impact time causes vibration V. IMP This leads to signal characteristic events in the vibration signal. Therefore, Figure 14B The rotational position shown is event position 205E of the rotating housing 20. Event position 205E is the rotational position of the rotating housing 20 when the protrusion impacts the toe 205. Therefore, event position 205E indicates the toe position 205. Therefore, as... Figure 14B As shown, the position 205E of the toe 205 can be represented as a percentage of the distance between two adjacent static positions P3 and P4.

[0347] Each revolution produces a position marker signal value P. S And the rotational speed f ROT When constant or approximately constant, there will be a constant or approximately constant number of vibration sample values ​​S(i) for each revolution of the mill housing 20. For the purposes of this example, the position signal P(0) indicates vibration sample i=0, as shown in Table 2 (see below). For the purposes of this example, the position of the position signal P(0) relative to the housing 20 may be insignificant, as long as the repetition frequency f P The rotational speed f of the grinding housing 20 depends on the rotational motion. ROT Therefore, if the position signal E of the housing 20 rotates once... P There is a pulse Ps. For each revolution of the digital position signal, there will be a position signal value P(i)=1, and the rest of the position signal values ​​will be zero.

[0348] Table 2

[0349]

[0350] Therefore, at a certain constant velocity f ROT Each revolution may have n time slots, as shown in Table 2, where n can be a positive integer. In the example in Table 2, n = 7680.

[0351] One position signal P is generated for each revolution. S We know that the position signal will repeat once every n time slots because the rotational speed f ROT It is constant. Therefore, multiple virtual position signals P can be generated through calculation. CIn one example, consider generating a virtual location signal P. C A virtual position signal P is provided for each protrusion 310. C It can be used to establish time relationships between the following items:

[0352] The amplitude component S of the repetitive vibration signal FIMP The emergence of, and

[0353] The position signal P(i) appears, which has a second repetition frequency f. P The repetition frequency depends on the rotational speed f of the rotating mill housing 20. ROT .

[0354] The mill housing has L equidistant protrusions 310, and a position signal P is generated for each revolution. S and constant speed f ROT It can generate a virtual position signal P for each protrusion. C Thus, the position signal P S P C The total number is evenly distributed. Each such location is marked with a signal value P. S and P C Indicates the stationary position, that is, the position of the stationary stator, such as... Figure 14A and Figure 14B The "P" in S "and "P C As shown in the figure.

[0355] Therefore, as shown in Table 3, when n time slots are provided per revolution, the position signal P S or P C This will appear at the location of every n / L sample values. In Table 3, n=7680, L=6, therefore a location signal P is provided for every 1280 samples. C The calculated position signal is represented as 1C.

[0356] As shown in the example in Figure 14, the location marker signal value P S and P C Indicate L fixed positions P1, P2, P3, P4, P5 and PL, where L = 6, because there are 6 protrusions 310 in the housing 20 shown.

[0357] It can be assumed that the position of the toe 205 of the mill is approximately constant during a single rotation of the mill housing 20. In other words, the position of the toe 205 is approximately fixed.

[0358] Due to the amplitude component S of the vibration signal FIMP S P It is produced by the interaction of the protrusion and the toe of the filling (see...). Figure 14BTherefore, each protrusion 310 will have a vibration signal amplitude component S. FIMP The frequency of Sp repeats. Therefore, we can assume that:

[0359] The amplitude component S of the repetitive vibration signal FIMP S p The emergence of, and

[0360] The temporal relationship between the occurrences of position signals P and PC is approximately constant for each of the L data blocks, in this example, L=6.

[0361] Table 3 illustrates the principle of the time progression of the position signal value P(i), and the calculated position signal value P(i) is represented as "1C".

[0362] Table 3

[0363]

[0364] Table 4

[0365]

[0366]

[0367] Table 5

[0368]

[0369]

[0370] As described above, the housing 20 can rotate about the rotation axis 60, so the position sensor 170, which is fixedly mounted, can generate a position signal Ep, which has a series of housing position signal values ​​P. S This is used to indicate the instantaneous rotational position of the housing 20. For example... Figure 23 As shown, the position mark 180 can be set on the outer surface of the housing 20, such that when the housing 20 rotates about the rotation axis 60, the position mark 180 passes the position sensor 170 during one rotation of the housing 20, thereby causing the position sensor 170 to generate a rotation mark signal value P. S .

[0371] As described above, the position sensor 170 can generate a position signal Ep, which has a series of housing position signal values ​​P. S This is used to indicate the instantaneous rotational position of housing 20 when housing 20 rotates. Referring to Table 2-4 in this document, such a marker signal value P... S It is displayed as "1" in column #2 of Table 2-4.

[0372] When the rotating housing is equipped with a position marking device 180, it will provide a marking signal value P once per revolution. S In Table 2-4, the signal value P is marked. S It is displayed as "1" in column #2. There are L equidistant protrusions 310 in the mill housing, and a position signal P and a constant speed f are provided for each revolution. ROT It is possible to generate a virtual position signal P for each protrusion. C This makes the position signals P and P C The total number is evenly distributed, as described above. Therefore, as shown in Table 3, when n time slots are provided per revolution, the position signal P or P C This will appear at the location of every n / L sample values. In Table 3, n=7680 and L=6, therefore a location signal P is provided for every 1280 samples. C The calculated position signal indication is 1C.

[0373] It is believed that a marker signal value P is provided once per revolution. S (Indicated as "1" in column #2 of Table 2-4) and the virtual position signal value P is generated in a uniformly distributed manner. C At this time, the equidistant positions of the protrusions 310 are important, so that when n time slots are provided per revolution in the housing position signal value sequence to indicate the instantaneous rotational position of the housing 20, the position signal P or P C The positions of the rotating marker signal P will appear at every n / L sample value, as shown in Table 3. In Table 3, the actual detected rotating marker signal value P... S This is reflected as "1" (see column #2 in Table 3, time slot "0" and time slot "7680"), and the virtual position signal value P C This is reflected as "1C" (see column #2 in Table 3, slot "0" and slot "7680").

[0374] This is believed to be important for some embodiments of this disclosure because the position mark 180 results in the generation of a position reference signal value, and the protrusion 310 results in the generation of signal events, such as amplitude peaks in a vibration signal, when material is engaged in the rotary mill load (see, for example, Figure 1 and...). Figure 15 Reference S in EA S MD Se(i), S(j), S(q)). Furthermore, the duration between the occurrence of the position reference signal value and the occurrence of the signal event in the vibration signal can indicate the internal state of the mill in operation, as discussed elsewhere in this disclosure, and this duration is caused by the protrusion 310 engaging the material in the rotating mill housing charge.

[0375] Table 4 is a schematic diagram of the first block (i.e., block I) with n / L = 7680 / 6 = 1280 consecutive time slots. It should be understood that if a constant velocity phase exists during the complete rotation of the housing 20 (see...),... Figure 9 If ), then each of blocks I through VI (see Table 3) will have the same appearance as block I shown in Table 4.

[0376] According to embodiments of this disclosure, referring to column #03 in Table 4, the vibration sample value S(i) is analyzed to detect vibration signal characteristics S. FIMP Vibration signal characteristics S FIMP This can be represented as the peak amplitude sample value S. P According to an example, referring to column #03 in Table 4, the vibration sample value S(i) is analyzed by a peak detector to detect the peak sample value S. P Referring to Table 5, peak analysis results in the detection of the highest vibration sample amplitude value S(i). In the example shown, the vibration sample amplitude value S (i=760) is detected as maintaining the highest peak value S. P .

[0377] Peak S has been detected P Located in time slot 760, the amplitude component S of the repetitive vibration signal can be established. P The time relationship between the occurrence of the position signal P(i) and the occurrence of the position signal P(i) is shown in Table 5. In Table 5, the time slots for transmitting the position signal P(i) are represented as 0% and 100%, respectively, and all time slots in between can be marked with their corresponding positions, as shown in column #02 of Table 5. As shown in the example in column #02 of Table 5, the time position of time slot i=760 is 59% of the time distance between time slot i=0 and time slot i=1280. In other words, 760 / 1280 = 0.59 = 59%.

[0378] Therefore, the inventors concluded:

[0379] The amplitude component S of the repetitive vibration signal FIMP The time relationship between the occurrence of the signal and the occurrence of the position signal P(i) can be used as an indication of the relative physical position of the loading toe 205 between two consecutive protrusions 310 in the rotating housing 20.

[0380] Therefore, the percentage expressed as the distance between two adjacent leading edges can be obtained by the following formula (see Figure 2 The positions of 312C and 312D in the toe region 205 (see Table 5) are as follows:

[0381] From the first reference signal appearing in sample number N0=0 to sample number N B The total number of samples in which the second reference signal appears in =1280 (N) B -N0= NB -0= N B =1280) to count, and

[0382] From the occurrence of the first reference signal at N0=0 to the occurrence of the signal at sample number N P Peak amplitude value S at the point P The number of other samples (N) P -N0= N P -0= N P ) to count, and

[0383] Based on the other quantity N P and the total number N B Generate the first time relation (R) T (r); T D ;FI(r)). This can be summarized as:

[0384] R T (r)=R T (760) = (N) P -N0) / (N B -N0)=(760-0) / (1280-0)=0.59=59%

[0385] Therefore, the relative toe position can be derived from the following formula:

[0386] The total number of samples (N) from the occurrence of the first reference signal to the occurrence of the second reference signal. B ) to count, and

[0387] From the appearance of the first reference signal to the appearance of sample number N P Peak amplitude value S at the point P Another number of samples (N) P ) to count, and

[0388] Based on the number of samples N P With the total number of samples (i.e., N) B The first time relation (R) is generated from the relationship between the two. T (r); T D ;FI(r)).

[0389] Referring to Figure 14, it should be noted that at the indicated time point, position marker 180 is depicted as passing exactly through the position sensor 170. Therefore, the indicated time point could be the time point indicated by time slot 1280, i.e., when the position signal P (i=1280) is generated. Due to the housing rotating clockwise, the most recent sample peak S... P It is caused by the impact between protrusion 310A and toe 205 (see...) Figure 14A and Figure 14B (and Table 5). Therefore, it was detected as maintaining the highest peak value S. P The vibration sample amplitude value S (i=760) appears at a time T before the position signal P (i=1280) appears. SP =dt (1280-760).

[0390] Because S=v t, where S = distance, v = constant velocity, and t is time, so the time relationship can be directly converted into distance. Therefore, column #02 of Table 5 can be regarded as indicating the physical position of the toe 205 at 59% of the distance between protrusions 310A and 310B (see Figure 14 along with column #02 of Table 5).

[0391] According to another example, referring to Table 6, the amplitude component S of the repetitive vibration signal P The temporal relationship between the occurrence of the position signal P(i) and the occurrence of the position signal P(i) can be considered as a phase deviation expressed in degrees.

[0392] Table 6

[0393]

[0394]

[0395] In fact, by using the position signal as the digital measurement signal S MD The reference signals S(i) and S(j) are used, and the settings of the Fast Fourier Transform (FFT) are adjusted in a certain way. The FFT can be used to extract the amplitude peak and phase value, as described below. Therefore, when the total distance between protrusions 310A and 310B is considered as 360 degrees, column #02 of Table 6 can be regarded as indicating the physical position of toe 205 at a distance of 213.75 degrees between protrusions 310A and 310B (see Figure 14 with column #02 of Table 6). When represented as a part of the distance between two adjacent protrusions 310, the physical position of toe 205 can be referred to as the relative position of toe 205. In other words, this disclosure provides a way to identify the relative toe position of toe 205 in a tumbling mill. Therefore, this disclosure provides a way to generate information indicating the position of toe 205 when represented as a part of the distance between two adjacent protrusions 310 in the rotating housing 20. Reference Figure 15 and Figure 16 The relative position of the toe can be represented as the phase angle FI(r), as shown below. Figure 15 and Figure 16The discussion focuses on the relative toe position. According to an embodiment of this disclosure, the relative toe position can be expressed as a percentage (see column #02 in Table 5 above). Furthermore, according to an embodiment of this disclosure, the relative toe position can be expressed as a duration, or a portion of a duration. As described above, in conjunction with Table 5, since S=v t, where S = distance, v = velocity of the protrusion, and t is time, so the time relationship can be directly converted into distance. In this case, it should be noted that the velocity v of the protrusion depends on the angular velocity f of the shell 20. ROT and the radius R of the shell 20 MIC (See Figure 14).

[0396] Figure 15 This is a block diagram showing an example of a state parameter extractor 450. Figure 15 The state parameter extractor 450 includes a receiver for receiving a number of vibration signals S MD A housing velocity detector 500 receives a digital position signal (Pi) and a housing velocity value generator (Pi). The housing velocity detector 500 can also be referred to as a housing velocity value generator 500. The housing velocity detector 500 can generate a value based on the received numerical vibration signal S. MD S(i) and the digital position signal (Pi) generate three signals S(j), P(j) and f. ROT (j). This can be illustrated, for example, by the above regarding... Figures 7 to 13 This is implemented in a descriptive manner. In this regard, it should be noted that three signals S(j), P(j), and f can be transmitted simultaneously. ROT (j), meaning these signals are all associated with the same time slot j. In other words, three signals S(j), P(j), and f can be provided synchronously. ROT (j). Providing signals such as S(j), P(j), and ROT(j) in a synchronous manner advantageously provides accurate information about the time relationship between the signal values ​​of each signal. Therefore, for example, the velocity value f transmitted by the housing velocity value generator 500... ROT (j) indicates the instantaneous rotational speed of housing 20 when the detection amplitude value S(j) is reached.

[0397] It should be noted that the signals S(j) and P(j) transmitted by the housing velocity value generator 500 are delayed relative to the signals S(i) and (Pi) received by the housing velocity value generator 500. It should also be noted that signals S(j) and P(j) are delayed equally relative to signals S(i) and (Pi), thus preserving their time relationship. In other words, signals S(j) and P(j) are synchronously delayed.

[0398] The housing speed detector 500 can transmit a signal indicating whether the rotational speed remains constant for a sufficiently long time. In this case, signals S(j) and P(j) can be transmitted to the fast Fourier converter 510.

[0399] As described above, variables Y, Z, and L should be set such that variable X is a positive integer. As an example, the variables Y, Z, and L can be set using a Human-Machine Interface (HCI) 210, 210S (see, for example, Figure 1 and / or...). Figure 5 and / or Figure 15 As described above, the resulting integer X indicates the number of revolutions of the monitored mill housing 20, during which digital signals S(j) and P(j) are analyzed by FFT 510. Therefore, based on the settings of variables Y, Z, and L, FFT 510 can generate a value X indicating the duration of the analysis session, and after the measurement session, FFT 510 transmits a set of status values ​​Sp(r) and FI(r).

[0400] In the state values ​​Sp(r) and FI(r), the concept "r" represents a point in time. It should be noted that there may be a time delay from the moment the first pair of input signals S(j), P(j) is received at the input of the FFT 510 until the pair of state values ​​Sp(r) and FI(r) is transmitted from the FFT 510. The pair of state values ​​Sp(r) and FI(r) can be based on the time series of the input signal pair S(j), P(j). The duration of the time series of the input signal pair S(j), P(j) should include at least two consecutive position signal values ​​P(j) = 1 and the corresponding input signal pair.

[0401] As described below, the state values ​​Sp(r) and FI(r) can also be referred to as C, respectively. L And ФL. As mentioned above... Figure 2 The vibration signal S EA S MD S(j) and S(r) will present signal characteristics indicating the impact between the protrusion and the toe 205. FIMP And when there are L protrusions 310 in the housing 20 (see Figure 1 combined) Figure 15 (as shown in Figure 14), for each revolution of the housing 20, this signal characteristic S FIMP This will be repeated L times.

[0402] To convey an intuitive understanding of this signal processing, it may be helpful to consider the superposition principle and repetitive signals such as sinusoidal signals. Sinusoidal signals can exhibit both amplitude and phase values. In short, the superposition principle, also known as the superposition property, states that for all linear systems, the net response induced by two or more stimuli at a given location and time is the sum of the responses induced by each stimulus individually. Sound waves are one such stimulus. Similarly, vibrational signals (e.g., including signal characteristics S indicating the impact of the protrusion with the toe 205)... FIMP Vibration signal S EA S MDS(j), S(r)) are one type of such stimulus. In fact, signal features S FIMP Vibration signal S EA S MD S(j) and S(r) can be considered as the sum of sinusoidal signals, each of which presents an amplitude and a phase value. In this regard, refer to the Fourier series (see Equation 1 below):

[0403] n=∞

[0404] F(t) =∑Cn sin(nωt +Ф n ) (Formula 1)

[0405] n=0

[0406] in,

[0407] The average value of the signal over a period of time when n=0 (it can be zero, but does not have to be zero).

[0408] n=1 corresponds to the fundamental frequency of the signal F(t).

[0409] n=2 corresponds to the first harmonic component of the signal F(t).

[0410] ω = angular frequency, i.e. (2 π f ROT ),

[0411] f ROT =Casing rotational speed, expressed in cycles per second.

[0412] t = time,

[0413] Φ n =The phase angle of the nth partial, and

[0414] C n = The amplitude of the nth partial.

[0415] From the Fourier series above, we can conclude that a time signal can be considered as a superposition of multiple sinusoidal signals.

[0416] Overtones are any frequencies higher than the fundamental frequency of a signal.

[0417] In the example above, it should be noted that the fundamental frequency will be f. ROT That is, the rotational speed of the housing, because for every revolution of the housing 20, the FFT510 only receives the tag signal value P(j)=1 once (see Figure 14 for example).

[0418] Using the Fourier analysis model, the fundamental tone and overtones together are called partials. Harmonics, or more precisely, harmonic partials, are partials whose frequencies are integer multiples of the fundamental frequency (including the fundamental frequency, which itself is 1).

[0419] refer to Figure 15 According to Formula 1 above, FFT 510 can transmit an amplitude value C for n=L. n (r), i.e., C L (r)=Sp(r). The FFT 510 can also transmit the phase angle of the split tone (n=L), i.e., ФL(r) = FI(r).

[0420] Now consider an example where the mill housing has ten (10) protrusions 310 when it rotates at a speed of 10 revolutions per minute (rpm). 10 rpm means one revolution every 6 seconds, or f ROT =0.1667 revolutions per second. It has ten protrusions (i.e., L=10) and uses f... ROT The housing operating at a speed of 0.1667 rpm causes the repetition frequency f of the signal associated with protrusion 310 to be... R It is 1,667 Hz because the repetition frequency f R It is a 10th order frequency.

[0421] Position signals P(j), P(q) (see...) Figure 15 The reference signals P(j) and P(r) can be used as reference signals for the digital measurement signals S(j) and S(r). According to some embodiments, when the FFT analyzer is configured to receive the reference signals, i.e., the position signals P(j) and P(q), once per revolution of the rotating housing 20, the settings of the FFT analyzer should meet the following criteria:

[0422] The integer value Oi is set to equal L, which is the number of protrusions in the housing 20, and

[0423] Choose configurable variables Y and Z such that the mathematical expression Oi Z / Y become positive integers. In other words: when the integer value Oi is set to equal L, the settable variables Y and Z should be set to integer values ​​so that variable X is a positive integer.

[0424] Where X=Oi Z / Y,

[0425] Y is the maximum order; and

[0426] Z is the number of frequency bands in the spectrum generated by the FFT, and

[0427] Oi is the frequency of interest, expressed as an integer of order, where f ROTIt is a frequency of order 1, i.e., the fundamental frequency. In other words, the rotational speed f of the casing 20 ROT It is the fundamental frequency, and L is the number of protrusions in the housing 20.

[0428] Using the above settings, that is, the integer value Oi is set to equal L, and referring to the above... Figure 15 According to Formula 1, FFT510 can transmit an amplitude value C such that n=L. n C L =Sp(r). The FFT 510 can also transmit a portion (n=L) of the phase angle, i.e., Ф. L =FI(r).

[0429] Therefore, according to embodiments of this disclosure, when the rotating housing 20 rotates once and the FFT 510 receives a position reference signal P(j) and P(q) once, the FFT analyzer can be configured to generate a peak amplitude value C of the signal. L The repetition frequency f of the signal R It is the L-order frequency, where L is the number of equidistant protrusions 310 in the rotating housing 20.

[0430] Referring to the discussion of Equation 1 above in this disclosure, the repetition frequency f R The amplitude of a signal with an L-order frequency can be called C. n Where n=L, i.e., C L Refer to Formula 1 and Figure 15 It can transmit amplitude value C L As the peak amplitude value, in Figure 15 It is represented as Sp(r).

[0431] Referring again to Formula 1 above, in this disclosure, its repetition frequency f can be transmitted. R The phase angle Ф of a signal with frequency L. L As a time indication value, this time indication value indicates the impact force F IMP The duration T between the occurrence of the rotating reference position of the rotating housing and the occurrence of the rotating reference position D1 .

[0432] Therefore, according to embodiments of this disclosure, when the rotating housing 20 rotates once and the FFT 510 receives a position reference signal P(j) and P(q) once, the FFT analyzer can be configured to generate a repetition frequency f. R The phase angle value Ф of the signal with frequency L. L Where L is the number of equidistant protrusions 310 in the rotating housing 20.

[0433] Therefore, using the above settings, i.e., the integer value Oi is set to equal L, and referring to the above... Figure 15According to Formula 1, FFT 510 can generate the phase angle value Ф. L .

[0434] Combination Figure 1A refer to Figure 15 State value Sp(r) = C L and FI(r) = Ф L The results can be transmitted to a human-machine interface (HCI) 210 to provide visual indications of the analysis results. As described above, the displayed analysis results may include information indicating the internal state of the tumbling process, enabling the operator 230 to control the tumbling mill.

[0435] Figure 16 This is an illustration of an example of a visual indication of the analysis results. According to one example, the visual indication of the analysis results may include providing a polar coordinate system 520. A polar coordinate system is a two-dimensional coordinate system in which each point in the plane is determined by its distance from a reference point 530 and its angle from a reference direction 540. The reference point 530 (similar to the origin of a Cartesian coordinate system) is called the pole 530, and the ray from the pole in the reference direction is the polar axis. The distance to the pole is called the radial coordinate, radial distance, or simply radius, and the angle is called the angular coordinate, polar angle, or azimuth angle.

[0436] In one example, the amplitude value Sp(r) is used as the radius, and the time-related values ​​FI(r), Ф(r), and T are... D Used as angular coordinates.

[0437] In this way, the internal status of the monitored tumbling mill can be displayed by providing the internal status indicator object 550 on the display 210S. Figure 16 Combination Figure 1A and / or Figure 1B ). Figure 16 Combination Figure 1A and / or Figure 1B Figure 14 may help in understanding the following example.

[0438] Therefore, one example relates to an electronic tumbling mill monitoring system 150, 210S for generating and displaying information related to the grinding process in a tumbling mill 10, which has a housing 20 that rotates at a rotational speed f. ROT Rotating about axis 60, used to grind material feed 30 by tumbling the material feed within the rotating housing. Example monitoring system 150 includes:

[0439] A computer-implemented method for displaying the internal state of the grinding process in the tumbling mill on a screen display 210S.

[0440] The method includes:

[0441] The following is displayed on the screen display 210S:

[0442] Polar coordinate system 520, the polar coordinate system 520 having

[0443] Reference point (O, 530), and

[0444] Reference direction (0) o 360 o 540 o );as well as

[0445] First internal state indicator object (550, S) P1 T D1 ), which indicates the internal state of the grinding process, having a first radius (Sp(r), S) from the reference point (O). P1 ), and relative to the reference direction (0 o 360 o 540 o ) has a first polar angle (FI(r), Ф(r), T) D T D1 ),

[0446] The first radius (Sp(r), S) P1 ) indicates the impact force (F) generated when the protrusion (310) on the inner surface of the rotating housing interacts with the toe portion 205 of the packing material (30). IMP ),and

[0447] The first polar angle (F1(r), Ф(r), T) D T D1 () Indicates the position of the toe 205 between the two protrusions 310 in the rotating housing 20.

[0448] As described above, the state parameter extractor 450 can be configured to generate consecutive state value pairs Sp(r) and FI(r). The state parameter extractor 450 can also generate the time derivative values ​​of the state values ​​Sp(r) and FI(r), respectively. This can be done, for example, by subtracting the most recent previous state value Sp(r-1) from the most recent state value Sp(r) divided by the duration between the two values. Similarly, the numerical derivative of the internal state value FI can be obtained. Therefore, derivative values ​​dSp(r) and dFI(r) can be generated. The derivative values ​​dSp(r) and dFI(r) can be used to indicate the first internal state index object (550, S). P1 T D1 ) movement.

[0449] Figure 17 and Figure 18 This is another example of a visual representation of the analysis results. (Reference) Figure 17 and Figure 18 The aforementioned derivative value can be used to display arrow 560 on the screen display 210S, which originates from the first internal state indicator object (550, S). P1 T D1 The position of ) and has an extension that depends on the magnitude of the derivative. In other words, the absence of arrow 560 means that the internal state is stable and has not changed over a period of time. Figure 18 The arrow in the middle is 560 times. Figure 17 The arrow in the middle is 560mm long, thus indicating Figure 18 The internal state of the mill shown is compared to Figure 17 The internal state of the mill shown changes more rapidly.

[0450] Figure 19A and Figure 19B Another example of a visual indication based on the analysis results of the internal state of the mill 10 is shown. The most recent internal state indicator object 550(r) indicates the current internal state of the mill 10. Another internal state indicator object 550(r-1) indicates the most recent previous internal state of the mill 10.

[0451] The internal state indicator object 550(1), displayed as a small hollow circle, indicates the internal state of the mill 10 when the filling degree is almost empty. It should be noted that when the mill is started from an unloaded state, the initial internal state indicator object appears at the initial polar angle Ф(1), which represents the first detected toe position of the mill. Figure 19A and Figure 19B In the diagram, starting from the smallest hollow circle 550 (1), the first thirty-one (31) detected toe positions are represented as hollow circles. Based on experimental measurements, it appears that the initial polar angle Ф (1) can be used as a reference toe position value. Therefore, the initial polar angle Ф (1) can be called the reference toe position value Ф. TR Regarding its internal state, it is determined by... Figure 19A and Figure 19B The display 210S shown indicates a specific tumbling mill, with the reference toe position corresponding to an angle value Ф of approximately 47 degrees. TR ,like Figure 19A and Figure 19B As shown.

[0452] The first thirty-one (31) detected toe positions are represented by hollow circles, while the subsequent toe position sequences are represented by shaded circles, one of which is in... Figure 19A It is represented as 550 (p). Figure 19A The shaded circle in the diagram indicates that the filling degree of the mill housing 20 is higher than that indicated by the hollow circle. Figure 19AThe solid black circle in the figure indicates that the filling degree of the mill housing 20 is higher than that indicated by the shaded circle. Therefore, it should be noted that the initial lowest detected filling degree appears to be represented by a relatively small radius, i.e., a low peak amplitude value Sp at the initial polar angle Ф(1).

[0453] refer to Figure 19A The gradually increasing detected toe position FI(r) and the correspondingly gradually increasing filling degree of the mill housing 20 present an image of the spiral arm rotating outward in a counterclockwise direction, starting from the first internal state index object 550(1), as shown in the image. Figure 19A The curved arrow 560A is shown in the image.

[0454] In this way, the current internal state of the roller mill 20 can be represented and visualized, making it intuitively clear to the operator 230 of the mill system 5. It should be noted that, although... Figure 17 As shown, the display of a single internal status indicator object 550 indicates the current internal status or the most recently detected internal status of the mill 10, but as... Figure 19A As shown, the display of the time progression of the internal state index object, ranging from the initial state 550 (1) through intermediate states (e.g., 550 (p) and 550 (r-1) to 550 (r)), represents the current internal state 550 (r) and the history of several earlier internal states 550 (p), 550 (p+1), and 550 (r-1) of the mill 10.

[0455] In other words, the gradually increasing polar angle F1(r) and the gradually increasing radius value S p (r) combined, presents an image of the spiral arm rotating outward from the first internal state index object 550 (1), as shown in the image. Figure 19A The curved arrow 560A in the diagram shows the "angular length" X6(r) of the spiral arm from the initial polar angle Ф(1) of the first internal state index object 550(1) to the currently or most recently detected toe position FI(r), which appears to indicate the absolute position X6(r) of the toe 205 (see, for example, [reference]). Figure 2 (And Figure 14). Regarding this point, it should be noted that... Figure 19A In the polar coordinate system 520, 360 degrees corresponds to two adjacent protrusions (e.g., Figure 2 100% of the distance between the leading edges of 312C and 312D.

[0456] Example of a variable speed phase state parameter extractor

[0457] As described above, if the tumbling mill housing 20 is variable Rotational speed f ROTRotation complicates the analysis of measurement data. In fact, regarding the tailing effect, it seems that even a very small change in the rotational speed of the mill casing can significantly and adversely affect the quality of the detected signal. Therefore, the rotational speed f of the mill casing 20... ROT Very precise detection appears to be crucial, as does accurate compensation for any speed variation.

[0458] refer to Figure 15 The housing speed detector 500 can transmit a signal indicating when the rotational speed changes, such as in combination with... Figure 9 The above is under discussion. Please refer again. Figure 15 Signals S(j) and P(j) and velocity value f ROT (j) can be transmitted to the speed variation compensation extractor 470. The speed variation compensation extractor 470 can also be called a fractional extractor. The extractor 470 is configured to be based on the received speed value f. ROT (j) Extracting the digital measurement signal S MD According to one example, decimator 470 is configured to decimate the digital measurement signal S by a variable decimation factor D. MD During the measurement session, based on the variable speed value f ROT (j) Adjust the variable decimation factor D. Therefore, the compensated decimator 470 is configured to generate a decimation quantity vibration signal S. MDR This ensures that when the rotational speed changes, the number of sample values ​​for each rotation of the rotating housing remains constant, or substantially constant. According to some embodiments, the number of sample values ​​for each rotation is considered substantially constant when the change in the number of sample values ​​is less than 5%. According to a preferred embodiment, the number of sample values ​​for each rotation is considered substantially constant when the change in the number of sample values ​​is less than 1%. According to the most preferred embodiment, the number of sample values ​​for each rotation is considered substantially constant when the change in the number of sample values ​​is less than 0.2%.

[0459] therefore, Figure 15 Implementations include a fractional extractor 470 for extracting a factor D = N / U. D Sampling rate, where U D Both N and U are positive integers. Therefore, the fractional decimator 470 advantageously allows the sampling rate to decrement the fraction. Thus, the velocity variation-compensated decimator 470 can operate to decrement the fraction D = N / U. D To extract signals S(j) and P(j) and f ROT (j). According to one embodiment, U D The values ​​of and N can be selected from a range of 2 to 2000. According to one embodiment, UD The values ​​of and N can be selected from a range of 500 to 1500. According to yet another embodiment, U D The values ​​of N can be chosen within the range of 900 to 1100. In this text, it should be noted that the term "fraction" is used in the following context: a fraction (from the Latin word fractus, "broken") represents a part of a whole, or more generally, any number of equal parts. In positive common fractions, both the numerator and denominator are natural numbers. The numerator represents some equal parts, and the denominator represents how many parts make up a unit or a whole. Common fractions are quantities that represent rational numbers. The same quantity can also be expressed as a decimal, percentage, or negative exponent. For example, 0.01, 1%, and 10... -2 Both are equal to the fraction 1 / 100. Therefore, the fraction D = N / U D It can be considered an inverse fraction.

[0460] Therefore, the result signal S transmitted by the fraction extractor 470 MDR With sampling rate:

[0461] f SR =f S / D= f S U D / N

[0462] Among them, f S The signal S received by the fraction extractor 470 RED The sampling rate.

[0463] Score U D / N depends on the rate control signal received at input port 490. The rate control signal may be an indication of the rotational speed f of the rotating housing. ROT The signal.

[0464] The variable extractor value D of the extractor can be set to D=f S / f SR , where f S f is the initial sampling rate of the A / D converter. SR It is an indicator of the number of vibration signals S extracted. MDR The setpoint value for the number of samples per revolution. For example, when there are twelve (12) protrusions to be monitored in the mill housing, the setpoint value f SR It can be set to 768 samples per revolution, that is, the number of samples per revolution is set as the number of vibration signals S extracted. MDR The fsr compensation extractor 470 is configured to vibrate the signal S based on the number of samples extracted. MDR The position signal P(q) is generated at regular intervals, which depend on the setpoint value f. SR For example, when fSR When set to 768 samples per revolution, the position signal P(q) can be transmitted once every 768 samples of the extracted vibration signal S(q).

[0465] Therefore, the sampling frequency f of the output data value R(q) SR (also known as f) SR2 ) compared to the input sampling frequency f S A lower factor D. Factor D can be set to any number greater than 1 and can be a fraction, as discussed elsewhere in this disclosure. According to a preferred embodiment, factor D can be set to a value between 1.0 and 20.0. In a preferred embodiment, factor D is a fraction that can be set to a value between approximately 1.3 and approximately 3.0. This can be achieved by subtracting an integer U... D Set N to an appropriate value to obtain the factor D. The factor D is equal to N divided by U. D :

[0466] D=N / U D

[0467] According to one embodiment, integer U D N can be set to a large integer so that the factor D = N / U D It can follow speed changes with minimal error. Choose variable U. D Using integers greater than 1000 for N is beneficial for achieving high accuracy when adjusting the output sampling frequency to track changes in the rotational speed of the housing 20. Therefore, for example, setting N to 500, and setting U... D If set to 1001, then D = 2.002.

[0468] Variable D is set to an appropriate value at the start of the measurement, and this value is associated with the specific rotational speed of the rotating component to be monitored. Subsequently, during the measurement session, the fractional value D is automatically adjusted in response to the rotational speed of the component to be monitored, such that the output signal S... MDR A roughly constant number of sample values ​​are provided per revolution of the rotating shell.

[0469] Figure 20 This is a block diagram of an example of a compensation extractor 470. This example of a compensation extractor is represented as 470B.

[0470] The compensation extractor 470B may include a memory 604 adapted to receive and store data values ​​S(j) and the corresponding rotational speed f of the monitored rotary mill housing. ROT Therefore, the memory 604 can store each data value S(j) such that it is associated with the sensor signal S corresponding to the data value S(j) detected. EA The rotational speed f of the mill casing being monitored at that time. ROT The value of (j) is related. Refer to the above. Figures 7-13 Describes the corresponding speed value f ROT (j) The provision of the associated data value S(j).

[0471] The compensated decimator 470B receives a receiver with a sampling frequency f SR1 signal S MD As a sequence of data values ​​S(j), and transmitted at its output 590 with a reduced sampling frequency f SR Output signal S MDR , as another sequence of data values ​​R(q).

[0472] The compensation extractor 470B may include a memory 604 adapted to receive and store data values ​​S(j) and the corresponding rotational speed f of the monitored rotary mill housing. ROT The information. Memory 604 can store the data value S(j) in the block, such that each block is associated with a value indicating the relevant rotational speed of the monitored mill casing, as shown below. Figure 21 As stated above.

[0473] The compensation extractor 470B may also include a compensation extraction variable generator 606, which is adapted to generate a compensation value D. The compensation value D may be a floating-point number. Therefore, in response to the received velocity value f... ROT The compensation number can be controlled as a floating-point value, allowing the floating-point value to indicate the speed value f with a specific degree of inaccuracy. ROT As mentioned above, when implemented by a properly programmed DSP, the inaccuracy of floating-point values ​​may depend on the DSP's ability to generate floating-point values.

[0474] Furthermore, the compensated decimator 470B may also include an FIR filter 608. In this respect, the acronym FIR stands for Finite Impulse Response. The FIR filter 608 is a low-pass FIR filter with a specific low-pass cutoff frequency, suitable for use with a factor of D. MAX Perform extraction. Factor D MAX It can be set to a suitable value, for example, 20,000. Furthermore, the compensation decimator 470B may also include a filter parameter generator 610.

[0475] The following is for reference. Figure 21 Section 22 describes the operation of the compensation extractor 470B.

[0476] Figure 21 This shows the operation. Figure 20 A flowchart of an embodiment of the method of the compensation sampler 470B.

[0477] In the first step S2000, the rotational speed f of the mill casing is to be monitored. ROT Recorded in memory 604 ( Figure 20and Figure 21 This can be done at roughly the same time as the vibration measurement begins. According to another example, the rotational speed of the mill casing to be monitored is measured over a period of time. The maximum detection speed f... ROTmax and minimum detection speed f ROTmin It can be recorded in, for example, memory 604 ( Figure 20 and Figure 21 ).

[0478] In step S2010, the recorded speed values ​​are analyzed to determine whether the rotational speed has changed.

[0479] In step S2020, the user interface 210, 210S displays the recorded velocity value f. RO Or velocity value f ROTmin f ROTmax It then requests the user to input the desired sequence value Oi. As mentioned above, the mill casing rotation frequency f ROT This is typically referred to as "order 1". An interesting signal might appear ten times (order 10) per revolution of the mill casing. Furthermore, analyzing the overtones of some signals can be interesting, so measuring signals up to orders 100, 500, or even higher can be intriguing. Therefore, the user can input the order Oi using the user interface 210, 210S.

[0480] In step S2030, a suitable output sampling rate f is determined. SR In this disclosure, the output sampling rate f SR It can also be called f SR2 According to one embodiment, the output sampling rate f SR Set to f SR =C Oi f ROTmin ,

[0481] in,

[0482] C is a constant with a value greater than 2.0.

[0483] Oi is a number indicating the relationship between the rotational speed of the monitored mill casing and the repetition frequency of the signal to be analyzed.

[0484] f ROTmin This is the minimum rotational speed of the mill casing to be monitored during the upcoming measurement session. According to one embodiment, as described above, the value f... ROTmin It is the lowest rotational speed detected in step S2020.

[0485] Considering the sampling theorem, the constant C can be chosen to be 2.00 (ii) or a higher value. According to embodiments of this disclosure, the constant C can be preset to a value between 2.40 and 2.70.

[0486] According to one embodiment, factor C is advantageously chosen such that 100 C / 2 represents an integer. According to one embodiment, the factor C can be set to 2.56. Choosing C to 2.56 makes 100 C = 256 = 2 to the power of 8.

[0487] In step S2050, the compensation extracted variable value D is determined. When the rotational speed of the monitored mill casing changes, the compensation extracted variable value D will change according to the instantaneously detected speed value.

[0488] According to one embodiment, the maximum compensation extracted variable value D MAX Set to D MAX = f ROTmax / f ROTmin The value of , and the minimum compensated extracted variable value D MIN It was set to 1.0. After that, the actual speed value f... ROT Perform instantaneous real-time measurements and set the instantaneous compensation value D accordingly.

[0489] f ROT It indicates the measured rotational speed of the rotating mill casing to be monitored.

[0490] In step S2060, the actual measurement begins, and the expected total duration of the measurement can be determined. The total duration of the measurement can be determined based on the expected rotational speed X of the monitored mill casing.

[0491] When the measurement begins, the digital signal S MD The signal is transmitted to input 480 of the compensation extractor. In the following discussion, the signal S is considered in relation to the signal having sample values ​​S(j). MD , where j is an integer.

[0492] In step S2070, the data value S(j) is recorded in the memory 604, and each vibration data value S(j) is compared with the rotational speed value f. ROT (j) Related.

[0493] In the subsequent step S2080, the recorded rotational speed values ​​are analyzed, and the recorded data values ​​S(j) are divided into data blocks based on the rotational speed values. In this way, multiple blocks of data values ​​S(j) can be generated, each data value block S(j) associated with a rotational speed value. The rotational speed value indicates the rotational speed of the monitored mill casing at the time the data value of that specific block S(j) is recorded. The data blocks can have different sizes, meaning each data block can store a different number of data values ​​S(j).

[0494] For example, if the monitored rotary mill casing first reaches a first speed f during the first time period. ROT1 It rotates, and then changes speed during a second, shorter time interval, to a second speed f. ROT2 If rotated, the recorded data value S(j) can be divided into two data blocks, the first data block being the first velocity value f. ROT1 Relatedly, the second data block value is related to the second velocity value f. ROT2 Related. In this case, the second data block will contain fewer data values ​​than the first data block because the second time period is shorter.

[0495] According to one embodiment, when all recorded data values ​​S(j) have been divided into blocks and all blocks have been associated with rotational speed values, the method continues to execute step S2090.

[0496] In step S2090, the first data value S(j) is selected, and the corresponding rotational speed value f is determined. ROT The compensation extraction value D is then used. This compensation extraction value D is associated with the first block data value S(j). According to one embodiment, when all blocks have been associated with their respective compensation extraction values ​​D, the method continues to step S2100. Therefore, the value of the compensation extraction value D is determined according to the velocity f. ROT Adjustments will be made.

[0497] In step S2100, the block of data value S(j) and the associated compensation extraction value D are selected, as described in step S2090 above.

[0498] In step S2110, in response to the selected input value block S and the associated compensated decimation value D, an output value block R is generated. This can be done as described with reference to Figure 22.

[0499] In step S2120, it is checked whether there are any remaining input data values ​​to process. If there is another block of input data values ​​to process, step S2100 is repeated. If there are no remaining blocks of input data values ​​to process, the measurement session is complete.

[0500] Figure 22A , Figure 22B and Figure 22CThe operation is shown Figure 20 A flowchart of an embodiment of the method of the compensation sampler 470B.

[0501] In step S2200, an input data value block S(j) and an associated specific compensation decimation value D are received. According to one embodiment, the received data is as described above. Figure 21 As described in step S2100. The input data values ​​S(j) in the received input data value block S are all associated with a specific compensated decimation value D.

[0502] In steps S2210 to S2390, the FIR filter 608 (see...) Figure 20 This applies to the specific compensated decimation value D received in step S2200 and generates a corresponding set of output signal values ​​R(q). This will be described in more detail below.

[0503] In step S2210, a filter setting suitable for a specific compensation decimation value D is selected. (As described above...) Figure 20 The FIR filter 608 mentioned is a low-pass FIR filter, suitable for filters with a factor of D. MAX The low-pass cutoff frequency to be decimated. Factor D MAX It can be set to an appropriate value, for example, 20.

[0504] Filter ratio F R Set to depend on factor D MAX And the value of the specific compensation decimation value D received in step S2200. Step S2210 can be generated by filter parameter generator 610 ( Figure 20 ) to execute.

[0505] In step S2220, a starting position value x is selected from the received input data block s(j). It should be noted that the starting position value x does not have to be an integer. The FIR filter 608 has a length F LENGTH Then, based on the filter length F LENGTH and filter ratio F R Select the starting position value x. The filter ratio FR is set as in step S2210 above. According to one embodiment, the starting position value x can be set to x:=F LENGTH / F R .

[0506] In step S2230, the filter sum value SUM is prepared and set to an initial value, for example, SUM:=0.0.

[0507] In step S2240, position j, which is adjacent to and precedes position x in the received input data, is selected. Position j can be selected as the integer part of x.

[0508] In step S2250, a position Fpos in the FIR filter is selected, corresponding to the selected position j in the received input data. Position Fpos can be a compensation amount. The filter position Fpos relative to the middle position of the filter can be determined as follows:

[0509] Fpos=[(xj) F R ]

[0510] Among them, F R It is the filter ratio.

[0511] In step S2260, it is checked whether the determined filter position value Fpos is outside the allowed limit value, that is, pointing to a position outside the filter. If this occurs, proceed to step S2300. Otherwise, proceed to step S2270.

[0512] In step S2270, the filter values ​​are calculated by interpolation. It should be noted that adjacent filter coefficients in an FIR low-pass filter typically have similar values. Therefore, interpolation will be advantageously accurate. First, the integer position value IFpos is calculated:

[0513] IFpos := the integer part of Fpos

[0514] The filter value Fval for position Fpos will be:

[0515] Fval = A(IFpos) + [A(IFpos+1) - A(IFpos)] [Fpos - IFpos]

[0516] Here, A(IFpos) and A(IFpos+1) are the values ​​in the reference filter, and the filter position Fpos is the position between these values.

[0517] In step S2280, in response to signal position j, the updated filtered sum value SUM is calculated:

[0518] SUM:= SUM + Fval S(j)

[0519] In step S2290, move to another signal position:

[0520] Set j:=j-1

[0521] Then proceed to step S2250.

[0522] In step 2300, position j in the received input data that is adjacent to position x and follows position x is selected. This position j can be selected as the integer part of x plus 1 (-), that is, j:=1+the integer part of x.

[0523] In step S2310, a position corresponding to the selected position j in the received input data is selected in the FIR filter. The position Fpos can be a compensation amount. The filter position Fpos relative to the middle position of the filter can be determined as:

[0524] Fpos = [(jx) F R ]

[0525] Among them, F R It is the filter ratio.

[0526] In step S2320, it is checked whether the determined filter position value Fpos is outside the allowed limit value, that is, pointing to a position outside the filter. If this occurs, proceed to step S2360. Otherwise, proceed to step S2330.

[0527] In step S2330, the filter values ​​are calculated by interpolation. It should be noted that adjacent filter coefficients in an FIR low-pass filter typically have similar values. Therefore, interpolation will be advantageously accurate. First, the integer position value IFpos is calculated:

[0528] IFpos := the integer part of Fpos

[0529] The filter value for position Fpos is:

[0530] Fval (Fpos) = A(IFpos) + [A(IFpos+1) - A(IFpos)] [Fpos - IFpos]

[0531] Here, A(IFpos) and A(IFpos+1) are the values ​​in the reference filter, and the filter position Fpos is the position between these values.

[0532] In step S2340, in response to signal position j, the updated filtered sum value SUM is calculated:

[0533] SUM:= SUM + Fval S(j)

[0534] In step S2350, move to another signal position:

[0535] Set j:=j+1

[0536] Then proceed to step S2310.

[0537] In step S2360, the output data value R(j) is transmitted. The output data value R(j) can be transmitted to the memory, so that consecutive output data values ​​are stored in consecutive memory locations. The value of the output data value R(j) is:

[0538] R(j) := SUM

[0539] In step S2370, update the position value x:

[0540] x:=x+D

[0541] In step S2380, the position value j is updated.

[0542] j:=j+1

[0543] In step S2390, it is checked whether the expected number of output data values ​​has been generated. If the expected number of output data values ​​has not been generated, proceed to step S2230. If the expected number of output data values ​​has been generated, proceed to the step about... Figure 21 Step S2120 in the described method.

[0544] In fact, step S2390 is designed to ensure that an output signal value R(q) corresponding to the input data value block S received in step S2200 is generated, and when the output signal value R corresponding to the input data value S has been generated, the following should be executed: Figure 21 Step S2120 in the process.

[0545] The method described with reference to Figure 22 can be implemented as a computer program subroutine, and steps S2100 and S2110 can be implemented as the main program.

[0546] Figure 23 Another example is shown: a cross-sectional view of the intermediate portion 98 of the rotary mill housing 20 during operation. This view can be, for example, along... Figure 1A The line AA is cut off. According to... Figure 23 For example, the tumbling mill housing 20 has six protrusions 310, which are configured to engage the material loading 30 when the housing rotates about the axis 60, i.e., the quantity L=6. For clarity, Figure 23 The protrusions in the examples are labeled as 3101, 3102, 3103, 3104, 3105 and 3106 respectively.

[0547] A position sensor 170 is provided to generate a position signal E based on the rotational position of the housing 20. PAs described above, the housing 20 can rotate about the rotation axis 60, so the position sensor 170, which is fixedly mounted, can generate a position signal E. P The position signal has a series of housing position signal values ​​P S This is used to indicate the instantaneous rotational position of the housing 20. For example... Figure 23 As shown, multiple position marks 180 can be provided on the outer surface of the housing 20, such that when the housing 20 rotates about the rotation axis 60, several position marks 180 pass the position sensor 170 in one rotation of the housing 20, and each mark 180 thereby causes the position sensor 170 to generate a rotation mark signal value Ps. According to one embodiment, L position marks 180 are provided on the housing 20, such that when the housing 20 rotates about the rotation axis 60, the position marks 1801...180... L The signal continuously passes through position sensor 170, causing position sensor 170 to generate L rotation mark signal values ​​Ps during one rotation of housing 20. According to... Figure 23 The embodiment shown has six protrusions 310, i.e., L=6, and six position markers 1801, 1802, 1803, 1804, 1805 and 1806.

[0548] It is believed that, importantly, the arrangement of the position mark 180 in terms of angular position reflects the arrangement of the protrusion 310 on the inner surface 22 of the housing 20 in terms of angular position.

[0549] exist Figure 23 In this embodiment, L position markers 180 are positioned equidistantly on the periphery of the housing 20, such that the position sensor 170 generates a marker signal Ps every 360 / L degrees during the rotation of the housing 20. In this case, it should be noted that... Figure 23 In the embodiments, L-shaped protrusions 3101, 3102, 3103, 3104, 3105 and 310 L They are positioned equidistantly on the inner surface 22 of the housing 20. It is believed that the equidistant positions of the protrusions 310 and the equidistant positions of the position marks 180 are important for some embodiments of this disclosure. This is considered important for some embodiments of this disclosure because the position marks 180 result in the generation of position reference signal values, and when engaging material in a rotary mill load, the protrusions 310 result in the generation of signal events in the vibration signal, such as amplitude peaks (see reference document S). EA S MD Se(i), S(j), S(q), for example, in Figure 1 and Figure 15(In the middle). Furthermore, the duration between the occurrence of the position reference signal value and the occurrence of the signal event in the vibration signal can indicate the internal state of the mill during operation, as discussed elsewhere in this disclosure, and this duration is caused by the material in the charge that engages the protrusion 310 with the rotating mill housing. For example, the duration between the occurrence of the position reference signal value and the occurrence of the signal event in the vibration signal can indicate the internal state, such as the position of the toe 205, and this duration is caused by the material in the charge that engages the protrusion 310 with the rotating mill housing.

[0550] However, the actual placement of the position mark 180 relative to the position of the protrusion 310 is considered less important. Therefore, although Figure 23 The position mark 180 is shown to be placed at the same angular position as the protrusion 310; however, it should be noted that the position mark 180 can also be displaced according to the angular position. However, if the position mark 180 is displaced in terms of angular position, it is believed that it is important that all position marks 180 are displaced equally to maintain the mutually equidistant positions of the position marks 180. More specifically, it is believed that it is important that the arrangement of the position marks 180 in terms of angular position reflects the arrangement of the protrusion 310 on the inner surface 22 of the housing 20 in terms of angular position.

[0551] As mentioned above, combined Figure 19A and Figure 19B It has been observed that when the mill is started from an empty state, the initial internal state index object appears at the initial polar angle Ф(1), which represents the first detected toe position 205 by the mill. Based on experimental measurements, it appears that the initial polar angle Ф(1) can be used as a reference toe position value. Therefore, the initial polar angle Ф(1) can thus be called the reference toe position value Ф. TR Regarding its internal state, it is determined by... Figure 19A and Figure 19B The display 210S shown indicates a specific tumbling mill, with the reference toe position corresponding to an angle value Ф of approximately 47 degrees. TR ,like Figure 19A and Figure 19B As shown. Reference Figure 2 As shown in Figure 14, it is believed that if the position mark 180 is physically moved to a different position in terms of angular location, the reference to the toe position value Ф TR The angle value will change to a different numerical angle value.

[0552] like Figure 23 The arrangement of the rotary mill housing 20 shown can be used in conjunction with the state parameter extractor 450 illustrated in this disclosure. (See reference) Figure 15 ,like Figure 23As shown, the arrangement of the rotary mill housing 20 can be used to generate a marker signal P(i), which is transmitted to the housing speed value generator 500. Therefore, during the rotation of the housing 20, the housing speed value generator 500 will receive a marker signal P(i) with a position indicator signal value every 360 / L degrees. Thus, when the rotational speed f... ROT At a constant speed, during the rotation of housing 20, the Fast Fourier Transform (FFT) 510 receives a marker signal value P(j) = 1 from the speed value generator 500 every 360 / L degrees. Alternatively, when the rotational speed f... ROT During the change, while the housing 20 is rotating, the fast Fourier converter 510 will receive the marker signal value P(q)=1 from the extractors 470, 470B every 360 / L degrees.

[0553] Furthermore, when the velocity value generator 500 receives a marker signal P(i) with a position indication signal value (e.g., P(i) = 1) every 360 / L degrees during the rotation of the housing 20, the velocity value generator 500 will be able to generate even more precise velocity values ​​f. ROT (j).

[0554] Regarding the appropriate setting of FFT 510 when a marker signal value P(j)=1 is received every 360 / L degrees during the rotation of housing 20, this means that the fundamental frequency will be the repetition frequency f. R .

[0555] As mentioned above Figure 2 The vibration signal S EA S MD S(j) and S(q) will exhibit signal characteristics S FIMP The indicator protrusion impacts the toe 205, and when there are L protrusions 310 in the housing 20 (see...). Figure 23 Combining with formula 2 below), for every revolution of the housing 20, the signal characteristic S FIMP This will be repeated L times.

[0556] Referring again to the Fourier series (see Formula 2 below):

[0557] n=∞

[0558] F(t) =∑ Cn sin(nωt +Ф n ) (Formula 2)

[0559] n=0

[0560] in,

[0561] The average value of the signal over a period of time when n=0 (it can be zero, but does not have to be zero).

[0562] n=1 corresponds to the fundamental frequency of the signal F(t).

[0563] n=2 corresponds to the first harmonic component of the signal F(t).

[0564] ω = the angular frequency of interest, i.e. (2 π f R ),

[0565] f R =Frequency of attention, expressed in cycles per second.

[0566] t = time,

[0567] Ф n =The phase angle of the nth partial,

[0568] C n = The amplitude of the nth partial.

[0569] In this embodiment, it should be noted that when the FFT 510 receives a marker signal value P(j)=1 every 360 / L degrees during the rotation of the housing 20, the base frequency will be one for each protrusion 310.

[0570] As mentioned above, the FFT 510 settings should take the reference signal into account. As mentioned above, the position signals P(j) and P(q) (see...) Figure 15 It can be used as a reference signal for digital measurement signals S(j) and S(q).

[0571] According to some embodiments, when the FFT analyzer is configured to receive a reference signal, i.e., position signals P(j) and P(q), every 360 / L degrees during the rotation of the housing 20, and L is the number of protrusions 310 in the housing 20, the settings of the FFT analyzer should meet the following criteria:

[0572] The integer value Oi is set to one, that is, equal to 1, and

[0573] Choose configurable variables Y and Z such that the mathematical expression Oi Z / Y become positive integers. In other words: when the integer value Oi is set to 1, the settable variables Y and Z should be set to integer values ​​so that variable X becomes a positive integer.

[0574] Where X=Oi Z / Y

[0575] Using the above settings, that is, the integer value Oi is set to equal to 1, and referring to the above... Figure 15 According to Formula 2, FFT510 can transmit an amplitude value C with n=1. nThat is, C1=Sp(r). The FFT 510 can also transmit the phase angle of the fundamental frequency (n=1), that is, Ф1 =FI(r).

[0576] Combination Figure 1A and / or Figure 1B Refer to Formula 2 above. Figure 15 The status values ​​Sp(r)=C1 and FI(r)=Ф1 can be transmitted to the human-machine interface (HCI) 210 to provide a visual indication of the analysis results. As described above, the displayed analysis results may include information indicating the internal state of the tumbling process, enabling the operator 230 to control the tumbling mill.

[0577] refer to Figure 16 , Figure 17 , Figure 18 , Figure 19A and Figure 19B The example illustration of the visual indication of the analysis results is effective for the setup of the rotary mill housing 20, such as... Figure 23 As shown, the FFT 510 will thus receive marker signals P(i), P(j), P(q) with position indication signal values ​​every 360 / L degrees, where L is the number of protrusions 310 in the housing 20.

[0578] Although the above discussion of the setup of the FFT510 involves Fourier series and Equations 1 and 2 for the purpose of conveying an intuitive understanding of the background of the FFT transformer 510 setup, it should be noted that the use of digital signal processing may involve the Discrete Fourier Transform (see Equation 3 below):

[0579] Formula 3:

[0580]

[0581] Therefore, according to embodiments of this disclosure, the aforementioned Discrete Fourier Transform (DFT) can be incorporated into signal processing for generating data indicating the internal state of the tumbling mill, for example, as discussed in the embodiment in conjunction with the state parameter extractor 450. In this regard, refer to, for example... Figure 3 , Figure 4 , Figure 5 , Figure 15 and / or Figure 24 Given the above discussion on the topics of FFT and Fourier series, the Discrete Fourier Transform will not be discussed in further detail, as the technical reader of this disclosure is already very familiar with it.

[0582] although Figure 23Multiple position markers 180 are shown to be disposed on the outer surface of the housing 20, each marker 180 thereby causing the position sensor 170 to generate a rotational marker signal value Ps. However, it should be noted that such position signals can alternatively be generated by an encoder 170 mechanically coupled to the rotating mill housing 20. Thus, the position sensor 170 can be implemented by an encoder 170 mechanically coupled to the rotating mill housing 20, such that during the rotation of the mill housing 20, the encoder generates, for example, a marker signal Ps on each protrusion 310 in the rotating housing 20.

[0583] In summary, regarding the appropriate settings for FFT 510 and Equations 1 and 2 above, attention should be paid to the phase angle (i.e., Φ) of the nth partial. n This can indicate the relative position of the toe 205. Specifically, the phase angle of the nth partial (i.e., Ф) n The position of the toe 205 can be indicated as a portion of the distance between two adjacent protrusions 310 in the rotating housing 20. Referring to Table 6 and Figure 14 above, the total distance between two adjacent protrusions can be considered as 360 degrees, and the phase angle value of the nth sub-tone (i.e., Ф) n Dividing by 360 degrees indicates the percentage of the total distance between two adjacent protrusions. This can be seen, for example, by comparing column #2 in Tables 5 and 6 above. As mentioned above, Ф n =The phase angle of the nth partial, C n = The amplitude of the nth tone. As described above, considering the number of protrusions L in the rotating housing 20 and the number of generated reference signals, as well as the resulting order Oi of the signal of interest, the FFT 510 can be set to transmit the phase angle Φ of the nth tone. n The amplitude C of the nth partial n The phase angle of the nth partial (i.e., Ф) n This can indicate the relative position of the toe 205. Furthermore, as described above, FFT 510 can be set such that the variable X is a positive integer, where...

[0584] X=Oi Z / Y

[0585] And among them,

[0586] Oi is set to an integer value.

[0587] Y is set to an integer value.

[0588] Z is set to an integer value.

[0589] Figure 24A schematic top view of another system 700 including a tumbling mill 10 is shown. For example, the tumbling mill 10 may be an autogenous (AG) mill. Alternatively, the tumbling mill 10 may be a semi-autogenous (SAG) mill. Another example of a tumbling mill 10 is a ball mill 10. The tumbling mill 10 includes a housing 20 having an inner housing surface 22, the inner housing surface forming a chamber 25 for grinding materials. Figure 24 The tumbling mill system 700 can be configured as described in any other embodiment described in this specification, for example, with respect to Figure 1 above. Figure 31 However, despite Figure 1A and / or Figure 1B The tumbling mill system is described as having a vibration sensor 70 on the input side of the mill, but it should be noted that... Figure 24 The tumbling mill system 700 can be configured to have:

[0590] Used to generate the first measurement signal S EAIN First vibration sensor 70 IN ,as well as

[0591] Used to generate the second measurement signal S EAOUT The second vibration sensor 70 OUT .

[0592] By the first vibration sensor 70 IN The first measurement signal S generated EAIN Signal processing can be performed as described in any other embodiment of the present disclosure regarding signal S EA As described, for example, regarding Figure 1 above - Figure 31 Similarly, by the second vibration sensor 70 OUT The generated second measurement signal S EAOUT Signal processing can be performed as described in any other embodiment of the present disclosure regarding signal S EA As described, for example, regarding Figure 1 above - Figure 31 Therefore, the difference compared to the above embodiments is that in system 700, the measurement signal S is based on... EAIN It provides data indicating the internal state of the input side of the tumbling mill, and is based on the second measurement signal S. EAOUT It provides data indicating the internal state of the output side of the tumbling mill. Therefore, regarding the provision of position signals or reference signals, Figure 24 The tumbling mill system 700 can be configured as described in any embodiment of this disclosure.

[0593] Figure 24The analysis device 150 shown may include a first state parameter extractor 4501 and a second state parameter extractor 4502. State parameter extractors 4501 and 4502 may operate as described in any other described embodiment, for example, referring to... Figure 5 and / or Figure 15 And / or as about Figures 30-31 Described. Therefore, the first state parameter extractor 4501 can be configured to generate parameters S. P1 (r), R T1 (r), f ROT (r), dS P1 (r) and dR T1 (r).

[0594] Similarly, the second state parameter extractor 4502 can be configured to generate parameters S. P2 (r), R T2 (r), f ROT (r), dS P2 (r) and dR T2 (r). However, the rotational speed f of the casing ROT (r) is of course the same, therefore if a state parameter extractor transmits the rotational speed value f ROT (r) is sufficient.

[0595] refer to Figure 24 The diagram shows a Cartesian coordinate system with three mutually perpendicular axes x, y, and z. It should be understood that during the operation of the mill 10, the material 30 travels from the input side 80 to the output side 90 of the mill in the positive x-axis direction.

[0596] Figure 24 The 700 tumbling mill system advantageously provides parameters indicating the internal state of the tumbling mill's input side: S P1 (r), R T1 (r), dS P1 (r) and dR T1 (r), and parameters indicating the internal state of the output side of the tumbling mill: S P2 (r), R T2 (r), dS P2 (r) and dR T2 (r).

[0597] Comparing input-side parameters with their corresponding output-side parameters can advantageously add another dimension to the understanding of the internal state of mill 10. For example, R T2 (r) and R T1 The relationship between (r) indicates that:

[0598] - Is the toe position the same on the input and output sides, or

[0599] - Is the toe position higher on the input side, when R T1 (r)>R T2 (r) indicates; or

[0600] - Is the toe position higher on the output side, when R T2 (r)>R T1 (r) indicates the time.

[0601] A higher toe position on the output side can indicate initial abnormalities. For example, a decrease in the outflow of output material 95 may be due to blockage, while the continued inflow of solid material 110 at an unreduced rate increases the risk of overload, potentially leading to reduced efficiency of the grinding process in the tumbling mill. Therefore, Figure 24 The tumbling mill system 700 can advantageously provide early indication of initial anomalies. Therefore, based on the comparison of input-side parameters with corresponding output-side parameters, the tumbling mill system 700 can adjust control parameters to avoid anomalies such as mill overload.

[0602] refer to Figure 24 It should be noted that the vibration sensor 70 OUT The non-rotating part connected to the main body of the mill structure 10, and the vibration sensor 70 OUT The sensor is positioned to primarily detect vibrations in the horizontal Y direction (see Cartesian coordinate system with three mutually perpendicular axes x, y, and z, where Y is the horizontal direction). Similarly, vibration sensor 70... IN The non-rotating part connected to the main body of the mill structure 10, and the vibration sensor 70 IN The sensor is positioned to primarily detect vibrations in the horizontal Y direction. Experimental measurements appear to indicate that when the vibration sensor is configured to primarily detect vibrations in the horizontal Y direction, the vibration signal quality is improved compared to when the vibration signal quality is obtained when the vibration sensor is configured to primarily detect vibrations in the vertical Z direction. As described above, for example, in combination with... Figure 2 The protrusion 310 interacts with the toe 205 of the charge, forcing the material in the toe to accelerate in the direction of movement of the protrusion 310, such as... Figure 2 As shown, this causes mechanical vibration V IMP The impact of protrusion 310C on a large amount of material in the toe portion 205 causes a large amount of material in the toe portion to be affected by the movement of protrusion 310C. ACC The acceleration in the direction results in a force F on the leading edge surface of the protrusion 310C. IMP Since the mass of the solid material in the mill's charge 30 is measured in metric tons, the impact force F... IMPIt is quite large. However, since the mill structure is typically placed on a very hard floor surface that tends to dampen vibrations in the vertical direction, it may appear that vibration detection in the horizontal Y direction provides improved vibration signal quality.

[0603] Figure 25 A schematic top view of yet another embodiment of a system 720 including a tumbling mill 10 is shown.

[0604] Figure 25 The 720 tumbling mill system can be combined as follows Figure 24 As described. However, despite Figure 24 The tumbling mill system 700 is described as having a vibration sensor 70 connected to the non-rotating portion of the main body of the grinding structure 10. OUT And a vibration sensor 70 connected to another non-rotating part of the main body of the grinding structure 10. IN ,but Figure 25 The difference in the tumbling mill system 720 is that it provides a vibration sensor 70 connected to the rotating housing 20 of the grinding structure 10. 20 .like Figure 25 As shown, a vibration sensor 70 is directly mounted on the rotating housing 20. 20 This will produce high amplitude, especially when the vibration sensor is 70. 20 When located outside the shell, directly on the side of the shell wall opposite to the protrusion 310.

[0605] Figure 25 The tumbling mill system 720 may optionally include:

[0606] Used to generate the first measurement signal S EAIN First vibration sensor 70 20IN ,as well as

[0607] Used to generate the second measurement signal S EAOUT The second vibration sensor 70 20OUT .like Figure 25 As shown, the first vibration sensor 70 20IN The measurement point 310 can be located closer to the input side 80 than the output side 90. IN It is securely attached to the outer surface of the housing 20. Additionally, the second vibration sensor 70... 20OUT The measurement point 310 can be located closer to the output side 90 than the input side 80. OUT It is firmly attached to the outer surface of the housing 20.

[0608] First vibration sensor 70 20IN Second vibration sensor 70 20OUTThe sensor 70 can be configured to communicate wirelessly with device 150, for example, via transceiver units 740 and 750 respectively. 20 70 20IN 70 20OUT It can be powered by a battery, or alternatively by a sensing device (not shown) connected to the outer surface of the rotating housing 20, which operates as a generator by interacting with one or more fixed permanent magnets. In this way, as the housing 20 rotates, the sensing device is repeatedly passed through the magnetic field of the fixed one or more permanent magnets, thereby inducing a field that can be used as a sensor 70. 20 70 20IN 70 20OUT The current of the power supply.

[0609] Figure 25 The tumbling mill system 720 can also advantageously provide parameters S indicating the internal state of the tumbling mill's input side. P1 (r), R T1 (r), dS P1 (r) and dR T1 (r) and the parameter S indicating the internal state of the output side of the rolling mill. P2 (r), R T2 (r), dS P2 (r) and dR T2 (r). Therefore, the technical reader of this disclosure draws a direct and explicit conclusion. Figure 25 The tumbling mill system 720 can advantageously be roughly similar to Figure 24 The 700-type tumbling mill system provides early indication of initial anomalies. Specifically, Figure 25 The tumbling mill system 720 can advantageously achieve the comparison of input-side parameters with corresponding output-side parameters in the manner described above with respect to the tumbling mill system 700. Therefore, Figure 25 The 720 roller mill system can also advantageously achieve the adjustment of control parameters, thereby avoiding, for example, abnormalities, such as mill overload.

[0610] Figure 26 A schematic diagram and top view of another embodiment of a system 730 including a tumbling mill 10 are shown. For example, the tumbling mill 10 may be an autogenous (AG) mill. Alternatively, the tumbling mill 10 may be, for example, a semi-autogenous (SAG) mill. Another example of a tumbling mill 10 is a ball mill 10. The tumbling mill 10 includes a housing 20 having an inner housing surface 22 that forms a chamber 25 for grinding materials. Figure 26 The tumbling mill system 730 may include components described in any other embodiment described in this disclosure, and is configured, for example, with respect to Figure 1- Figure 25 and / or as Figures 30-31As described. In particular, Figure 26 The device 150 shown can be configured as described in any other embodiment described in this disclosure, for example, with respect to FIG1- Figure 25 and / or as Figures 30-31 As described.

[0611] However, in Figure 26 In the embodiment of system 730 shown, device 150 includes a monitoring module 150A and a control module 150B. Although the device 150 is illustrated as two blocks in the figures, it should be understood that device 150 may also be provided as a single entity 150 including monitoring module 150A and control module 150B, as indicated by uniform reference numeral 150.

[0612] System 730 is configured to control the internal state of the tumbling mill 10, which has a rotational speed f. ROT The housing 20, which rotates about axis 60, is used for feeding material 30 by grinding the material in the rotating housing.

[0613] The housing 20 has an inner housing surface 22 including a first number L of protrusions 310 configured to engage material when the housing 20 rotates about an axis 60. The system 730 may include means 170, 180 for generating a position signal. Means 170, 180 may include a position sensor 170 and a marker 180, as described elsewhere in this disclosure. The position signal is E. P P(i), P(j), and P(q) indicate the rotational position of the rotating housing 20, and the position signal includes a time series of position signal sample values ​​P(i), P(j), and P(q).

[0614] Provide sensor 70, 70 IN 70 OUT 330, and it is configured to respond to mechanical vibration V originating from the rotation of the housing. IMP To generate vibration signal S EA S MD Se(i), S(j), S(q). Vibration signal S EA Se(i), S(j), and S(q) can include the time series of vibration sample values ​​Se(i), S(j), and S(q).

[0615] The device 150 of system 730 may include a monitoring module 150A and a control module 150B. The monitoring module 150A includes state parameter extractors 450, 4501, 4502, and 450C, which are configured to detect the first occurrence of a first reference position signal value in the time series of position signal sample values ​​P(i), P(j), and P(q) (see Tables 2, 3, and 4 above, where column #2 shows position signals with values ​​1 and 1C).

[0616] The state parameter extractor 450 can be configured to detect the second occurrence of the second reference position signal value 1, 1C, and 100% in the time series of the position signal sample values ​​P(i), P(j), and P(q). The state parameter extractor 450 can also be configured to detect event feature S in the time series of vibration sample values ​​Se(i), S(j), and S(q). P (r) The occurrence of Sp. This event can be caused by the protrusion 310 impacting the toe 205 of the charge 30, causing impact vibration, which can induce vibration signal characteristics as discussed elsewhere in this disclosure. The state parameter extractor 450 can be configured to generate an indication of the first time relationship R between the following. T (r), T D Data for FI(r) and X1(r):

[0617] Event characteristics appeared, and

[0618] First appearance and second appearance.

[0619] As described above, system 730 includes a control module 150B configured to receive data indicating the internal state of mill 10 from mill monitoring modules 150 and 150A. The data indicating the internal state may include any information generated or transmitted by the state parameter extractor 450, as described in this disclosure with respect to Figure 1- Figure 31 Any of those described. Reference Figure 26 The control module 150B includes an adjuster 755 for controlling the angle toe position FI(r), A based on the following: TOE (See) Figure 26 Combination Figure 2 ):

[0620] Toe position reference value FI REF (r) (see also) Figure 26 ),

[0621] The first time relationship R T (r), T D FI(r), X1(r) (see Figure 1-) Figure 31 ),as well as

[0622] Toe position error value FI ERR (r) (see also) Figure 26 ).

[0623] Toe position error value (FI) ERR (r) depends on the toe position reference value FI REF (r) and the first time relationship R T (r), T D FI(r) (see Figures 3-26 Toe position reference value FI REF (r) can be entered manually ( Figure 26 (Not shown in the image) is generated, but can be combined as shown above, for example. Figure 1A and / or Figure 1B To accomplish as discussed.

[0624] like Figure 26 As shown, the toe position error value (FI) ERR (r) can depend on the toe position reference value FI REF (r) and the first-time relationship R T (r), T D The difference between FI(r) and X1(r).

[0625] The adjuster 755 can be configured to adjust according to the toe position reference value FI. REF (r) is used to control the setpoint R of the solid material feed rate. SSP Combining Figure 1A The feed rate R of the solid material under discussion S Depends on the solid material feed rate setpoint R SSP (See) Figure 26 ). (e.g., combined) Figure 1A The solid material feed rate R is mentioned above. S It is the amount of solid material fed to the input end 100 of the tumbling mill 10 per unit time.

[0626] The adjuster can also be configured to adjust according to the toe position reference value FI. REF (r) is used to control the liquid feed rate setpoint R. LSP Liquid feed rate R L It may depend on the liquid feed rate setpoint R LSP For example, combining Figure 1A The liquid feed rate R is mentioned. L It can be the amount of liquid fed into the input end 130 of the tumbling mill 10 per unit time.

[0627] Event characteristics can indicate the impact force F generated when the protrusion 310 on the inner shell surface 22 of the rotating shell 20 interacts with the toe 205 of the charge material 30.IMP .

[0628] The state parameter extractor 450 can be configured to generate the first time relationship R. T (r), T D FI(r) and X1(r) are used as phase angles FI(r).

[0629] First-time relationship R T (r), T D FI(r) and X1(r) indicate the toe position 205, A TOE (r) (see also) Figure 2 Combination Figure 26 First-time relationship R T (r), T D FI(r) and X1(r) can indicate the ratio of the distance between two adjacent protrusions 310 in the mill housing.

[0630] Alternatively, the relational value X1(r) can indicate the relative position of the toe 205, that is, the position of the toe 205 relative to two predetermined stator positions that are separated from each other in a manner corresponding to the positions of two adjacent protrusions 310.

[0631] In addition, the relational value X1(r) can indicate the absolute toe position.

[0632] The absolute toe position, also known as Sp(r), can be generated based on a combination of the relation value X1(r) and the second internal state parameter X2(r). Specifically, the absolute toe position can be generated based on the time series of the combination of the first internal state parameter X1(r) and the second internal state parameter X2(r), for example, by combining... Figure 16 , Figure 17 , Figure 18 , Figure 19A and Figure 19B The subject of discussion. For example... Figure 19A As shown, the initial dataset 550(r) = 550(1) corresponding to X1 (r=1) and X2 (r=1) represents the mill in an unloaded or near-unloaded state. As the mill's filling degree increases, the absolute toe position increases in the direction of arrow 560A. Figure 19A and Figure 19B In the middle, from the initial angle FI TR The "angular length" indicator at current indicator 550(r) indicates the absolute toe position. Combined with... Figure 2 refer to Figure 19B , Figure 2 The toe angle of 0 degrees at 960° on the mid-vertical line can correspond to Figure 19B The initial angle FI in TR As r increases, the value of X2(r) increases at... Figure 19BThe distance from the origin is shown as an increase, and the mass of the toe 205 is also indicated as an increase, as discussed elsewhere in this document. When the value of parameter X1(r) increases to a value equal to 360 degrees, the toe position 205 is at a distance from the initial angle FI. TR At an angle distance of 360 / L.

[0633] When the value of parameter X1(r) increases to more than 360 degrees, it indicates that the absolute toe position 205 is located at a distance from the initial angle FI. TR At an angular distance of 360 / L+X1(r).

[0634] The state parameter extractor 450 can be configured to generate the event features as amplitude values ​​S. P (r), Sp, C L (r), C1(r), X2(r).

[0635] The state parameter extractor 450 may include components configured to generate the first temporal relationship R. T (r), T D Fourier converters 510 for FI(r) and X1(r) (see [reference]) Figure 15 ).

[0636] As discussed in Table 5, the state parameter extractor 450 can be configured to extract the total number N samples from the first occurrence to the second occurrence. B Counting is performed. Furthermore, the state parameter extractor 450 can be configured to perform a further number of samples N from the first occurrence to the occurrence of the event. P The counting is performed, and the state parameter extractor 450 can be configured to generate the first time relationship R based on the other quantity and the total number. T (r), T D , FI(r), X1(r).

[0637] The state parameter extractor 450 can be configured to extract the total number N samples from the first occurrence to the second occurrence. B The counting is performed, and the state parameter extractor 450 can be configured to perform a further number of samples N from the first occurrence to the occurrence of the event. P Counting is performed. Furthermore, the state parameter extractor 450 can be configured to generate the first time relationship R based on the relationship between the other quantity and the total number. T (r), T D FI(r), wherein the relationship between the other quantity and the total number can indicate the toe position 205.

[0638] According to one embodiment, the regulator 755 operates to control the toe position on the input side (FI) based on the following:IN (r), A TOE_IN ):

[0639] Toe position reference value (FI) REFIN (r)),

[0640] First time relationship (FI) IN (r)), and

[0641] Toe position error value (FI) ERRI (r)), where,

[0642] The toe position error value (FI) ERRI (r) depends on the following:

[0643] The toe position reference value (FI) REFIN (r)), and

[0644] The first time relationship (R) T (r); T D ;FI IN (r)).

[0645] According to one embodiment, the adjuster 755 operates according to the toe position reference value FI. REFIN (r) Control the setpoint R of the solid material feed rate SSP .

[0646] According to one embodiment, regulator 755 operates to control the solid material feed rate setpoint R based on the following: SSP :

[0647] Toe position reference value (FI) REFIN (r)),

[0648] First time relationship (FI) IN (r)), and

[0649] Toe position error value (FI) ERRI (r)), where,

[0650] The toe position error value (FI) ERRI (r) depends on the following:

[0651] The toe position reference value (FI) REFIN (r)), and

[0652] First time relationship (FI) IN (r)).

[0653] although Figure 26 , Figure 28 and Figure 29Two feedback signals are shown, namely the first time relationship FI related to the input side of mill 10. IN (r) and the first time relationship FI related to the output side of mill 10 OUT (r), but it should be understood that the system can be operated with a single feedback signal. Therefore, for example, the regulator can be configured with a single input, for example, for receiving a first-time relationship FI related to the state of the mill's input side. IN (r).

[0654] According to one embodiment, regulator 755 operates to control the solid material feed rate setpoint R based on the following: SSP :

[0655] Toe position reference value (FI) REFOUT (r)),

[0656] First time relationship (FI) OUT (r)), and

[0657] Toe position error value (FI) ERRO (r)), where,

[0658] The toe position error value (FI) ERRO (r) depends on the following:

[0659] The toe position reference value (FI) REFOUT (r)), and

[0660] First time relationship (FI) OUT (r)).

[0661] The regulator 755 can be configured to include a proportional-integral-derivative (PID) controller. Alternatively, the regulator 755 can be configured to include a proportional-integral (PI) controller. Alternatively, the regulator 755 can be configured to include a proportional (P) controller.

[0662] Alternatively, regulator 755 can be configured to include Kalman filtering, also known as linear quadratic estimation (LQE). Kalman filtering is an algorithm that uses a series of measurements observed over time, including statistical noise and other inaccuracies, and produces estimates of the unknown variable by estimating the joint probability distribution of the variable over each time interval. These estimates tend to be more accurate than estimates based on a single measurement alone.

[0663] Figure 27A schematic block diagram of a distributed process monitoring system 770 is shown. Reference numeral 780 refers to a client location having a mill 10 with a rotatable housing 20, as discussed above with respect to the foregoing figures in this document. The client location 780, also referred to as a client section or mill location 780, may be, for example, a mining company site, or a site for an ore mill, or, for example, a manufacturing mill used to produce cement.

[0664] When one sensor 70 or several sensors 70, 70 IN 70 OUT The distributed process monitoring system 770 is operable when attached to or at a measurement point associated with housing 20. As described above, such a measurement point can be, for example, at bearings 40, 50 (see...). Figure 26 and Figure 27 Or at measurement point 310 IN 310 OUT (See place) Figure 25 ).

[0665] Measurement signal S EA S EAIN S EAOUT and E P (See, for example, Figure 1) Figure 27 , Figure 26 , Figure 25 This can be coupled to the input port of the mill position communication device 790. The mill position communication device 790 may include a device for measuring the signal S. EA S EAIN S EAOUT and E P The analog-to-digital converter 795 performs A / D conversion. The A / D converter 975 can operate as disclosed elsewhere in this document regarding the A / D converter 330, for example, in conjunction with... Figure 3 and Figure 5 The mill position communication device 790 has a communication port 800 for bidirectional data exchange. This communication port 800 can be connected to a communication network 810, for example, via a data interface 820, to realize data exchange corresponding to the measurement signal S. EA S EAIN S EAOUT and E P The communication network 810 can be the World Wide Web, also known as the Internet. The communication network 810 may also include a public switched telephone network.

[0666] Server computer 830 is connected to communication network 810. Server 830 may include database 840, user input / output interface 850, data processing hardware 852, and communication port 855. Server computer 830 is located at server location 860, which is geographically spaced from mill location 780. Server location 860 may be in a first city, such as Stockholm, the capital of Sweden, while mill location 780 may be in a rural area near the mill, and / or in another country, such as Norway, Australia, or the United States. Alternatively, server location 860 may be in a first part of a country, while mill location 780 may be in another part of the same country. Server location 860 may also be referred to as supplier component 860 or supplier location 860.

[0667] According to one example, central control location 870 includes a monitoring computer 880 with data processing hardware and software for monitoring and / or controlling the internal status of mill 10 at remote mill location 780. Monitoring computer 880 may also be referred to as control computer 880. Control computer 880 may include database 890, user input / output interface 900, and data processing hardware 910, as well as communication ports 920, 920A, or several communication ports 920, 920A, 920B. Central control location 870 may be geographically separated from mill location 780. Central control location 870 may be in a first city, such as Stockholm, the capital of Sweden, while mill location 780 may be in a rural area near the mill, and / or in another country, such as Norway, Australia, or the United States. Alternatively, central control location 870 may be in a first part of a country, while mill location 780 may be in another part of the same country. Control computer 880 may be coupled to communicate with mill location communication device 790 via communication ports 920, 920A. Therefore, the control computer 880 can receive the measurement signal S from the mill position communication device 790 via the communication network 810. EA S EAIN S EAOUT and E P (See, for example, Figure 1) Figure 27 , Figure 26 , Figure 25 ).

[0668] System 770 can be configured to receive measurement signal S in real time or near real time. EA S EAIN S EAOUT and E PAlternatively, it may be able to monitor and / or control the mill 10 in real time from location 870. Furthermore, the control computer 880 may include monitoring modules 150, 150A as disclosed in any example of this document, for example, as disclosed in conjunction with any of the above Figures 1-26.

[0669] The supplier company can occupy server location 860. The supplier company can sell and deliver equipment 150 and / or monitoring module 150A and / or software for such equipment 150 and / or monitoring module 150A. Therefore, the supplier company can sell and deliver software for control computer 880 at central control location 870. This software 370, 390, 400, for example, combines... Figure 4 This will be discussed. Such software 370, 390, 400 can be transmitted via transmission over the communication network 810. Alternatively, such software 370, 390, 400 can be transmitted as a computer-readable medium 360 for storing program code. Therefore, computer programs 370, 390, 400 can be provided as articles of manufacture including a computer storage medium in which the computer program is encoded.

[0670] According to an exemplary embodiment of system 770, monitoring computer 880 can receive measurement signals S from mill position communication device 790 substantially continuously, for example via communication network 810. EA S EAIN S EAOUT and E P (See, for example, Figure 1) Figure 27 , Figure 26 , Figure 25 This allows for continuous or near-continuous monitoring of the internal state of the mill 10. The user input / output interface 900 at the central control location 870 may include a screen 900S for displaying images and data, as discussed elsewhere in this document in conjunction with HCI 210. Therefore, the user input / output interface 900 may include a display or screen 900S, 210S for providing visual indications of the analysis results. The displayed analysis results may include information indicating the internal state of the tumbling process, enabling the operator 930 at the central control location 870 to control the tumbling mill 10.

[0671] Furthermore, the monitoring computer 880 at the central control location 870 can be configured to transmit information indicating the internal status of the tumbling process to the HCI 210 via communication ports 920, 920B and via communication network 810. In this way, the monitoring computer 880 at the central control location 870 can be configured to enable the operator 230 at the client location 780 to control the tumbling mill. The local operator 230 at the client location 780 can be located in the control room 220 (see...). Figure 1A and / or Figure 1B and / or Figure 27 Therefore, client locations 780, 220 may include a second mill position communication device 790B. The second mill position communication device 790B has a communication port 800B for bidirectional data exchange, and the communication port 800B can be connected to the communication network 810, for example, via a data interface 820B.

[0672] Although two position communication devices 790 and 790B have been described for clarity, alternatively, a single mill position communication device 790 and 790B and / or a single communication port 800 and 800B may be provided for bidirectional data exchange. Therefore, items 790 and 790B can be integrated into a single unit at mill position 780, and similarly, items 820 and 820B can be integrated into a single unit at mill position 780.

[0673] Figure 28 A schematic block diagram of yet another embodiment of the distributed process monitoring system 940 is shown. Reference numeral 780 relates to the mill position of mill 10, which has a rotatable housing 20, as discussed above with respect to the foregoing figures in this document. Figure 28 The distributed process monitoring system 940 may include components and be configured as described in any other embodiment described in this disclosure, for example, with respect to Figure 1- Figure 31 As described. Specifically, Figure 28 The monitoring device 150 shown, also referred to as monitoring module 150A, can be configured as described in any other embodiment described in this disclosure, for example, with respect to Figure 1- Figure 31 As described. Specifically, Figure 28 The process monitoring system 940 shown can be configured to include a monitoring module 150A, such as in combination with... Figure 27 It is publicly available, but located at the central control position 870.

[0674] In addition, Figure 28 In the process monitoring system 940 shown, the mill location 780 includes a control module 150B, as described above. Figure 26 As described.

[0675] Therefore, the internal state of the mill 10 can be automatically controlled by the control module 150B located at or near the mill position 780, and the monitoring computer 880 at the central control position 870 can be configured to transmit information indicating the internal state of the tumbling process to the HCI 900, 900S, so that the operator 930 at the central control position 870 can monitor the internal state of the tumbling mill 10.

[0676] Measurement signal SEA S EAIN S EAOUT and E P (See, for example, Figure 1) Figure 27 , Figure 26 , Figure 25 This can be coupled to the input port of the mill position communication device 790. The mill position communication device 790 may include a device for measuring the signal S. EA S EAIN S EAOUT and E P The analog-to-digital converter 795 performs A / D conversion. The A / D converter 975 can operate as disclosed elsewhere in this document regarding the A / D converter 330, for example, in conjunction with... Figure 3 and Figure 5 The mill position communication device 790 has a communication port 800 for bidirectional data exchange. The communication port 800 can be connected to a communication network 810, for example, via a data interface 820. The communication port 800 can be connected to the communication network 810, for example, via a data interface 820, to implement [data exchange] corresponding to the measurement signal S. EA S EAIN S EAOUT and E P The transmission of digital data.

[0677] Furthermore, the client location 780 may include a second mill location communication device 790B. The second mill location communication device 790B has a communication port 800B for bidirectional data exchange, and the communication port 800B can be connected to the communication network 810, for example, via a data interface 820B, so that data indicating the internal status of the mill 10 can be received by the control module 150B.

[0678] like Figure 28 As shown, data indicating the internal status of the mill 10 can be generated by the monitoring module 150A located at the central position 870.

[0679] Although for the sake of clarity, Figure 28 Two position communication devices 790 and 790B are described, but alternatively, a single mill position communication device 790 and 790B and / or a single communication port 800 and 800B may be provided for bidirectional data exchange. Therefore, items 790 and 790B can be integrated into a single unit at mill position 780, and similarly, items 820 and 820B can be integrated into a single unit at mill position 780.

[0680] Figure 29A schematic block diagram of yet another embodiment of the distributed process control system 950 is shown. Similarly, reference numeral 780 relates to the mill position of the mill 10, which has a rotatable housing 20, as discussed above with respect to the foregoing figures in this document. Figure 29 The distributed process monitoring system 950 can be components and configured as described in any other embodiment described in this disclosure, for example, with respect to Figure 1- Figure 31 As described. Specifically, Figure 28 and Figure 29 The monitoring device 150 shown, also referred to as monitoring module 150A, can be configured as described in any other embodiment described in this disclosure, for example, as with respect to Figure 1- Figure 31 The subject of discussion. Furthermore, Figure 29 The process monitoring system 950 shown can be configured to include the above-mentioned combination Figure 26 The described control module 150B and how it is combined Figure 27 The publicly disclosed monitoring module is 150A.

[0681] exist Figure 29 In the example, monitoring module 150A and control module 150B are located at control position 870. Control position 870 can be located remotely from mill position 780. Data communication between control position 870 and mill position 780 can be provided via data ports 820 and 920 and communication network 810, as discussed above in conjunction with the preceding figures.

[0682] Figure 30 Another example is shown: a cross-sectional view of the intermediate portion 98 of the rotary mill housing 20 during operation. This view can be seen, for example, along... Figure 1A The line AA is cut off. According to... Figure 30 For example, the tumbling mill housing 20 has four protrusions 310, which are configured to engage the feed material 30 when the housing rotates about the axis 60, i.e., the number L=4. For clarity, Figure 23 The protrusions in the examples are referred to as 3101, 3102, 3103 and 3104, respectively.

[0683] A position sensor 170 is provided to generate a position signal Ep based on the rotational position of the housing 20. For example... Figure 30 As shown, the position sensor 170 is positioned along the vertical line 960 of the rotation axis 60, about which the housing 20 can rotate. Furthermore, a position mark 180 is provided on the outer surface of the housing 20, such that when the protrusion 310 passes the vertical line 960, the position sensor 170 generates a mark signal P. S When the tumbling mill housing 20 has four protrusions 310, such as Figure 30As shown, and when a single static position sensor 170 is provided, a first static position signal Ps1, P1 can be received in response to a first channel of a position marker 180 according to an example method, and a second static position signal Ps2 can be received in response to a second channel of the position marker 180. The method can then generate a virtual static position signal P in the recorded time series of position signal sample values. C When the protrusions are evenly distributed on the inner circumference of the shell 20, the generated virtual static position signal P is inserted. C This allows for a uniform distribution of the location signal sample values ​​throughout the recorded time series. This advantageously results in a recorded time series of location signal sample values ​​indicating L uniformly distributed static locations, such as... Figure 30 As shown. In Figure 30 In the example, there are four spikes, i.e., L=4, so the recorded time series of position signal sample values ​​indicates four static positions P1, P2, P3, and P4=PL. L static position signals P S P C This can then be used as a reference position signal. The event signal characteristics will also appear L times per revolution in the time series of the vibration signal sample values, and can be relative to a static position signal P. S P C Or two static position signals P S P C To analyze the occurrence of event signal characteristics.

[0684] As mentioned above, combined Figure 19A and Figure 19B It has been observed that when the mill is started from an unloaded state, the initial internal state indicator object appears at the initial polar angle Ф(1), which represents the first detected toe position 205 of the mill. Based on experimental measurements, it appears that the initial polar angle Ф(1) can be used as a reference toe position value. Therefore, the initial polar angle Ф(1) can be referred to as the reference toe position value Ф. TR Regarding its internal state, it is determined by... Figure 19A and Figure 19B The display 210S shown indicates a specific tumbling mill, with the reference toe position corresponding to an angle value Ф of approximately 47 degrees. TR ,like Figure 19A and Figure 19B As shown. Reference Figure 2 As shown in Figure 14, it is believed that if the position mark 180 is physically moved to a different position in terms of angular position, then the toe position value Ф is referenced. TR The angle value will change to a different numerical angle value.

[0685] refer to Figure 30It is believed that the position mark 180 is disposed on the outer surface of the housing 20 such that when the protrusion 310 passes the vertical line 960, the position sensor 170 generates a rotation mark signal value P. S This signal value will result in the reference toe position value Ф TR It has a very small value or zero value because the initial polar angle Ф(1)=Ф TR This indicates the first detected toe position when the tumbling mill is started from an unloaded state.

[0686] Regarding this, when the toe is located at the lowest part of the housing 20, the zero-degree absolute toe position X6 can be indicated at the position pointed to by the vertical line 960 from the rotation axis 60 (see [reference]). Figure 30 and Figure 2 ).

[0687] refer to Figure 30 , Figure 2 and Figure 14A and Figure 14B It is believed that if the position mark 180 physically moves to a different position in terms of angular location, then the toe position value Ф is referenced. TR The angle value will change to a different numerical angle value.

[0688] Figure 31 This is a block diagram illustrating another example of a state parameter extractor 450 (referred to as state parameter extractor 450C). As described below, state parameter extractor 450C may include a vibration event feature detector, a position signal value detector, and a relationship generator. As described below, the vibration event feature detector may be implemented by a peak detector.

[0689] According to various aspects of the solution disclosed in this document, reference position signal values ​​Ep, I, IC are generated at L predetermined rotational positions of the rotatable housing 20, the L predetermined rotational positions following a pattern reflecting the angular positions of L protrusions 310 in the housing 20. Providing these reference position signal values ​​Ep, I, IC in the manner disclosed herein, along with providing vibration event feature detection, enables the generation of data indicating the position of the toe 205 in an advantageously accurate manner.

[0690] Although this solution has been illustrated using an equidistant pattern positioning, i.e., protrusions 310 evenly distributed within the housing 20, this approach is also applicable to other patterns of angular positions of the L protrusions 310 within the housing 20. When using other patterns of angular positions of the L protrusions 310 within the housing, it is important to generate reference position signal values ​​Ep, I, IC at L predetermined rotational positions of the rotatable housing 20, the L predetermined rotational positions following a pattern that reflects the angular positions of the L protrusions 310 within the housing 20.

[0691] refer to Figure 5The A / D converter 330 can be configured to transmit a series of vibration measurement pairs S(i) associated with the corresponding position signal value P(i) to the state parameter extractor 450.

[0692] Figure 31 The state parameter extractor 450C is adapted to receive the measurement value sequence S(i) and the position signal sequence P(i) and the time relationship between them.

[0693] Therefore, a single measurement value S(i) is associated with a corresponding position value P(i). This signal pair S(i) and P(i) is transmitted to memory 970. (Reference) Figure 31 The state parameter extractor 450C includes a memory 970.

[0694] Memory 970 is operable to receive signal pairs in the form of S(i) and P(i) to enable analysis of the temporal relationships between events occurring in the received signals. Columns #2 and #3 in Table 3 provide illustrations of examples of data collected in memory 970 during one full revolution of the housing when six position signals 1, 1C are provided per revolution, due to the presence of L = 6 protrusions 310 in housing 20. Tables 4 and 5 provide more detailed information on example signal values ​​in the first 1280 time slots of Table 3.

[0695] Position signals 1 and 1C can be generated by physical marking device 180, and / or some position signals 1C can be virtual position signals. The time series of position signal sample values ​​P(i), P(j), P(q)) should be provided in a manner that reflects the occurrence pattern of the angular position of the protrusion 310 in the housing 20.

[0696] For example, when there are six (L=6) equidistant protrusions 310 in the housing 20, the angular distance between any two adjacent protrusions 310 is 60 degrees. This is because 360 ​​degrees is a complete circle, and when L=6, the angular distance between any two adjacent protrusions is 360 / L=360 / 6=60. Therefore, the corresponding time series representing the position signal sample value P(i) of a complete circle of the housing 20 should include six (L=6) position signal values ​​I, IC with corresponding occurrence patterns, as shown in Table 3.

[0697] The state parameter extractor 450C also includes a position signal value detector 980 and a vibration event feature detector 990. The vibration event feature detector 990 can be configured to detect vibration signal events, such as amplitude peaks in the received measurement sequence S(i).

[0698] The output of the position signal value detector 980 is coupled to the start / stop input 995 of the reference signal time counter 1010 and the start input 1015 of the event feature time counter 1020. The output of the position signal value detector 980 can also be coupled to the start / stop input 1023 of the vibration event feature detector 990 to indicate the start and stop of the duration to be analyzed. When a position signal value 1 or 1C is detected, the detector 990 sends a signal at its output.

[0699] The vibration event feature detector 990 is configured to analyze all sample values ​​S(i) between two consecutive position signal values ​​I and IC to detect the highest peak amplitude value Sp. The vibration event feature detector 990 has a first output 1021 coupled to the stop input 1025 of the event feature time counter 1020.

[0700] The reference signal time counter 1010 is configured to count the duration between two consecutive position signal values ​​1 and 1C, thereby generating a first reference duration value T at the output terminal 1030. REF1 This can be implemented, for example, using a reference signal timer 1010, which is a clock timer that counts the duration between two consecutive position signal values ​​1 and 1C. Figure 14B First reference duration value T REF1 The time duration between static position signal P4 and static position signal P5 can be indicated in this way.

[0701] Alternatively, the reference signal time counter 1010 can count the number of time slots between two consecutive position signal values ​​1 and 1C (see column #01 in Table 3).

[0702] The event characteristic time counter 1020 is configured to count the duration from the occurrence of the position signal value 1, 1C to the occurrence of the vibration signal event (such as amplitude peak). This can be achieved as follows:

[0703] - When the position signal value detector 980 detects the presence of position signal values ​​1 and 1C at the start input terminal 1015, the event feature time counter 1020 starts counting.

[0704] When the vibration event feature detector 990 detects a vibration signal event (such as an amplitude peak in the received measurement sequence S(i)) at the stop input 1025, the event feature time counter 1020 stops counting.

[0705] In this way, the event feature time counter 1020 can be configured to count the time duration from the occurrence of the position signal value 1, 1C to the occurrence of the amplitude peak. The time duration from the occurrence of the position signal value 1, 1C to the occurrence of the amplitude peak is referred to herein as the second reference duration value T. REF2 Second reference duration value T REF2 It can be transmitted on output terminal 1040. (See reference) Figure 14B The second reference duration value T REF2 This can be used to indicate the time duration between the occurrence of the static position signal P4 and the occurrence of the amplitude peak.

[0706] refer to Figure 31 The output terminal 1040 is coupled to the input terminal of the relation generator 1050 to provide the relation generator 1050 with a second reference duration value T. REF2 .

[0707] The relation generator 1050 also has a first reference duration value T coupled to receive from the output 1030 of the reference signal time counter 1010. REF1 The input terminal. The relation generator 1050 is configured to be based on the received second reference duration value T. REF2 and the received first reference duration value T REF1 Generate relation value X1. Relation value X1 can also be called R. T (r), T D FI(r). The housing 20 can generate L relational values ​​X1 for each revolution. Furthermore, the L relational values ​​X1 generated from a single rotation of the housing can be averaged to generate a value X1(r) for each rotation of the housing 20. In this way, the state parameter extractor 450C can be configured to transmit an updated value X1(r) once per revolution.

[0708] For clarity, the example of relation value X1 is generated as follows: Please refer to... Figure 31 Referring to column #03 in Table 4: Vibration sample values ​​S(i) are analyzed by the vibration event feature detector 990 to detect vibration signal features S. FIMP .

[0709] Vibration signal characteristics S FIMP This can be represented by the peak amplitude sample value Sp. Referring to Table 5, peak analysis results in the detection of the highest vibration sample amplitude value S(i). In the example shown, the vibration sample amplitude value S (i=760) is detected as maintaining the highest peak value Sp.

[0710] The peak value Sp has been detected in time slot 760, and the time relationship value X1 can be established.

[0711] In Table 5, in the time series of position signal sample values ​​P(i), the time slots carrying position signal values ​​1 and 1C are indicated as 0% and 100%, respectively.

[0712] As shown in the example in column #02 of Table 5, the time position of time slot i=760 is 59% of the time distance between time slot i=0 and time slot i=1280. In other words, 760 / 1280=0.59=59%.

[0713] Therefore, the position of toe 205 is expressed as a percentage of the distance between two adjacent static positions PC (see Table 5). Figure 14B The static positions P4 and P5 in the equation can be obtained using the following formula:

[0714] From the first reference signal appearing in sample number N0=0 to sample number N B The total number of samples in which the second reference signal appears in =1280 (N) B – N0 = N B – 0 = N B =1280) to count, and

[0715] From the occurrence of the first reference signal at N0=0 to the peak amplitude value Sp at sample number N P The number of other samples appearing at (N) P – N0 = N P –0 = N P ) to count, and

[0716] Based on the other quantity N P and the total number N B Generate the first time relationship (X1, R) T (r); T D ;FI(r)). This can be summarized as:

[0717] X1(r) = R T (r) = R T (760) = (N P – N0 ) / (N B – N0) = (760 - 0) / (1280-0)= 0.59 = 59%

[0718] Therefore, relative to the toe position X1, R T It can be generated in the following ways:

[0719] The total number of samples (N) from the occurrence of the first reference signal to the occurrence of the second reference signal. B ) to count, and

[0720] From the appearance of the first reference signal to the appearance of sample number N P The number of other samples (N) where the peak amplitude value Sp appears. P ) to count, and

[0721] Based on the number of samples N P With the total number of samples (i.e., N) B The relationship between X1 and R is used to generate the first time relationship (X1; R). T (r); T D ;FI(r)).

[0722] The relation generator 1050 can use a transmission frequency that depends on the rotational speed of the housing 20 to generate an update of the relation value X1.

[0723] As described above, the state parameter extractor 450C can be configured to transmit an update value X1(r) once per revolution. In this way, the transmitted update value X1(r) can be based on L values ​​generated during one revolution. The latest update of the first internal state parameter X1(r), numbered r, can be transmitted at the output 1060 of the first state parameter extractor.

[0724] refer to Figure 31 The vibration event feature detector 990 can be configured to detect peak amplitude sample values ​​Sp. The vibration event feature detector 990 has an output terminal 1070 for transmitting the detected peak amplitude Sp of the vibration signal. The detected peak amplitude Sp of the vibration signal can be transmitted from the output terminal 1070 of the vibration signal peak amplitude detector 990 to the output terminal 1080 of the state parameter extractor 450C. The output terminal 1080 constitutes the output terminal of the second state parameter extractor for transmitting a second internal state parameter X2(r), also referred to as Sp(r). The second internal state parameter X2(r) is transmitted at the same transmission frequency as the first internal state parameter X1(r).

[0725] Furthermore, the first internal state parameter X1(r) and the second internal state parameter X2(r) are preferably transmitted simultaneously as a set of internal state parameter data (X1(r); X2(r)). In the symbol X1(r), "r" indicates the number of samples in the time slot, that is, increasing the value of "r" indicates the time progress, in the same way as the number "i" in column #01 of Table 3.

[0726] As mentioned elsewhere in this document, vibration signal characteristics S FIMP The magnitude of the peak amplitude sample value Sp appears to depend on the impact force F. IMP The size of the impact force F resulting from the interaction between the rotating protrusion 310 and the material charge 30. IMP This causes at least one particle in the toe 205 of the material charge 30 to accelerate, and the impact causes a mechanical impact vibration V.IMP . refer to Figure 2 It should be noted that the impact of protrusion 310C on a large amount of material in the toe region 205 causes a large amount of material in the toe region to be lost in A. ACC Accelerate in direction. Direction A ACC This is the direction of movement of protrusion 310C. This acceleration results in a force F against the leading edge surface 312C of protrusion 310C. IMP The impact force F IMP It can be estimated to be on the order of magnitude:

[0727] F IMP = m 205 a 205

[0728] in,

[0729] m 205 It is the mass of the accelerated portion of the toe.

[0730] a 205 It is the magnitude of the acceleration of that part of the toe.

[0731] In view of the above, the inventors conclude that the magnitude of the detected peak amplitude sample value Sp can advantageously indicate the charge density in the tumbling mill 10.

[0732] In this case, it should be noted that the content of the desired metal in the solid material 110 of the charge material 30 affects the charge density in the tumbler mill 10, as discussed in conjunction with Table 1 in this document. Therefore, the charge density in the tumbler mill 10 can indicate the relationship between the desired metal and the waste mineral in the charge of the tumbler mill 10.

[0733] Therefore, the inventors concluded that the magnitude of the detected peak amplitude sample value Sp can advantageously indicate the relationship between the desired metal and the waste mineral in the charge of the tumbling mill 10.

[0734] Furthermore, the inventors concluded that the magnitude of the detected peak amplitude sample value Sp, combined with the data indicating the toe position, i.e. the aforementioned relational value X1, can advantageously indicate the filling degree of the tumbling mill 10.

[0735] In this regard, it should be noted that the filling degree of the tumbling mill 10 affects the efficiency of the grinding process. In order to maximize the amount of output material 95 from the tumbling mill 10, it is desirable to control the inflow of input material 110 in order to maintain the optimal state of the tumbling process, including the optimal filling degree. The optimal internal state of the tumbling process may include a certain filling degree of the housing 20, i.e., a certain loading volume.

[0736] Therefore, the feed rate setpoint R of the solid material can be controlled based on the combination of the relational value X1(r) and the detected peak amplitude sample value X2(r). SSP .

[0737] Furthermore, the inventors concluded that the magnitude of the detected peak amplitude sample value Sp(r)=X2(r), combined with the data indicating the toe position, i.e. the relational value X1(r) discussed above, can advantageously indicate the absolute toe position value X6(r) of the tumbling mill 10.

[0738]

[0739] exist Figure 19A and Figure 19B It can be seen from this that the gradually increasing polar angle X1(r) = FI(r) combined with the gradually increasing radius value X2(r) = S P (r) presents an image of the rotating arm rotating outward from the first internal state indicator object 550 (1), as shown in the image. Figure 19A The curved arrow 560A in the diagram shows the "angular length" X6(r) of the helical arm from the initial polar angle Ф(1) of the first internal state indicator object 550(1) to the currently or most recently detected toe position FI(r), which appears to indicate the absolute position X6(r) of the toe 205 (see, for example, the curved arrow 560A). Figure 2 (and Figure 14). In this regard, it should be noted that... Figure 19A In the polar coordinate system 520, 360 degrees corresponds to a relative toe position value X1 that indicates 100% of the distance between two adjacent static reference positions, as shown in the context of... Figure 14B The subject of discussion.

[0740] Special attention should be paid to the reference. Figure 19A and Figure 19B The change in the absolute toe position X6 is somewhat slow.

[0741] Figure 32 This is a block diagram of a rolling mill system 5, 320, 770, including block 10 which receives multiple inputs U1, ... Uk and generates multiple outputs Y1, ... Yn. (Reference) Figure 32 and Figure 1C It should be noted that, for analytical purposes, the tumbling mill 10 can be considered as a black box 10B with multiple input variables, referred to as input parameters U1, U2, U3, ..., Uk, where the index k is a positive integer. During the operation of the tumbling mills 10 and 10B, the tumbling mill has an internal state X, and for analytical purposes, the tumbling mill 10 can be considered as a black box 10B with multiple output variables, referred to as output parameters Y1, Y2, Y3, ..., Yn, where the index n is a positive integer.

[0742] The internal state X of the mill can be described or indicated by multiple internal state parameters X1, X2, X3, ..., Xm, where the index m is a positive integer.

[0743] In linear algebra terminology, the input variables U1, U2, U3, ..., Uk can be collectively referred to as the input vector U. Therefore, the dimension of the input vector U is k:

[0744] Input vector U: Dim(U)=k

[0745] Similarly, the internal state parameters X1, X2, X3, ... Xm can be collectively referred to as the internal state vector X.

[0746] The dimension of the internal state vector X is m:

[0747] Internal state vector X: Dim (X) = m

[0748] The output parameters Y1, Y2, Y3, ... Yn can be collectively referred to as the output vector Y:

[0749] The dimension of the output vector Y is n:

[0750] Output vector Y: Dim(Y) = n

[0751] At a time point called r, the internal state X of the mill 10 can be referred to as X(r). This internal state X(r) can be described or indicated by a plurality of internal state parameters X1, X2, X3, ..., Xm, as described above. These internal state parameters define different aspects of the internal state X(r) of the mill 10 at time r.

[0752] The internal state X(r) of the mill 10 depends on the input vector U(r). One aspect of the internal state X is the total amount of material 30 in the housing 20, and this total amount does not change immediately. Therefore, during the operation of the mill 10, the internal state X(r) can be considered as a function of the earlier internal state X(r-1) and the input U(r):

[0753] X(r) = f1(X(r-1), U(r) ), (Formula 4)

[0754] Wherein, X(r-1) indicates the internal state X of mill 10 at a time point before time point r.

[0755] The output Y of the tumbling mill 10 can be considered as a function of the internal state X. Therefore, in linear algebra terms, the output vector Y(r) depends on the internal state vector X(r):

[0756] Y(r) = f2(X(r)) (Formula 5)

[0757] One aspect of this document aims to address the problem of maintaining the internal pulverizing process of mill 10 at a suitable operating point. Therefore, during the operation of mill 10, it may be desirable to offset deviations from this suitable operating point. This problem can be solved by providing a linearized model of the pulverizing process at the operating point. The functions f1 and f2 described above can be linear when considered at operating points near the suitable operating point. Therefore, at a selected operating point, the internal state X(r) can be considered as a function of the earlier internal state X(r-1) and the input U(r) according to the linear model, which can be written as follows:

[0758] X(r) = A X(r-1) + B U(r) (Formula 6)

[0759] Here, A and B are coefficient matrices.

[0760] In this respect, it should be noted that in linear algebra, the coefficient matrix is ​​a matrix that contains the coefficients of the variables in a set of linear equations. As the technical reader of this document will know, the coefficient matrix is ​​used to solve systems of linear equations.

[0761] In this regard, it should be noted that the coefficients in matrices A and B can be constants.

[0762] Similarly, at a selected operation point, the output vector Y(r) depends on the internal state vector X(r) according to a linear model, which can be written as follows:

[0763] Y(r) = C X(r) (Formula 7)

[0764] Where C is the coefficient matrix.

[0765] However, Formula 7 does not imply that a change in state X must immediately translate into a change in state Y, because there may sometimes be a delay between the occurrence of a change in internal state X and the corresponding change in state Y(r) of product materials 95 and 96. However, when operating in steady state, a causal relationship appears to exist between the internal state X of the pulverizing process occurring in mill 10 at time r and the state Y(r) of product materials 95 and 96 at the same time r. Therefore, Formula 7 is valid, at least when operating mill 10 in steady state.

[0766] Referring to Formula 7, the coefficients in matrix C can be constants. The constant values ​​of the coefficients in matrix C can be determined at the selected operation point X. OP Set the derivative as C = dY / dX.

[0767] refer to Figure 32The system includes a monitoring module 150A for generating an m-dimensional internal state vector X, where m is a positive integer. In one example, Dim(X) is at least 2. The values ​​in the internal state vector X can be expressed as described above regarding... Figures 1A to 31 Generate in any of the publicly disclosed methods.

[0768] The monitoring module 150A can be adapted to transmit, for example, information describing the internal state X of the mill 10 via user interface 210, as indicated by arrow 1122. Therefore, one or more values ​​of the internal state vector X can be transmitted to the operator 230 via user interface 210. This advantageously simplifies the operator 230 of the mill 10 in making appropriate adjustments 1124 to the setpoint value (index SP) to affect the input vector U. Thus, by adjusting, for example, the speed setpoint value U1... SP (See) Figure 32 Combination Figure 1B Operator 230 can adjust the speed f ROT , U1.

[0769] In this way, the operator adjusts the relevant setpoint value U SP The corresponding input variables U1, U2, U3, ..., Uk can be adjusted.

[0770] Set point value U1 SP U2 SP U3 SP ...Uk can be collectively referred to as the setpoint vector U. SP Therefore, let the point vector U be defined. SP The dimension is k:

[0771] Set point vector U SP Dim (U SP ) = k

[0772] Figure 32 Systems 5, 320, and 770 may include the monitoring module 150A described in any other embodiment described in this disclosure, for example, regarding Figure 1- Figure 31 Any one of them.

[0773] Figure 33 This is a block diagram of another system 730, 940, 950, which includes a tumbling mill of block 10, illustrated as receiving multiple inputs U1, ... Uk and generating multiple outputs Y1, ... Yn.

[0774] Figure 33 The system 940 may include a monitoring module 150A as described in any other embodiment described in this disclosure, for example, regarding Figure 1- Figure 31 Any one of them. Furthermore, Figure 33The system 940 may include a control module 150B, as described in any other embodiment described in this disclosure, for example, regarding Figure 28 .

[0775] Figure 33 The monitoring module 150A can be adapted to transmit information describing the internal state X of the mill 10 during operation, for example, via a user interface 210. Therefore, one or more values ​​of the internal state vector X can be transmitted 1122 to the operator 230 via the user interface 210, as indicated by arrow 1122. This advantageously simplifies the operation of the mill 10 by the operator 230 with regard to the mill setpoint value U and / or the internal state reference value X. REF (Index REF) Make appropriate adjustments 1126 to affect the internal state X of the mill during operation of the mill 10. Arrow 1126 indicates, for example, the desired internal state X. REF Relevant user input. Internal state reference parameter X1 REF X2 REF X3 REF , ..., Xm REF They can be collectively referred to as the internal state reference vector X. REF .

[0776] Internal state reference vector X REF The dimension is m:

[0777] Internal state reference vector X REF Dim (X) REF ) = m

[0778] In this way, operator 230 adjusts the mill setpoint value U and / or the relevant internal state reference parameter value X1. REF X2 REF X3 REF , ..., Xm REF The internal state X of the mill can be affected during the operation of mill 10. Therefore, in response to user input, user interface 210 can be configured to generate an internal state reference vector X. REF The value of .

[0779] like Figure 33 As shown, the internal state reference vector X REF It is transmitted to the reference input terminal of control module 150B. Combined with... Figure 26 refer to Figure 33 The control module 150B is a multivariable control module, and the control module 150B also receives the aforementioned internal state vector X from the monitoring module 150A.

[0780] In this regard, the internal state vector X can indicate the current state of the grinding process in mill 10, and the internal state reference vector XREF Indicates the desired state of the grinding process.

[0781] The multivariable control module 150B is adapted to be based on the received internal state reference vector X. REF The received internal state vector X is used to generate the internal state error vector X. ERR .

[0782] Internal state error vector X ERR Including internal state error value X1 ERR X2 ERR X3 ERR , ..., Xm ERR

[0783] Internal state error vector X ERR The dimension is m:

[0784] Internal state error vector X ERR Dim (X) ERR ) = m

[0785] The error vector is transmitted to regulators 755 and 755C. Figure 33 The regulators 755 and 755C are suitable for generating the setpoint vector U. SP A multivariable regulator. Therefore, the setpoint vector U SP This includes the setpoint values ​​of the corresponding input variables U1, U2, U3, ... Uk mentioned above for controlling or adjusting (see...). Figure 33 and Figure 34 ).

[0786] Therefore, regarding Figure 33 The described system advantageously simplifies the operation of mill 10 by transmitting information 1122 indicating the internal state X of the mill during operation, while also allowing the operator to provide 1126 information describing the desired internal state, for example, using the aforementioned internal state reference vector X. REF The reference value is in the form of a reference value.

[0787] Regulators 755 and 755C can be multivariable regulators configured to include a multivariable proportional-integral-derivative (PID) controller. Alternatively, regulators 755 and 755C can be configured to include a multivariable proportional-integral (PI) controller. Alternatively, regulators 755 and 755C can be configured to include a multivariable proportional (P) controller.

[0788] Alternatively, regulators 755 and 755C can be configured to include Kalman filtering, also known as linear quadratic estimation (LQE). Kalman filtering is an algorithm that uses a series of measurements observed over time, including statistical noise and other inaccuracies, and produces estimates of unknown variables by estimating the joint probability distribution of the variable over each time interval. These estimates tend to be more accurate than estimates based on a single measurement alone.

[0789] Figure 34 Another schematic diagram of a system 1130 including a tumbler mill 10 is shown. Therefore, reference numeral 1130 refers to a system including a mill 10 having a rotatable housing 20, as described herein. Figure 34 System 1130 may include multiple components, and may be as described above. Figure 1A and / or Figure 1B The configuration described and / or as described in any other example described in this disclosure, for example, regarding Figure 1- Figure 33 .

[0790] The monitoring module 150A may include a state parameter extractor function, as described elsewhere in this document, for generating internal state parameter values ​​X1, X2, X3, ..., Xm. It should be noted that at a time point referred to as r, the internal state X of the mill 10 may be referred to as X(r). This internal state X(r) may be described or indicated by multiple parameter values ​​that define different aspects of the internal state X(r) of the mill 10 at time r. Therefore, the values ​​of the internal state parameters X1, X2, X3, ..., Xm at time r can be collectively referred to as the internal state vector X(r).

[0791] Figure 34 The system shown can provide integrated HCI 210, 250, and 210S. Therefore, Figure 34 The input / output interface 210 can be configured to enable all of the above inputs and / or outputs. Additionally, Figure 34 The input / output interface 210 can be configured to provide 1132 information related to the state of the output material. The state of the output material can be described by output parameters Y1, Y2, Y3, ... Yn, collectively referred to as the output vector Y. As mentioned above, the dimension of the output vector Y is n:

[0792] Output vector Y: Dim(Y) = n

[0793] Vector Y can also be called the expelled material state vector Y.

[0794] Figure 34System 1130 includes regulator 1190. Regulator 1190 can be configured to enable all the functions described with reference to regulator 240, which is described elsewhere in this document. Alternatively, regulator 1190 can be configured to enable all the functions described with reference to regulator 755, which is described elsewhere in this document. In addition to the functions described in regulator 240 and / or regulator 755, regulator 1190 can also be configured to perform additional functions, such as transmitting and / or receiving information related to output materials 95, 96, for example, in the form of output parameters Y1, Y2, Y3, ... Yn. Therefore, regulator 1190 can also be indicated by reference numerals 240C and / or 755C.

[0795] Therefore, regulator 1190 can be configured to transmit information related to output materials 95, 96 to mill operator 230, as shown by arrow 1132. Furthermore, as shown by arrow 1196, regulator 1190 can be configured to receive information related to output materials 95, 96 from mill operator 230.

[0796] Figure 35 It can be made by Figure 34 A general schematic diagram of the information transmitted by the input / output interface 210. (Reference) Figure 34 and Figure 35 It should be noted that Figure 34 The regulators 1190 and 755C are coupled via coupling 1100 for data exchange with the input / output interface 210. The information to be transmitted via coupling 1100 includes the aforementioned internal state reference vector X. REF Reference values.

[0797] refer to Figure 34 System 1130 includes a product analyzer 1140 configured to analyze at least a portion of the product particles 96. The analyzer 1140 is configured to generate at least one product measurement value Y1, Y2, Y3, ... Yn based on the product particle analysis.

[0798] In practice, at least one output material measurement value Y1, Y2, Y3, ... Yn can indicate the discharged material state Y, which is the instantaneous state of the output material 95. When the analyzer 1140 provides two or more output material measurements, these values ​​can be provided in the form of the aforementioned output vector Y.

[0799] The at least one product measurement may, for example, include an indicator of the product discharge rate R. SDis The value of R. The product's discharge rate R. SDis It can also be referred to as the output parameter Y1.

[0800] The instantaneous state of the output material 95, i.e., the discharged material state Y, can be identified by measuring at least one output material measurement value Y1, Y2, Y3, ... Yn. In practice, it may be desirable to generate more than one output material measurement value in order to obtain information indicating the discharged material state (Y).

[0801] At least one output material measurement value can be selected from one or more of the following groups:

[0802] The values ​​Y1 and Y2 indicate the mass per unit time of the output material 95;

[0803] The values ​​Y1 and Y2 indicate the mass of the product particles 96 per unit time;

[0804] The values ​​Y1 and Y2 indicate the median particle size.

[0805] The values ​​Y1 and Y2 represent the mass per unit time of the product particles 96 whose particle size is below the predetermined particle size limit;

[0806] Values ​​Y1 and Y2 indicate the proportion or percentage share of product particles between the lower limit and the upper limit of product particle size;

[0807] The values ​​Y1 and Y2 indicate the number of product particles whose particle size is between the lower limit and the upper limit of the product particle size.

[0808] Indicating the particle size distribution Y of the product, such as the standard deviation values ​​Y1, Y2; and

[0809] Indicates the particle size values ​​Y1 and Y2 of the product.

[0810] The particle sizes Y1 and Y2 of the product can be selected from at least one of the following groups:

[0811] -Mean particle size of the product;

[0812] - Average particle size of the product;

[0813] -The median diameter of the product particles; and

[0814] - Average diameter of product particles.

[0815] The particle size limit value of the product can be selected from at least one of the following groups:

[0816] -Product particle diameter value; and

[0817] - Maximum width of product particles.

[0818] The values ​​Y1 and Y2 indicating the particle size distribution Y of the product can be selected from at least one of the following groups:

[0819] -Standard deviation value;

[0820] - Variance value;

[0821] - The range between the highest and lowest granularity;

[0822] -Quarterial range.

[0823] The range between the minimum granularity value and the maximum granularity value can be between the following:

[0824] 30 micrometers and 20 millimeters;

[0825] 150 micrometers and 300 micrometers;

[0826] 200 micrometers and 220 micrometers; and / or

[0827] 0 mm and 40 mm.

[0828] Therefore, the product analyzer 1140 can be configured to analyze at least a portion of the product particles 96 to generate at least one product measurement value Y1, Y2, Y3, ... Yn based on the product particle analysis. The at least one product measurement value Y1, Y2, Y3, ... Yn can be configured with information indicating the time point at which the at least one product measurement value Y1, Y2, Y3, ... Yn is generated.

[0829] Furthermore, at time point w, the discharged material state Y can be referred to as Y(w). This discharged material state Y(w) can be described or indicated by multiple parameter values ​​Y1(w), Y2(w), Y3(w), ...Yn(w), which define different aspects of the materials 95, 96 discharged from mill 10 at time w. Therefore, the discharged material parameter values ​​Y1, Y2, Y3, ...Yn at time w can be collectively referred to as the discharged material state vector Y(w), also known as the output vector Y(w).

[0830] As mentioned above, there is a causal relationship between a certain internal state X(r) and a certain output Y(r), so the output Y of the tumbling mill 10 can be considered as a function of the internal state X.

[0831] refer to Figure 34 The output vector Y can be transmitted to the first input of correlator 150C1. Furthermore, the internal state vector X can be transmitted by module 150A to the second input of correlator 150C1. Correlator 150C1 is configured to identify the correspondence between the internal state X and the corresponding output Y.

[0832] However, to perform the correlation, it is desirable to ensure that the measured value of the output Y(w) points to at least approximately the same time point as the internal state X(r). In other words, the values ​​in the internal state vector X(r) may need to be synchronized with the values ​​in the corresponding output vector Y(w). (See reference...) Figure 34 The output vector Y(w) can be transmitted to the first input of the optional synchronizer 1150. The synchronizer 1150 is optional because it may not be necessary, for example, when the internal state vector X(r) and the corresponding output vector Y(w) are generated synchronously, such that...

[0833] - Time point w is the same time point as time point r, or

[0834] - Make time point w a point that is at least approximately the same as time point r.

[0835] like Figure 34 As shown, the time synchronization vectors X(t) and Y(t) are received by the correlation data generator 1160.

[0836] The correlation data generator 1160 generates a correlation dataset 1170. According to an example, the correlation data generator 1160 generates the correlation dataset by performing the following correlation analysis:

[0837] The received at least one state parameter value, for example, X1(t), and

[0838] At least one corresponding product measurement value received, for example, Y2(t).

[0839] The correlation data generator 1160 can receive multiple timestamped internal state vectors X(r) and multiple timestamped corresponding output vectors Y(w). The received information vectors can be received in a time-interleaved manner, such as X(10), Y(12), X(14), Y(16), X(18), Y(20), X(22), Y(24), where the synchronizer 1150 receives vector X in the time period between the reception of two consecutive vectors Y. For example, this is the case when vector X(18) is timestamped in the time period between t=20 and t=16, and vectors Y(16) and Y(20) are timestamped at the time points between t=16 and t=20, respectively. When the mill 10 is operated under steady-state conditions, i.e., when all values ​​in vectors X and Y are stable over time, the synchronizer 1150 can generate vector pairs X and Y by adjusting the timestamps so that the generated vector pairs X and Y have the same timestamp. This same timestamp can be, for example, an intermediate timestamp. For example, when the aforementioned vectors X(18) and Y(20) are received, synchronizer 1150 can arrange them into vector pairs labeled with an intermediate time t=19. Therefore, synchronizer 1150 can generate vector pairs X(t+1) and Y(t+2) in response to the receipt of vectors X(t) and Y(t+2) to transmit to correlation data generator 1160.

[0840] Furthermore, the transmission frequencies of the X and Y vectors can be different. This problem can be solved, for example, by configuring the synchronizer 1150 to transmit the following to the correlation data generator 1160:

[0841] The received vector pairs X and Y are such that each timestamp vector Y is associated with the vector X that has the closest earlier timestamp. Therefore, the synchronizer 1150 may have to discard or reject some vectors.

[0842] Therefore, for example, when the transmission frequency of vector X is lower than the transmission frequency of vector Y, synchronizer 1150 can receive vectors as follows:

[0843] Vector X (34).

[0844] Vector Y (36).

[0845] Vector X (37).

[0846] Vector Y (38)

[0847] Vector X (40).

[0848] Vector Y (40)

[0849] Vector Y (42)

[0850] Vector X (43).

[0851] Vector Y (44)

[0852] Synchronizer 1150 can then send vector X and Y pairs 1165 to correlation data generator 1160, such that each timestamped vector Y is associated with the vector X having the closest earlier timestamp. In the example above, synchronizer 1150 can send the following pairs:

[0853] Vector X (34), vector Y (36).

[0854] Vector X (37), vector Y (38).

[0855] Vector X (40), vector Y (40).

[0856] Vectors X (43) and Y (44), and as the same sequence vector Y (42), can be discarded.

[0857] Table 7 below is an example of 1165 consecutive pairs of vectors X and Y arranged in chronological order.

[0858] Table 7: Consecutive pairs of vectors X and Y arranged in chronological order 1165

[0859]

[0860] The example of consecutive pairs of vectors X and Y shown in Table 7 includes information indicating the toe position X1 and information indicating the corresponding output parameter Y2. The output parameter Y2 indicates the median particle size of the particles produced by the tumbling mill.

[0861] The correlation data generator 1160 can be configured to perform correlation based on the received vector X and Y pairs 1165. According to one example, the correlation data generator 1160 can be configured to perform regression analysis based on a large number of received vector X and Y pairs 1165.

[0862] Regression analysis can use one or more statistical procedures to estimate the relationship between a dependent variable (i.e., the value in the vector Y) and one or more independent variables (i.e., the value in the vector x).

[0863] Figure 36 The shell 20 of the ball mill 10 is at a rotational speed f ROT A cross-sectional view during the next operation. Therefore, Figure 36 Can be combined with the above Figure 1A , Figure 2 , Figure 14A , Figure 14B , Figure 23 and Figure 30 Compared to cross-sectional views. Figure 36The tumbling mill 10 operates as a ball mill, and therefore the feed material 30 includes a plurality of grinding balls 1168 and solid feed materials 110, 115. In some examples, the feed material 30 may also include liquid feed materials, such as water.

[0864] Figure 37 This is for a constant or approximately constant rotational speed U1=f ROT =Running at 18rpm Figure 36 The graph shows a large number of consecutive curves of vectors X1 and Y2 of the ball mill, with a value of 1165. Figure 37 In the diagram, the density of black dots, where each dot represents a pair of values ​​X1-Y1, is very high when X1 = 60 degrees. A high density of black dots at values ​​near X1 = 60 degrees indicates that the mill frequently operates at or near the operating point of X1.

[0865] It can be seen that X1=60 corresponds to a median particle size Y1 of approximately 260 micrometers. The density of black spots is lower at approximately X1=40 to 50 degrees, indicating that the mill typically operates less at the operating point where X1 is between 40 and 50 degrees.

[0866] Combination Figure 36 refer to Figure 1A The radius of the ball mill is R. MIC =1930 mm, and has 28 protrusions 310 ( Figure 36 (Not shown in the image). During operation of the ball mill 10, the grinding ball feed rate U4 can be set or selected so that the amount of grinding balls remains constant or approximately constant.

[0867] refer to Figure 34 The correlation data generator 1160 can be configured to be based on, for example, Figure 37 The received values ​​X1 and Y2 are used to perform regression analysis, also known as correlation analysis.

[0868] Regression analysis can, for example, employ linear regression. When applied to a single dependent variable Y2 and a single independent variable (such as X1 or X6), linear regression analysis will operate according to specific mathematical standards to identify the linear relationship that best fits the data, i.e., line 1180. For example, ordinary least squares computes a unique line 1180 that minimizes the sum of the squared differences between the true data and this line. Therefore, as mentioned above, Figure 37 Line 1180 in the figure is a graph of the results of linear regression based on the received values ​​X1-Y1 pairs.

[0869] Therefore, the correlation dataset 1170 generated by the correlator 150C1 may include a data table or a linear equation.

[0870] Figure 38It is a graph of the generated linear regression results. Therefore, the curve in the figure shows the line labeled as line 1180, which shows the relationship between X1 and Y1, at least when the ball mill operates at a constant or substantially constant rotational speed f ROT = 18 rpm as described above. Therefore, when linear regression analysis is applied to a single dependent variable Y2 and a single independent variable, the correlation data generator 1160 can transmit correlation data 1170 indicating the linear relationship 1180.

[0871] Reference Figure 34 , the correlation data set 1170 generated by the correlator 150C1 can be transmitted to the internal state reference value generator 150c2.

[0872] The internal state reference value generator 150c2 can be configured to use the received correlation data 1170 to convert the expected value Y REF into the corresponding internal state reference value X REF . Table 8 is an illustration of an example of a data conversion table for converting the expected value Y2 REF into the corresponding internal state reference value X1 REF . In fact, Table 8 is an example data set corresponding to the information in Table 7 above.

[0873] Table 8: The correlation data set 1170 in the form of a correlation table, used to convert the desired product characteristic Y2 REF into the internal state parameter reference value X1 REF

[0874]

[0875] The example correlation data table 1170 (the example of which is shown in Table 8) indicates the correlation between the internal state parameter value X1 and the output parameter Y2. The internal state parameter value indicates the toe position, and the output parameter indicates the median particle size of the particles produced by the roller mill.

[0876] More complex situations in multivariate monitoring systems

[0877] Figure 37 And Figure 38 serves as an illustration of the function of the correlation data generator 116 object in a relatively simple case where regression analysis is applied to a single dependent variable Y2 and a single independent variable X1. In fact, compared with non-ball mill roller mills, ball mills inherently exhibit less variation in toe position, especially when the ball mill also operates at a constant or substantially constant rotational speed U1, as described above.

[0878] However, another objective of the solutions and examples disclosed in this document is to describe methods and systems for improving the monitoring and / or control of the internal state X in the tumbler mill 10 during operation. When the tumbler mill 10 operates at a variable speed X5 = U1 and also exhibits changes in the toe position X1, the regression analysis described above applied to a single dependent variable Y2 and a single independent variable X1 may be insufficient. However, to address this issue, the correlation data generator 1160 can apply regression analysis to multiple data pairs 1165, including:

[0879] The received internal state vector X(t) of dimension m, and

[0880] The received output vector Y(t) of dimension n,

[0881] Where m and n are positive integers.

[0882] Therefore, when m state parameter values ​​X1, X2, X3, ..., Xm are correlated with n product measurement values ​​Y1, Y2, Y3, ..., Yn, the correlation data generator 1160 can be configured to generate a set of correlation data 1170 by performing the following correlation:

[0883] The received internal state vector X(t),

[0884] as well as

[0885] The received corresponding output vector Y(t),

[0886] in,

[0887] X(t) is m 1. A vector, where m is a positive integer, and

[0888] Y(t) is n 1. A vector, where n is a positive integer.

[0889] Therefore, in this context, the correlation data generator 1160 can be configured to perform regression analysis to identify more complex linear combinations (i.e., more complex than a straight line) that best fit the data according to specific mathematical criteria. For example, the correlation data generator 1160 can perform ordinary least squares applied to multiple received vectors X(t) in m dimensions and multiple received corresponding output vectors Y(t) in n dimensions to compute a unique hyperplane that minimizes the sum of squared differences between the received data and the hyperplane.

[0890] Therefore, when receiving an m-dimensional vector X(t) and multiple corresponding n-dimensional output vectors Y(t), the correlation data generator 1160 is configured to generate a multidimensional correlation dataset 1170. According to one example, the multidimensional correlation dataset 1170 can be transmitted as data 1170 indicating the aforementioned hyperplane. Alternatively, the multidimensional correlation dataset 1170 can be transmitted as data 1170 indicating the coefficient matrix C, as discussed above with respect to Equation 7.

[0891] According to one example, when generating the correlation dataset 1170, the correlation data generator 1160 can be configured to include Kalman filtering, also known as linear quadratic estimation (LQE).

[0892] This solution advantageously enables the identification and / or determination of a causal relationship between the internal state X of the pulverizing process and at least one output material measurement Y.

[0893] Furthermore, this solution advantageously enables the identification and / or determination of a causal relationship between the internal state X of the pulverizing process and the state Y of the discharged material. The discharged material state Y can also be referred to as the product material state Y.

[0894] This solution is general because it allows for the definition of the desired discharge material state Y. REF It also allows testing alternative internal states of the crushing process, also known as operating point X. OP In order to search for and identify the internal state X of the crushing process. BEP This crushing process leads to or produces the desired discharged material state Y. REF Or, it may result in or produce a discharge material state Y that is as close as possible to the desired state. REF The discharged material state Y. This internal state can be called the optimal operating point BEP. The parameter values ​​at BEP can be collectively referred to as the internal state BEP vector X. BEP .

[0895] Furthermore, the internal state X(r) of the detected instantaneous crushing process is correlated with the corresponding instantaneous discharged material state Y(r), generating correlation data indicating the correlation between the following:

[0896] The internal state X(r) of the instantaneous crushing process, and

[0897] The corresponding instantaneous discharged material state Y(r).

[0898] By repeatedly recording and correlating multiple distinct detected internal states X(r) of the instantaneous crushing process with the instantaneous discharged material state Y(r) caused by the corresponding internal state X(r), where r is a numerical variable indicating multiple different time points, a correlation dataset can be generated. This correlation dataset indicates the correlation between the following items:

[0899] The internal states X(r) of multiple instantaneous crushing processes, and

[0900] Multiple corresponding instantaneous discharge material states Y(r).

[0901] The ball mill operating characteristic curve, or BMOC curve, is a graph that shows the median particle size (Y2) of the product particles produced by the ball mill as the toe position value varies. Figure 37 and Figure 38 As shown.

[0902] The BMOC curve is created by plotting the relationship between the toe position value and the median particle size (Y2) of the product particles at different toe positions.

[0903] Roll mill operating point or X OP Or TOP is a specific point within the operating characteristics of the tumbling mill. It has been found that when the toe position value is around a specific tumbling mill operating point (X... OP When the toe position value of the mill (TOP) varies within a certain range, there is a linear relationship between the toe position value and the particle size distribution (Y) of the product. In the context of this document, the term Mill Operating Area (MOA) can be used to describe this range of toe position values.

[0904] The mill operating characteristic curve or MOC curve of a tumbling mill is a graph that shows the particle size distribution (Y) of the product particles produced by the tumbling mill when at least one of the state parameter values ​​(X1, X2, X3, X4, X5, X6) changes. Therefore, for example, when, for example, the rotational speed (f) of the casing... ROT While keeping the particle size distribution (Y) constant, an MOC curve is created by plotting the measured values ​​of the product particle size distribution (Y) relative to the toe position values.

[0905] A linear relationship has been found between the following items:

[0906] The median particle size (Y2) of the product particles produced by the ball mill, and

[0907] At least when the toe position value X1 varies within a certain range of toe position values, the toe position value...

[0908] Refer again Figure 34The internal state reference value generator 150c2 can be configured to use the received correlation data 1170 to generate the expected value Y. REF Convert to the corresponding internal state reference value X REF .

[0909] Use correlation data to operate the mill.

[0910] refer to Figure 34 The operator 230 in control room 220 is tasked with operating the tumbling mill 10. The operator can operate the mill 10 using a regulator 1190. The regulator 1190 is coupled to user interfaces 210, 210B, also known as a human-machine interface (HCI) 210B, such as... Figure 34 As shown.

[0911] Figure 34 The example control room 220 shown includes an internal state control system 1200, which includes an internal state reference value generator 150c2, user interfaces 210, 210B, and a regulator 755C or regulator 240C.

[0912] The internal status control system 1200 can be configured to perform the following steps:

[0913] (Step S3000:) Causes the user interface 210 to transmit a request to the operator to provide an indication of the desired discharge material status Y. REF The information input by the user. As mentioned above, it indicates the desired state of the discharged material Y. REF User input can indicate at least one desired output material measurement, such as Y1 and / or Y2. For example, user input can indicate the desired median particle size Y2 of the product. REF And / or the desired product particle size distribution Y3 REF Y4 REF Or the expected output material quantity Y1 per unit time REF .

[0914] The request S3000 can be generated by software included in regulator 755C, or software included in regulator 240C, or software included in internal state reference value generator 150c2.

[0915] The internal status control system 1200 can also be configured as:

[0916] (Step S3005:) For example, receiving the desired discharge material state Y via user interface 210. REF and / or the desired median particle size Y2 of the product REF And / or the data for the desired product particle size distribution Y2, Y3, Y4.

[0917] Furthermore, the internal state control system 1200 can be configured to perform a method including the following steps:

[0918] S3010: Generate toe position reference values ​​(X1) based on the following: REF ;FI REF ):

[0919] The data indicates the desired state of the discharged material Y. REF And / or the desired median particle size of the product (Y2) REF ) and / or the desired product particle size distribution Y2 REF Y3 REF Y4 REF ,as well as

[0920] The correlation dataset (1170); the correlation dataset (1170)

[0921] Indicate the causal relationship between the following items:

[0922] Specific toe position values ​​(X1(r), FI(r), T) D R T (r); X6, A TOE (r)), and

[0923] The corresponding median particle size (Y2) of a specific product.

[0924] At the aforementioned housing rotational speed (U1, f) ROT );

[0925] And / or indicate the causal relationship between the following:

[0926] Specific internal state X REF ,as well as

[0927] The corresponding specific discharge material state Y REF .

[0928] The corresponding specific discharge material state Y REF It can include specific product particle size distributions (Y2, Y3, Y4).

[0929] Step S3010 may include transmitting the received data from the user interface 210 to the internal state reference value generator 150c2 (see...) Figure 34 and / or Figure 35 and / or Figure 39 ).

[0930] As described above, the internal state reference value generator 150c2 is configured to compare the internal state reference value generator with the desired discharged material state Y. REFThe relevant data is converted into an indication of the corresponding desired internal state X. REF Data and / or indications of the corresponding expected toe position reference value X1 REF (r), FI REF (r) data.

[0931] Combination Figure 35 refer to Figure 34 The internal state control system 1200 can also be configured as follows:

[0932] S3020: Cause the user interface (210, 210S, 240, 250) to transmit the corresponding desired internal state X. REF Information and / or indication of the corresponding expected toe position reference value (X1) REF (r), FI REF (r)) data, and

[0933] S3020: Enables the user interface (210, 210S, 240, 250) to transmit indications, such as the actual toe position values ​​(X1(r), FI(r), T) received from the monitoring module 150A. D R T (r); X6, A TOE Information (r)

[0934] S3020: Receive the feed rate (U2, R) of the solid material via the user interface (210, 210S, 240, 250). S The first user input related to this;

[0935] S3020: Setpoint value for the feed rate of generated solid materials (U2) SP R SSP This affects the internal state (X) to control or influence the desired discharged material state Y. REF The median particle size of the product (Y2); among which,

[0936] The feed rate setpoint value of the generated solid material (U2) SP R SSP Based on the received first user input.

[0937] According to one example, the solid material feed rate setpoint value U2 is generated based on the received first user input. SP The material in the rotating shell (20) is tumbled under the affected internal state (X) to produce product particles with a median particle size (Y2) corresponding to the affected internal state (X) of the pulverizing process.

[0938] A system for monitoring and providing operators with improved information about the crushing process.

[0939] Figure 39 This is a block diagram of a system 1130 for monitoring the internal status X of mill 10 and for providing improved information content to the operator 230 of mill 10.

[0940] System 1130 includes a tumbling mill 10, as described above. Figures 34 to 38 The subject of discussion. Figure 39 In the diagram, system 1130 is shown as a block diagram including a tumbling mill, which is shown as block 10 that receives multiple inputs U1, ... Uk and generates multiple outputs Y1, ... Yn. Therefore, in terms of signal processing and analysis, mill 10 receives input vector U and generates output vector Y in a manner discussed elsewhere in this document. Figure 39 System 1130 may include multiple components, and may be as described above. Figure 1A and / or Figure 1B The configuration described and / or as described in any other example described in this disclosure, for example, regarding Figure 1- Figure 38 .

[0941] like Figure 39 As shown, system 1130 includes a monitoring module 150A and / or a correlation module 150C. As described above, the correlation module 150C is operable to generate a correlation dataset 1170 during operation of the mill 10, and / or the correlation module 150C is operable to correlate the desired discharge material state Y. REF The relevant data is converted into an indication of the corresponding desired internal state X. REF The data transformation steps are based on a correlation dataset 1170 related to the operating mill 10.

[0942] Figure 39 The system 1130 shown includes an internal state control system 1200, which includes an internal state reference value generator 150c2, user interfaces 210, 210B, and a regulator 240C.

[0943] The internal status control system 1200 can be configured to perform the following steps:

[0944] (Step S3000:) The user interface 210 transmits a request to the operator to provide an indication of the desired discharge material status Y. REF The information input by the user. As mentioned above, it indicates the desired state of the discharged material Y. REF User input can indicate at least one desired output material measurement, such as Y1 and / or Y2. For example, user input can indicate the desired median particle size Y2 of the product. REFAnd / or the desired product particle size distribution Y3 REF Y4 REF Or the expected output material quantity Y1 per unit time REF .

[0945] The request S3000 can be generated by software included in the regulator 240C.

[0946] The internal status control system 1200 can also be configured as:

[0947] (Step S3005:) For example, receiving the desired discharge material state Y via user interface 210. REF and / or the desired median particle size Y2 of the product REF And / or the data for the desired product particle size distribution Y2, Y3, Y4.

[0948] Furthermore, the internal state control system 1200 can be configured to perform a method including the following steps:

[0949] S3010: Generate the corresponding desired internal state X REF (Also known as the internal state reference vector X) REF ), Expected internal state X REF This may include toe position reference values ​​(X1) REF ;FI REF Internal state reference vector X REF It can be based on:

[0950] Indicates the desired state of the discharged material Y REF And / or the desired median particle size of the product (Y2) REF ) and / or the desired product particle size distribution Y2 REF Y3 REF Y4 REF The data mentioned above, and

[0951] Correlation dataset (1170); the correlation dataset (1170) indicates causal relationships between the following items:

[0952] Specific internal state X REF ,as well as

[0953] The corresponding specific discharge material state Y REF .

[0954] The corresponding specific discharge material state Y REF This may include the particle size distribution of a specific product (Y2, Y3, Y4) and / or the discharge rate of a specific product Y1. REF .

[0955] Step S3010 may include receiving the data (i.e., indicating the desired state of the discharged material Y) REF ) is transmitted from user interface 210 to correlation module 150C (see Figure 39 ).

[0956] The relevant module 150C may include an internal state reference value generator 150c2, which is configured to correlate the desired discharged material state Y. REF The relevant data is converted into an indication of the corresponding desired internal state X. REF Data and / or indications of the corresponding expected toe position reference value X1 REF (r), FI REF The data for (r) are as described above.

[0957] Combination Figure 35 refer to Figure 39 The internal state control system 1200 can also be configured as follows:

[0958] S3020: Cause the user interface (210, 210S, 240, 250) to transmit the corresponding desired internal state X. REF Information and / or indication of the corresponding expected toe position reference value (X1) REF (r), FI REF (r)) data, and

[0959] S3020: Enables the user interface (210, 210S, 240, 250) to transmit, for example, the actual toe position value (X1(r), FI(r), T) received from the monitoring module 150A. D R T (r); X6, A TOE Information (r)

[0960] S3020: Receive the feed rate (U2, R) of the solid material via the user interface (210, 210S, 240, 250). S The first user input related to this;

[0961] S3020: Setpoint value for the feed rate of generated solid materials (U2) SP R SSP This affects the internal state (X) to control or influence the desired discharged material state Y. REF The median particle size of the product (Y2); among which,

[0962] The feed rate setpoint value of the generated solid material (U2) SP R SSP Based on the received first user input.

[0963] According to one example, the solid material feed rate setpoint value U2 is generated based on the received first user input. SP The material in the rotating housing (20) is tumbled under the affected internal state (X) to produce product particles with a median particle size (Y2) corresponding to the affected internal state (X) of the pulverizing process.

[0964] A system for monitoring mill products and providing improved process control.

[0965] Figure 40 This is a block diagram of a system 1130B for monitoring the internal state X of a mill 10 and for improving the control of the grinding process occurring within the mill 10. System 1130B may include... Figure 39 Some or all of the features discussed. Therefore, system 1130B may include Figure 39 Some or all of the features of system 1130.

[0966] like Figure 39 As shown, system 1130B includes related module 150C, and system 1130B may also include monitoring module 150A.

[0967] As described above, the correlation module 150C is operable to generate a correlation dataset 1170 during operation of the mill 10, and / or the correlation module 150C is operable to correlate the desired discharge material state Y. REF The relevant data is converted into an indication of the corresponding desired internal state X. REF The data transformation steps are based on a correlation dataset 1170 related to the operating mill 10.

[0968] Figure 39 The system 1130 shown includes an internal state control system 1200, which includes an internal state reference value generator 150c2, user interfaces 210, 210B, and a regulator 240C.

[0969] System 1130B can be configured to perform the following steps:

[0970] (Step S3000:) The user interface 210 transmits a request to the operator to provide an indication of the desired discharge material status Y. REF The information entered by the user. Indicates the desired state of the discharged material Y. REF User input can indicate at least one desired output material measurement, such as Y1 and / or Y2, as described above. For example, user input can indicate the desired median particle size Y2 of the product. REF And / or the desired product particle size distribution Y3 REF Y4REF Or the expected output material quantity Y1 per unit time REF .

[0971] The request S3000 can be generated by software included in the regulator 150B, or by software included in the relevant module 150C, or by the internal state control system 1200.

[0972] System 1130B can also be configured as:

[0973] (Step S3005:) For example, receiving the desired discharge material state Y via user interface 210. REF and / or the desired median particle size Y2 of the product REF And / or the data for the desired product particle size distribution Y2, Y3, Y4.

[0974] Furthermore, system 1130B can be configured to perform a method including the following steps:

[0975] S3010: Generate the corresponding desired internal state X REF Also known as the internal state reference vector X REF ), which may include toe position reference values ​​(X1) REF ;FI REF Internal state reference vector X REF Based on

[0976] Indicates the desired state of the discharged material Y REF And / or the desired median particle size of the product (Y2) REF ) and / or the desired product particle size distribution Y2 REF Y3 REF Y4 REF The data mentioned above, and

[0977] Correlation dataset (1170); the correlation dataset (1170) indicates causal relationships between the following items:

[0978] Specific internal state X REF ,as well as

[0979] The corresponding specific discharge material state Y REF .

[0980] The corresponding specific discharge material state Y REF This may include the particle size distribution of a specific product (Y2, Y3, Y4), and / or the discharge rate of a specific product Y1. REF .

[0981] Step S3005 may include receiving the data (i.e., indicating the desired state of the discharged material Y) REF ) is transmitted from user interface 210 to correlation module 150C (see Figure 40 ).

[0982] The relevant module 150C may include an internal state reference value generator 150c2, which is configured to compare the desired discharged material state Y with the internal state reference value generator 150c2. REF The relevant data is converted into an indication of the corresponding desired internal state X. REF Data and / or indications of the corresponding expected toe position reference value X1 REF (r), FI REF The data for (r) are as described above.

[0983] Furthermore, system 1130B can be configured to perform a method including the following steps:

[0984] The discharged material state (Y) is controlled by regulators 755C and 755 based on the following:

[0985] The at least one state parameter reference value (X1) REF ;FI REF ), including the internal state reference vector X REF middle,

[0986] At least one state parameter value (X1, X2, X3, X4, X5, X6, X7) or internal state vector (X), including said at least one state parameter value indicating the current internal state (X) of the crushing process, and

[0987] At least one state parameter error value (X1) ERR X2 ERR X3 ERR X4 ERR X5 ERR X6 ERR X7 ERR (or an internal state error vector X including at least one state parameter error value) ERR ,

[0988] in,

[0989] The error value of at least one state parameter (X1) ERR X2 ERR X3 ERR X4 ERR X5 ERR X6 ERR X7 ERR )depending on:

[0990] The at least one state parameter reference value (X1)REF ;FI REF ),as well as

[0991] The at least one state parameter value (X1, X2, X3, X4, X5, X6, X7).

[0992] Furthermore, system 1130B can be configured to perform a method including the following steps:

[0993] The discharged material state (Y) is controlled by regulators 755C and 755 based on the following:

[0994] The internal state reference vector X indicates the current internal state (X) of the crushing process. REF ,as well as

[0995] The internal state vector (X) indicates the current internal state (X) of the crushing process, and

[0996] An internal state error vector X including at least one state parameter error value ERR ,

[0997] in,

[0998] The internal state error vector X ERR depending on:

[0999] The internal state reference vector X ERR ,as well as

[1000] The internal state vector (X).

[1001] Furthermore, system 1130B can be configured to perform a method including the following steps:

[1002] The solid material feed rate (U2, R) is received via the user interface (210, 210S, 240, 250). S The first user input related to this; and

[1003] Generate the setpoint value of the feed rate of the solid material (U2) SP R SSP );in,

[1004] The generated indicator solid material feed rate setpoint value (U2) SP R SSP The data is based on the first user input received.

[1005] Various examples are shown below, starting with Example 1.

[1006] Example 1 relates to a system 5 for grinding materials, the system comprising:

[1007] A tumbling mill, characterized by its high rotational speed (f) ROT A housing that rotates about an axis (60) for grinding a material by tumbling a material in the housing; wherein the housing has an inner housing surface including at least one protrusion configured to engage material within the housing;

[1008] Vibration sensor, configured to respond to mechanical vibrations (V) originating from the rotation of the housing. IMP To generate analog measurement signals (S) EA );

[1009] A position sensor is configured to generate a position signal indicating the rotational position of the rotating housing;

[1010] Signal recorder, suitable for recording:

[1011] - Digital measurement data signal (S MD S ENV S MD The time series of measured sample values ​​(Se(i), S(j)) and

[1012] - Time series of location signal values ​​(P(i)), and

[1013] -Time information (i, dt; j)

[1014] This associates a single measured data value (S(j)) with data indicating the time of occurrence of the single measured data value (S(j)), and also associates a single location signal value (P(i)) with data indicating the time of occurrence of the single location signal value (P(i)).

[1015] A signal processor suitable for detecting amplitude peaks in a time series of recorded measurement sample values ​​(Se(i), S(j));

[1016] The signal processor is adapted to generate data indicating the duration between the occurrence of a position signal value and the occurrence of an amplitude peak.

[1017] 2. Based on the system in Example 1, where,

[1018] The signal processor is configured to generate a housing charge dataset that indicates the internal charge status within the housing; the housing charge dataset includes amplitude peaks and durations.

[1019] 3. The system according to any of the foregoing examples, wherein,

[1020] The shell loading dataset indicates the rotational speed of the rotary mill shell.

[1021] 4. The system according to any of the foregoing examples, wherein

[1022] The rotating housing is configured to hold more than 500 kg of material during operation of the tumbling mill.

[1023] Example 5 relates to an electronic tumbling mill monitoring system for generating and displaying information related to the internal state of the grinding process in a tumbling mill (10), the tumbling mill having a rotational speed (f ROT A housing that rotates about an axis (60) for grinding a material (30) by means of a material in the rotating housing, the monitoring system of the tumbling mill includes:

[1024] State parameter extractor (450) is used to generate

[1025] First internal state index data structure (550, S) indicating the internal state of the grinding process P1 T D1 The first internal state indicator data structure (550, S) P1 T D1 This includes the first impact force indication value (S). P1 ) and the first time indication value (T) D1 );

[1026] First impact force indication value (S) P1 This indicates the impact force (F) generated when the protrusions on the inner surface of the rotating housing interact with the toe of the charge material. IMP ),as well as

[1027] First time indication value (T) D1 ) Indicator of impact force (F) IMP The duration (T) between the appearance of the rotating reference position of the rotating housing and the appearance of the rotating reference position. D1 ).

[1028] 6. According to the rolling mill monitoring system of Example 5, wherein the state parameter extractor (450) further generates

[1029] Second Internal State Indicator Data Structure (S) P2 T D2 ), which indicates the internal state of the grinding process, the second internal state index data structure (550, S P1 T D1 This includes the second impact force indication value (S). P2 ) and second time indication value (T) D2 ),

[1030] Second impact force indication value (S) P2 This indicates the impact force (F) generated when the protrusions on the inner surface of the rotating housing interact with the toe of the charge material. IMP ),as well as

[1031] Second time indication value (T) D2 ), its indicated impact force (F IMP The duration (T) between the appearance of the rotating reference position of the rotating housing and the appearance of the rotating reference position. D1 );in,

[1032] First Internal State Indicator Data Structure (S) P1 T D1 This indicates the internal state of the grinding process at the first time point, and

[1033] Second Internal State Indicator Data Structure (S) P2 T D2 This indicates the internal state of the grinding process at the second time point.

[1034] 7. According to the rolling mill monitoring system of Example 6, wherein the first internal status index data structure (S P1 T D1 Combined with internal state indicator data structure (S) P2 T D2 (This indicates the time progression of the internal state of the grinding process.)

[1035] 8. A monitoring system for a tumbling mill according to any of the foregoing examples, wherein,

[1036] The state parameter extractor (450) includes:

[1037] The housing speed detector (500) is configured to generate an indication of the mill housing rotational speed (f) based on a digital position signal (P(i)). ROT The value of (j) indicates the rotational speed of...

Claims

1. A method of operating a grinding process in a ball mill, the ball mill comprising a rotatable housing having an inner housing surface having a first number of protrusions configured to engage a material feed for grinding received solid material feed particles by tumbling the material in the rotatable housing to generate product particles at the mill output, such that when the protrusions engage with the toes of the material, vibrations having a first repetition frequency dependent on the rotational speed of the housing are induced; The method includes: -During operation of the ball mill, the rotatable housing is rotated at a housing rotation speed; - Provides a solid material feed rate setpoint value to set the solid material feed rate, which is the amount of feed particles fed to the input end of the ball mill per unit time, thereby affecting the internal state of the pulverizing process; -Analyze at least a portion of the product particles; - Generate at least one product measurement value based on product particle size analysis, the at least one product measurement value indicating the median particle size of the product; - Receive vibration signals indicating the vibration; - Receive a position signal indicating the rotational position of the rotatable housing; - Generate at least one state parameter value indicating the internal state based on the vibration signal and the position signal, the at least one state parameter value including: A toe position value indicating the position of the toe; - Receive data indicating the desired median particle size of the product particles; - Generate reference values ​​for state parameters based on the following: Data indicating the desired median particle size of the product particles, and A correlation dataset that indicates causal relationships between the following: The at least one state parameter value, and The at least one product measurement value; At least one state parameter reference value includes a toe position reference value; and - The at least one product measurement value is controlled via the regulator based on the following: The at least one state parameter reference value The at least one state parameter value, and At least one state parameter error value, wherein, The error value of at least one state parameter depends on the following: The at least one state parameter reference value, and The at least one state parameter value.

2. The method according to claim 1, wherein, The material in the rotatable housing is tumbled in the affected internal state of the crushing process to produce product particles with a corresponding median particle size.

3. The method according to claim 1, wherein, The method further includes the following steps: - Receive second user input related to the desired median particle size of the product particles via a user interface; and - Generate data indicating the desired median particle size of the product particles; wherein... The generated data indicating the desired median granularity of the product particles is based on the received second user input.

4. The method according to claim 1, wherein, The position signal has a second repetition frequency that depends on the rotational speed; and The vibration signal includes a time series of vibration sample values; the method further includes: In the time series of the vibration sample values, event features with an event feature occurrence frequency are detected, the event feature occurrence frequency being equal to the first repetition frequency; A periodic event signal is generated based on the frequency of occurrence of the event characteristics, and the periodic event signal exhibits the first number of cycles per revolution of the shell during the operation of the ball mill; A periodic reference signal is generated based on the position signal, the periodic reference signal exhibiting the first number of periods per revolution of the housing during the operation of the ball mill; Generate data indicating the first-time relationships between the following items: The periodic event signal, and The periodic reference signal, the time relationship, indicates the internal state of the ball mill.

5. The method according to claim 1, further comprising: In the time series of position signal values, detect the first occurrence of a first reference position signal value indicating a predetermined rotational position of the rotatable housing; A first reference signal is provided based on the position signal, such that the reference signal is provided for a specific number of revolutions of the housing; as well as Detect signal event characteristics in the vibration signal when the protrusion engages with the toe portion of the material; Measure the first duration from the provision of the first reference signal to the provision of a subsequent reference signal; as well as The second duration between the provision of the reference signal and the occurrence of the subsequent signal event feature is measured, or the second duration between the occurrence of the signal event feature and the provision of the subsequent reference signal is measured. as well as A time relationship value is generated based on the second duration and the first duration, the time relationship value indicating the internal state of the ball mill.

6. The method according to claim 4, wherein, The toe position value is the first time relationship.

7. The method according to claim 5, wherein, The toe position value is the time relationship value.

8. The method according to claim 1, wherein, Generating the at least one state parameter value indicating the internal state further includes: Another state parameter value indicating the rotational speed of the housing is generated based on the vibration signal and the position signal.

9. The method according to claim 1, further comprising: Provide a ball feed rate setpoint value for setting the ball feed rate, which is the amount of grinding balls fed per unit time to the input end of the ball mill to enhance the grinding process, thereby affecting the internal state of the grinding process.

10. The method of claim 9, further comprising: A fourth user input related to the ball feed rate is received via a user interface; The setpoint value for the ball feed rate is generated, thereby affecting the internal state to control or influence the median particle size of the product; wherein, The generated ball feed rate setpoint value is based on the received fourth user input.

11. The method of claim 9, further comprising: The vibration signal is detected to include a signal event feature that occurs when the protrusion engages with the toe of the material, the event feature indicating the impact force generated when the protrusion on the inner shell surface of the rotatable housing interacts with the toe of the material.

12. The method of claim 11, further comprising: Another state parameter value is generated based on the impact force; When generated at a known shell rotation speed and a known toe position value, the additional state parameter value indicates the mass of the material charge.

13. The method according to claim 11 or 12, further comprising: Another state parameter value is generated based on the impact force; When generated at a known shell rotation speed, a known toe position value, and a known charge volume, the additional state parameter value indicates the average mass density of the charge.

14. The method of claim 13, further comprising: The ball feed rate setpoint value is generated based on the average mass density of the material charge and based on the following: First density information indicating the average density of the feed particles, and Second density information indicating the average density of the grinding balls.

15. The method of claim 11, further comprising: The ball feed rate setpoint value is generated based on a combination of the following: The impact force, and The toe position value, and The rotational speed of the housing.

16. The method according to claim 1, wherein, The feed particles have a feed particle size distribution, which includes the median particle size value of the feed particles, wherein... The median particle size of the feed particles is greater than the median particle size of the product particles.

17. The method according to claim 1, wherein, At least 80% by mass of the feed particles have a feed particle size of more than 20 mm.

18. The method according to claim 1, wherein, The at least one product measurement value includes: A value indicating the proportion or percentage share of product particles having a particle size within the range between the lower limit and the upper limit of product particle size.

19. The method according to claim 1, wherein, At least 80% by mass of the product particles have a particle size in the range of 30 micrometers to 20 millimeters.

20. The method according to claim 19, wherein, At least 80% by mass of the product particles have a particle size in the range of 150 micrometers to 300 micrometers.

21. The method according to claim 1, wherein, At least 80% by mass of the product particles have a median particle size in the range of 200 to 220 micrometers.

22. The method according to claim 1, wherein, The feed particles have a feed particle size distribution; wherein... At least 80% by mass of the feed particles have a particle size of more than 20 mm.

23. The method according to claim 1, wherein, The shell rotation speed during the operation of the ball mill is a predetermined shell rotation speed.

24. The method according to claim 1, wherein, At least within a first range of the toe position values ​​and at the housing rotation speed, the correlation dataset indicates a linear relationship between the following: The toe position value, and The median particle size of the product particles, and wherein, The first range of the toe position values ​​provides the mill operating area.

25. The method according to claim 1, wherein: The ball mill is located at the mill position, and At least a portion of the method is performed at a monitoring location geographically separated from the mill location by a geographical distance, wherein the method further includes the following steps: At least some signals are transmitted between the mill location and the monitoring location.

26. The method of claim 25, wherein, The geographical distance exceeds one kilometer; and / or wherein, The mill is located in the first country constituting the first jurisdiction, and The monitoring location is in a second country constituting a second jurisdiction, such that at least a portion of the method for generating information related to the internal state is performed in the first country, and at least a portion of the method is performed in the second country.

27. The method according to claim 25 or 26, wherein, At least part of the signal transmission is performed by the communication network.

28. The method according to claim 27, wherein, The communication network includes the Internet.

29. The method according to claim 1, wherein, The at least one product measurement value includes: Values ​​indicating the particle size distribution of the product.

30. The method according to claim 1, wherein, At the shell rotational speed and the solid material feed rate and / or liquid material feed rate and / or ball feed rate, the correlation dataset indicates the correlation between the following: The toe position value, and The median particle size of the product particles.

31. The method of claim 30, further comprising: - Generate and / or update the correlation dataset based on the following: The toe position value. The measured median particle size of the product particles, and The rotational speed of the housing.

32. The method according to claim 30, wherein, The correlation dataset is generated and / or updated based on the following: The toe position value. The median particle size of the product particles was measured. The rotational speed of the housing, and The feed rate of the solid material and / or the feed rate of the liquid material and / or the feed rate of the ball.

33. The method according to claim 31 or 32, wherein, Generate and / or update the correlation dataset based on a set of values ​​indicating that the ball mill has been operating for at least 2 minutes.

34. The method according to claim 1, further comprising: The rotational speed setpoint is controlled based on the toe position reference value, and wherein, The rotational speed of the housing depends on the rotational speed setpoint.

35. The method according to any claim 1, further comprising: The liquid feed rate setpoint is controlled based on the toe position reference value, and wherein, The liquid feed rate depends on the liquid feed rate setpoint, which is the amount of liquid fed to the input end of the ball mill per unit time.

36. The method according to claim 1, further comprising: This makes the user interface more user-friendly and prompts the operator to: When the toe position reference value is higher than the toe position value Increase the setpoint value of the solid material feed rate, and / or This makes the user interface more user-friendly and prompts the operator to: When the toe position reference value is lower than the toe position value Reduce the setpoint value of the feed rate of the solid material.

37. The method of claim 16, wherein, The median particle size of the feed particles is at least ten times larger than the median particle size of the product particles.

38. A computer program product comprising a non-transitory computer-readable storage medium having a computer program thereon including program instructions, the computer program being loadable into a processor and configured to cause the processor to perform the method according to any one of claims 1 to 37.

39. An apparatus for operating a pulverizing process in a ball mill, comprising a data processor and a computer-readable storage medium having a computer program thereon, the computer program including program instructions for causing the data processor to perform the method according to any one of claims 1 to 37.

40. A system for operating a grinding process in a ball mill, comprising: - A tumbling mill for performing a pulverizing process, the tumbling mill being a ball mill having a housing capable of rotating about an axis at a certain speed for grinding a material charge by tumbling the material together with a plurality of grinding balls in the housing to produce product particles, the housing having an internal housing surface including a first number of protrusions configured to engage the material and / or grinding balls when the housing rotates about the axis, thereby causing vibrations having a first repetition frequency dependent on the rotational speed; The ball mill includes: The first feed inlet is used to receive solid feed material for grinding at a solid feed rate, which is the amount of solid feed particles fed to the input end of the tumbling mill per unit time, thereby affecting the internal state of the grinding process. The solid feed rate is controlled or set by a solid feed rate setpoint value, and the solid feed particles have a feed particle size distribution. A ball feed inlet is used to receive the grinding balls at a ball feed rate to enhance the grinding process. The ball feed rate is the amount of grinding balls fed into the ball feed inlet of the ball mill per unit time, thereby affecting the internal state of the pulverizing process. The ball feed rate is controlled or set by a ball feed rate setpoint value. The mill output end is used to convey the product particles, which have a particle size distribution that is different from the particle size distribution of the feed particles. - A vibration sensor for generating a signal indicating the vibration; - A position sensor for generating a signal indicating the rotational position of the housing; and - The monitoring module is configured to receive: Data indicating vibration signals, and Data indicating position signals; The monitoring module includes: The state parameter extractor is configured to generate: At least one state parameter value, based on the vibration signal and the position signal, indicates the internal state of the crushing process. The at least one state parameter value includes a toe position value; and - A product analyzer is configured to analyze at least a portion of the product particles, the analyzer being configured to generate at least one product measurement based on the product particle analysis, the at least one product measurement indicating the particle size distribution of the product particles; The system also includes: - Reference value generator, with: The input is configured to receive data indicating the desired particle size distribution of the product. The reference value generator is configured to generate at least one state parameter reference value based on the following: Data indicating the desired product particle size distribution; and Correlation data indicating causal relationships between the following items: The at least one state parameter value, and The at least one product measurement value; The at least one state parameter reference value includes a toe position reference value; and - A regulator for controlling the particle size distribution of the product based on the following: The at least one state parameter reference value The at least one state parameter value, and At least one state parameter error value, in, The error value of at least one state parameter depends on the following: The at least one state parameter reference value, and The at least one state parameter value.

41. The system according to claim 40, wherein, The error value of at least one state parameter depends on the difference between the following: The at least one state parameter reference value, and The at least one state parameter value; in, The at least one state parameter reference value includes the toe position reference value, and The at least one state parameter value includes the toe position value.

42. The system according to claim 40 or 41, wherein, The setpoint value vector includes the setpoint value of the solid material feed rate and the setpoint value of the ball feed rate. The reference value vector includes at least one state parameter reference value. The internal state vector includes the values ​​of the internal states, and The output value vector includes at least one product measurement value.

43. The system according to claim 42, wherein, The error value vector includes the error values.

44. The system according to claim 40, wherein, The regulator is configured to generate a setpoint value for the feed rate of the solid material in order to control the particle size distribution of the product.

45. The system according to claim 43, wherein, The regulator is configured to generate the setpoint value vector in order to control the output value vector; The regulator generates the setpoint value vector based on the following: The reference value vector, The internal state vector, and The error value vector.

46. ​​The system according to claim 40, wherein, The regulator is configured to control the liquid feed rate setpoint based on the toe position reference value, and wherein, The liquid feed rate depends on the liquid feed rate setpoint, which is the amount of liquid fed to the input end of the ball mill per unit time.

47. The system according to claim 46, wherein, The toe position value depends on the following: The rotational speed, and / or The solid material feed rate, and / or The liquid feed rate, and / or The ball feed rate.

48. The system according to claim 40, wherein, The toe position value is an absolute toe position value; and The toe position reference value is an absolute toe position reference value.

49. The system of claim 40, further comprising: Correlators are used to perform correlations on the following: The at least one product measurement value, and The at least one state parameter value; wherein... The correlator is set to generate: Correlation data indicating causal relationships between the following items: The at least one state parameter value, and The at least one product measurement value, and / or wherein, The correlator is set to generate: Correlation data indicating causal relationships between the following items: The internal state of the pulverizing process, and The particle size distribution of the product.

50. The system of claim 40, further comprising: The user interface is configured to receive data from the mill operator indicating the desired product particle size distribution, and wherein... The toe position value is based on received data indicating the desired product particle size distribution.

51. The system according to claim 50, wherein, The user interface is configured to display the values ​​of the at least one status parameter, and The at least one state parameter reference value.

52. The system according to claim 40, wherein, The regulator is configured to minimize the difference between the at least one state parameter reference value and the corresponding at least one state parameter value.

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