Instrument reliability detection method, system, equipment and medium

Abstract

The invention provides an instrument reliability detection method, system and device and a medium, and relates to the technical field of instrument detection.The method comprises the steps that the i-th detection strategy of the i-th detection instrument is obtained, and the i-th detection strategy is determined according to at least one of the following data: the instrument value of the i-th detection instrument and the operation parameters of linkage equipment, the linkage equipment is equipment influencing the instrument value of the ith detection instrument in the ore grinding production line; obtaining an instrument data set of the ith detection instrument, wherein the instrument data set comprises a plurality of instrument values collected by the ith detection instrument within a preset time period; according to the instrument data set of the i-th detection instrument and the i-th detection strategy, determining a reliability evaluation factor of the i-th detection instrument, the reliability evaluation factor comprising at least one of the following: a communication state, a logic state and a numerical state; and determining the reliability state of the i-th detection instrument according to the reliability evaluation factor. According to the invention, the detection efficiency of the detection instrument is improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of instrument detection, in particular to an instrument reliability detection method, system, device and medium. BACKGROUND

[0002] The grinding process of a ball mill is complex and changeable. The detection instruments in the grinding process are directly in contact with solid materials or ore pulp, which affects the stability and reliability of the detection instruments. In the prior art, experienced operators need to regularly observe instrument data and comprehensively analyze the historical distribution of instrument data to determine whether the current instrument data is reliable in combination with the current working condition. This method is low in efficiency and difficult to promote. SUMMARY

[0003] Therefore, the present application aims to overcome the deficiencies in the prior art and provide an instrument reliability detection method, system, device and medium. The present application provides the following technical solutions: In a first aspect, the present application provides an instrument reliability detection method applied to a grinding production line, wherein the grinding production line comprises N detection instruments, and N is greater than or equal to 1. The method comprises the following steps: obtaining an i-th detection strategy of an i-th detection instrument, wherein 1≤i≤N, and the i-th detection strategy is determined according to at least one of the following data: an instrument value of the i-th detection instrument and an operating parameter of a linkage device, wherein the linkage device is a device in the grinding production line that affects the instrument value of the i-th detection instrument; obtaining an instrument data set of the i-th detection instrument, wherein the instrument data set comprises a plurality of instrument values collected by the i-th detection instrument within a preset time period; determining a reliability evaluation factor of the i-th detection instrument according to the instrument data set and the i-th detection strategy of the i-th detection instrument, wherein the reliability evaluation factor comprises at least one of the following: a communication state, a logic state and a value state; determining a reliability state of the i-th detection instrument according to the reliability evaluation factor, wherein the reliability state comprises reliable or unreliable.

[0004] In an embodiment, the i-th detection strategy is determined according to the instrument value of the i-th detection instrument. The communication state of the i-th detection instrument is determined according to the instrument data set and the i-th detection strategy of the i-th detection instrument, and comprises the following steps: determining whether each of the instrument values in the instrument data set belongs to an i-th preset range; if not, determining that the communication state of the i-th detection instrument is an abnormal state; If yes, it is judged whether there is a first sub-time period satisfying the following condition: whether a plurality of instrument values collected in the first sub-time period are same, wherein the first sub-time period belongs to the preset time period, and the first sub-time period is greater than a first preset time threshold; If yes, it is determined that the communication state of the ith detection instrument is: abnormal state. If no, it is determined that the communication state of the ith detection instrument is: normal state.

[0005] In an embodiment, the ith detection strategy is determined according to the operating parameter of the linkage device, and the value state of the ith detection instrument is obtained according to the instrument data set of the ith detection instrument and the ith detection strategy, comprising: The operating parameter set of the linkage device of the ith detection instrument is obtained, and the operating parameter set comprises: a plurality of operating parameter values of the linkage device in a preset time period; The operating parameter curve of the linkage device is determined according to each operating parameter in the operating parameter set, and the instrument curve is determined according to each instrument value in the instrument data set; If the operating parameter curve shows an increasing trend and the instrument curve shows a decreasing trend, or the operating parameter curve shows a decreasing trend and the instrument curve shows an increasing trend in a second sub-time period, it is determined that the logic state of the ith detection instrument is: abnormal state, wherein the second sub-time period belongs to the preset time period, and the second sub-time period is greater than a second preset time threshold.

[0006] In an embodiment, the ith detection strategy is determined according to the instrument value of the ith detection instrument and the operating parameter of the linkage device; The grinding production line comprises: a cyclone and a ball mill; the detection instrument comprises: an overflow flow meter and an overflow concentration meter, the overflow flow meter is used for detecting the overflow flow of the cyclone, and the overflow concentration meter is used for detecting the overflow concentration of the cyclone; the operating parameter of the linkage device comprises: the feed amount of the ball mill; The value state of the ith detection instrument is obtained according to the instrument data set of the ith detection instrument and the ith detection strategy, comprising: The dry ore density is obtained, and the overflow density is determined according to the dry ore density and the overflow concentration; The overflow quality is determined according to the overflow density and the overflow flow; The overflow solid amount is determined according to the overflow quality and the overflow concentration; Obtaining the feed quantity of the ball mill, and determining that the value state of the overflow flow meter is an abnormal state if the absolute value of the difference between the overflow solid quantity and the feed quantity is greater than a first preset difference value.

[0007] In an embodiment, the i-th detection strategy is determined according to the meter value of the i-th detection instrument; the detection instrument further comprises a feed flow meter and a feed concentration meter, the feed flow meter is used to detect the feed flow of the cyclone, and the feed concentration meter is used to detect the feed concentration of the cyclone. The value state of the i-th detection instrument is obtained according to the meter data set of the i-th detection instrument and the i-th detection strategy, which comprises: The feed density is determined according to the dry ore density and the feed concentration; The feed mass is determined according to the feed density and the feed flow; The desilting mass is determined according to the feed mass and the overflow mass; The feed solid quantity is determined according to the feed mass and the feed concentration; The desilting solid quantity is determined according to the feed solid quantity and the overflow solid quantity; The actual ratio value is determined as the ratio of the desilting solid quantity to the overflow solid quantity; The desilting concentration is determined as the ratio of the desilting solid quantity to the desilting mass; If the absolute value of the difference between the actual ratio value and a preset theoretical ratio value is greater than a second preset difference value, or the absolute value of the difference between the desilting concentration and a preset theoretical desilting concentration is greater than a third preset difference value, it is determined that the value state of the feed flow meter is an abnormal state.

[0008] In an embodiment, the reliability evaluation factor comprises a communication state and a logic state; and the reliability state of the i-th detection instrument is determined according to the reliability evaluation factor, which comprises: If the communication state and the logic state are both normal states, it is determined that the reliability state of the i-th detection instrument is reliable. The reliability evaluation factor comprises a communication state, a logic state and a value state; and the reliability state of the i-th detection instrument is determined according to the reliability evaluation factor, which comprises: If the communication state, the logic state and the value state are all normal states, it is determined that the reliability state of the i-th detection instrument is reliable. The reliability evaluation factor comprises any one of the communication state, the logic state and the value state. If any one of the communication state, the logic state and the numerical state is an abnormal state, the reliability state of the ith detection instrument is determined as: unreliable.

[0009] In an embodiment, after determining that the numerical state of the feed flow meter is an abnormal state, the method further comprises: performing a correlation analysis on the feed flow, and if a correlation coefficient is greater than a preset coefficient, determining a feed flow prediction value according to an operating parameter of a linkage device of the feed flow meter and a feed flow prediction model; determining a deviation value according to the feed flow prediction value and the feed flow value; correcting the feed flow value according to the deviation value.

[0010] In a second aspect, the present application provides an instrument reliability detection system, the system comprising: a first acquisition module configured to acquire an ith detection strategy of an ith detection instrument, wherein 1≤i≤N, and the ith detection strategy is determined according to at least one of the following data: an instrument value of the ith detection instrument and an operating parameter of a linkage device, the linkage device being a device in a grinding production line that affects the instrument value of the ith detection instrument; a second acquisition module configured to acquire an instrument data set of the ith detection instrument, the instrument data set comprising a plurality of instrument values collected by the ith detection instrument within a preset time period; a first determination module configured to determine a reliability evaluation factor of the ith detection instrument according to the instrument data set and the ith detection strategy, the reliability evaluation factor comprising at least one of the following: a communication state, a logic state and a numerical state; a second determination module configured to determine a reliability state of the ith detection instrument according to the reliability evaluation factor, the reliability state comprising reliable or unreliable.

[0011] In a third aspect, the present application provides an electronic device comprising a memory and a processor, the memory storing a computer program, and the computer program being executed on the processor to perform the instrument reliability detection method of any one of the preceding embodiments. In a fourth aspect, the present application provides a computer readable storage medium storing a computer program, and the computer program being executed on a processor to implement the instrument reliability detection method of any one of the preceding embodiments.

[0012] The application provides a kind of instrument reliability detection method, system, equipment and medium, by obtaining the i detection strategy of the i detection instrument, wherein 1≤i≤N, the i detection strategy is determined according to at least one of the following data: instrument value of the i detection instrument and operating parameter of linkage equipment, the linkage equipment is the equipment in the grinding production line that affects the instrument value of the i detection instrument;Obtain the instrument data set of the i detection instrument, the instrument data set includes: multiple instrument values collected by the i detection instrument in a predetermined time period;According to the instrument data set and the i detection strategy of the i detection instrument, determine the reliability evaluation factor of the i detection instrument, the reliability evaluation factor includes at least one of the following: communication state, logic state and numerical value state;According to the reliability evaluation factor, determine the reliability state of the i detection instrument, the reliability state includes reliable or unreliable, the reliability of detection instrument is evaluated from three dimensions of communication state, logic state and numerical value state, realizes the automatic detection of the reliability of detection instrument, effectively improves the reliability detection efficiency of detection instrument.

[0013] In order to make the above-mentioned purposes, features and advantages of the present application more obvious and easy to understand, the following preferred embodiments are described in detail below, and the accompanying drawings are described as follows. BRIEF DESCRIPTION OF DRAWINGS

[0014] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the following will briefly introduce the drawings needed to be used in the embodiments. It should be understood that the following drawings only show some embodiments of the present application, and therefore should not be regarded as a limitation on the scope. For those skilled in the art, other related drawings can also be obtained without creative labor.

[0015] Figure 1 A flowchart of the instrument reliability detection method provided by the embodiments of the present application is shown; Figure 2 A structural schematic diagram of the grinding production line provided by the embodiments of the present application is shown; Figure 3 Another flowchart of the instrument reliability detection method provided by the embodiments of the present application is shown; Figure 4 Still another flowchart of the instrument reliability detection method provided by the embodiments of the present application is shown; Figure 5 Still another flowchart of the instrument reliability detection method provided by the embodiments of the present application is shown; Figure 6 Still another flowchart of the instrument reliability detection method provided by the embodiments of the present application is shown; Figure 7A structural schematic diagram of an instrument detection system provided by an embodiment of the present application is shown. Figure 8 A structural schematic diagram of an electronic device provided by an embodiment of the present application is shown.

[0016] Main element symbol description: 700 - instrument reliability detection system; 710 - first acquisition module; 720 - second acquisition module; 730 - first determination module; 740 - second determination module; 800 - electronic device; 801 - transceiver; 802 - processor; 803 - memory. DETAILED DESCRIPTION

[0017] Embodiments of the present application are described in detail below with reference to the accompanying drawings, examples of which are shown in the drawings, wherein the same or similar notations represent the same or similar elements or elements having the same or similar functions throughout. The embodiments described below with reference to the accompanying drawings are exemplary and are only used to explain the present application, and cannot be understood as a limitation of the present application.

[0018] In addition, the terms "first", "second" are only for descriptive purposes, and cannot be understood as indicating or implying relative importance or implicitly indicating the number of indicated technical features. Therefore, the features defined with "first", "second" can explicitly or implicitly include one or more of the features. In the description of the present application, the meaning of "a plurality of" is two or more, unless otherwise explicitly specified.

[0019] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which the present application belongs. The terms used in the specification of the template herein are only for the purpose of describing specific embodiments and are not intended to limit the present application. The term "and / or" used herein includes any and all combinations of one or more related listed items.

[0020] Embodiment 1 In the grinding production process, the stability and reliability of the detection instrument are very important, in the prior art, it is usually necessary for experienced operators to observe instrument data regularly, and to comprehensively analyze the historical distribution of instrument data and the current working condition, and then to evaluate the reliability of the detection instrument, which is low in efficiency and difficult to promote. For this purpose, please refer to Figure 1 , the present application provides an instrument reliability detection method, which is applied to a grinding production line as shown in Figure 2 , the grinding production line comprises N detection instruments, N≥1, and the method comprises steps S110-S140.

[0021] Before the instrument reliability detection method provided by the embodiments of the present application is introduced, the ore grinding production line is briefly introduced, please refer to Figure 2 , the ore grinding production line includes: a fine ore bin, a belt scale, a ball mill, an ore grinding pump pool, a sand pump and a cyclone. The working process is: the ore in the fine ore bin is sent into the ball mill after being measured by the belt scale, at the same time, the front water supply of the ball mill participates in the grinding process of the ball mill, the ore slurry after being ground by the ball mill flows into the ore grinding pump pool, is transported to the cyclone through the sand pump, and the cyclone performs classification and flotation on the sand slurry, and the sand slurry with larger particles is re-transported back to the ball mill for continuous grinding, and the sand slurry with smaller particles is output through the flotation process. The ore grinding production line includes N detection instruments, specifically including: a water flow meter arranged at the water supply port of the ore grinding pump pool, a water flow meter arranged at the front water supply port of the ball mill, an ore supply flow meter and an ore supply concentration meter arranged at the output port of the sand pump, and an overflow flow meter and an overflow concentration meter arranged at the flotation output port of the cyclone. The instrument reliability detection method provided by the embodiments of the present application is introduced below, and the method includes steps S110-S140.

[0022] Step S110, obtaining an i-th detection strategy of an i-th detection instrument, wherein 1≤i≤N, the i-th detection strategy is determined according to at least one of the following data: an instrument value of the i-th detection instrument and an operating parameter of a linkage device, the linkage device being a device in the ore grinding production line that affects the instrument value of the i-th detection instrument.

[0023] In this embodiment, the reliability state of the i-th detection instrument is determined according to a reliability factor, wherein the reliability factor includes at least one of the following: a communication state, a logic state and a value state, and the i-th detection strategy of the i-th detection instrument is used to determine at least one of the communication state, the logic state and the value state.

[0024] It should be noted that the i-th detection strategy is formulated according to at least one aspect of data: one is the real-time measurement value of the i-th detection instrument, that is, the instrument value; the other is the operating parameter of the linkage device in the ore grinding production line that can affect the instrument value of the i-th detection instrument. Taking the belt scale as an example, the linkage device thereof is a belt feeder. It can be understood that the instrument value of the belt scale is related to the frequency of the belt feeder, the greater the frequency of the belt feeder, the greater the instrument value of the belt scale, and the smaller the frequency of the belt feeder, the smaller the instrument value of the belt scale. When detecting the reliability of the belt scale, the detection strategy can verify the logic rationality of the belt scale ore supply amount according to the frequency change of the belt feeder, so as to determine whether the logic state of the instrument is normal.

[0025] Step S120, obtaining an instrument data set of the i-th detection instrument, the instrument data set including a plurality of instrument values collected by the i-th detection instrument within a preset time period.

[0026] In the embodiment, the preset time period can be 1 hour, 2 hours, etc. In the preset time period, the i-th detection instrument continuously collects instrument values at a preset frequency, and each instrument value constitutes an instrument data set of the i-th detection instrument.

[0027] In step S130, a reliability evaluation factor of the i-th detection instrument is determined according to the instrument data set of the i-th detection instrument and the i-th detection strategy. The reliability evaluation factor includes at least one of a communication state, a logic state, and a value state.

[0028] In the embodiment, the reliability evaluation factor of the detection instrument is determined by analyzing the value size, the value change rule, and the logical association between the instrument values in the instrument data set and the operating parameters of the linkage equipment. The reliability evaluation factor includes at least one of the communication state, the logic state, and the value state.

[0029] In an embodiment, the i-th detection strategy is determined according to the instrument values of the i-th detection instrument. Please refer to Figure 3 In step S130, a reliability evaluation factor of the i-th detection instrument is determined according to the instrument data set of the i-th detection instrument and the i-th detection strategy. The reliability evaluation factor includes at least one of a communication state, a logic state, and a value state.

[0030] In step S301, it is determined whether each instrument value in the instrument data set belongs to the i-th preset range.

[0031] It can be understood that for multiple instrument values in the instrument data set of the i-th detection instrument, it is determined whether each instrument value belongs to the i-th preset range of the i-th detection instrument. For example, taking a mine feed flowmeter as an example, the preset range of the mine feed flowmeter is 0-1000 m³ / h. Through this step, the rationality of the instrument values of the i-th detection instrument can be verified, and the communication state of the i-th detection instrument can be preliminarily determined. If the value exceeds the preset range, it is determined that the communication state of the i-th detection instrument is abnormal.

[0032] In step S302, if not, it is determined that the communication state of the i-th detection instrument is abnormal. It can be understood that a detection instrument working normally should always be within a physically feasible preset range. Excessive values are usually caused by communication terminals, data transmission errors, or instrument hardware failures. In step S303, if yes, it is determined whether there is a first sub-time period that satisfies the following condition: whether the multiple instrument values collected in the first sub-time period are the same, wherein the first sub-time period belongs to the preset time period, and the first sub-time period is greater than a first preset time threshold.

[0033] In the embodiment, if all the instrument values are within the preset range, further analysis is performed on the instrument data set to determine whether there are multiple instrument values belonging to the first sub-time period that are the same. If there are, it is proved that the instrument value exceeds the first preset time threshold and remains unchanged, and at this time, it can be determined that the communication state of the ith detection instrument is: abnormal state. It can be understood that this step is used to determine whether the ith detection instrument is continuously updated to avoid data freezing caused by communication link jamming.

[0034] Step S304, if there are, it is determined that the communication state of the ith detection instrument is: abnormal state.

[0035] It can be understood that a normally operating detection instrument should update in real time with changes in process parameters. If the instrument value of the ith detection instrument does not change for a long time in the normal production process, it is determined that the communication state of the ith detection instrument is: abnormal state.

[0036] Step S305, if there are not, it is determined that the communication state of the ith detection instrument is: normal state.

[0037] If no first sub-time period satisfying the condition is found (i.e., all instrument values normally fluctuate within the preset time period, or even if there is a short period of invariance, but the duration does not exceed the first preset threshold), it is determined that the communication state of the ith detection instrument is: normal state. This means that the instrument value is within a reasonable range and can update in real time with changes in the process, and the communication link is working normally.

[0038] In an embodiment, the ith detection strategy is determined according to the operating parameters of the linkage device, please refer to Figure 4 According to the instrument data set of the ith detection instrument and the ith detection strategy, the logic state of the ith detection instrument is obtained, including steps S401-S403.

[0039] S401, the operating parameter set of the linkage device of the ith detection instrument is obtained, and the operating parameter set includes: multiple operating parameter values of the linkage device within a preset time period.

[0040] In the embodiment, the linkage device is a device in the ore grinding production line that affects the instrument value of the ith detection instrument. For example, the linkage device of the belt scale is the belt feeder; for example, the linkage device of the water flow meter is the valve; for example, the linkage devices of the ore concentration meter and the overflow concentration meter are both ball mills; for example, the linkage devices of the ore flow meter and the overflow flow meter are both cyclones.

[0041] It is understandable that there is the following logical relationship between the operating parameters of the belt scale and the belt feeder—frequency: when the feeding frequency of the belt feeder increases, the instrument value of the belt scale increases; when the feeding frequency of the belt feeder decreases, the instrument value of the belt scale decreases.

[0042] There is a logical relationship between the operating parameters of the water flow meter and the valve—specifically, the valve opening degree: when the valve opening degree increases, the reading on the water flow meter increases; when the valve opening degree decreases, the reading on the water flow meter decreases.

[0043] There is a logical relationship between the feed concentration meter and the overflow concentration meter and the operating parameter of the ball mill—the feed rate: when the feed rate increases, the instrument readings of the feed concentration meter and the overflow concentration meter increase; when the feed rate decreases, the instrument readings of the feed concentration meter and the overflow concentration meter decrease.

[0044] The following logical relationship exists between the operating parameters of the feed flow meter, overflow flow meter, and hydrocyclone—the number of channel opening groups: as the number of channel opening groups increases, the instrument readings of the feed flow meter and overflow flow meter increase; as the number of channel opening groups decreases, the instrument readings of the feed flow meter and overflow flow meter decrease.

[0045] S402, determine the operating parameter curve of the linkage device according to each of the operating parameters in the operating parameter set, and determine the instrument curve according to each of the instrument values ​​in the instrument dataset. In this embodiment, the logic state of the i-th detection instrument can be determined by observing the curve trends of the operating parameter curve and the instrument curve.

[0046] S403, if the operating parameter curve shows an increasing trend and the instrument curve shows a decreasing trend during the second sub-time period, or the operating parameter curve shows a decreasing trend and the instrument curve shows an increasing trend, then the logical state of the i-th detection instrument is determined to be: abnormal state, wherein the second sub-time period belongs to the preset time period and the second sub-time period is greater than the second preset time threshold.

[0047] In this embodiment, if the i-th detection instrument is a belt scale, then the logical state of the belt scale can be determined as: Abnormal state:

[0048] or,

[0049] in, This indicates the change in the feeding frequency of the belt feeder during the second sub-time period. This indicates the change in the instrument reading of the belt scale during the second sub-time period.

[0050] If the i-th measuring instrument is a water flow meter, then the logical state of the water flow meter can be determined as follows: Abnormal state:

[0051] or,

[0052] in, This indicates the change in valve opening during the second sub-time period. This indicates the change in the meter reading of the water flow meter during the second sub-time period.

[0053] If the i-th measuring instrument is a feed concentration meter (overflow concentration meter), then the logical state of the feed concentration meter (overflow concentration meter) can be determined as follows when the following conditions are met: Abnormal state:

[0054] or,

[0055] in, This represents the change in the ball mill's feed rate during the second sub-time period. This indicates the change in the meter reading of the feed concentration meter (overflow concentration meter) during the second sub-time period.

[0056] If the i-th measuring instrument is a feed flow meter (overflow flow meter), then the logical state of the feed flow meter (overflow flow meter) can be determined as follows when the following conditions are met: Abnormal state:

[0057] or,

[0058] in, This indicates the change in the number of open channels of the hydrocyclone during the second sub-time period. This indicates the change in the meter reading of the feed flow meter (overflow flow meter) during the second sub-time period.

[0059] In one embodiment, the i-th detection strategy is determined based on the meter value of the i-th detection instrument and the operating parameters of the linkage device; The grinding production line includes a hydrocyclone and a ball mill; the detection instruments include an overflow flow meter and an overflow concentration meter, wherein the overflow flow meter is used to detect the overflow flow rate of the hydrocyclone, and the overflow concentration meter is used to detect the overflow concentration of the hydrocyclone; the operating parameters of the linked equipment include the feed rate of the ball mill; please refer to [link to relevant documentation]. Figure 5The step of obtaining the numerical status of the i-th detection instrument based on the instrument dataset of the i-th detection instrument and the i-th detection strategy includes steps S501 to S504.

[0060] Step S501: Obtain the dry ore density, and determine the overflow density based on the dry ore density and the overflow concentration.

[0061] Obtain the dry ore density, and then, combined with the overflow concentration (the percentage of solids in the slurry) detected by the overflow concentration meter, calculate the overflow density using the following formula:

[0062] in, Indicates the density of dry ore. Indicates the overflow concentration. This indicates the overflow density.

[0063] Step S502: Determine the overflow mass based on the overflow density and the overflow flow rate.

[0064] Calculate the overflow mass using the following formula:

[0065] in, Indicates the overflow quality. This indicates the overflow flow rate.

[0066] Step S503: Determine the amount of overflow solids based on the overflow mass and the overflow concentration.

[0067] The amount of overflow solids is determined using the following formula:

[0068] in, This indicates the amount of solids overflowing.

[0069] Step S504: Obtain the feed rate of the ball mill. If the absolute value of the difference between the overflow solids and the feed rate is greater than a first preset difference, then determine that the value status of the overflow flow meter is: abnormal status.

[0070] It is understandable that, when the grinding process reaches equilibrium, the overflow solids should theoretically be equal to the feed rate of the ball mill, i.e. Where Q represents the feed rate of the ball mill. In actual production, if the difference between the overflow solids and the feed rate of the ball mill is too large, the value of the overflow flow meter will be in an abnormal state, which means that there may be a calibration error or instrument failure.

[0071] Specifically, if ,in, If the first preset difference is indicated, then the numerical status of the overflow flow meter is determined to be: abnormal state.

[0072] In one embodiment, the i-th detection strategy is determined based on the meter value of the i-th detection instrument; the detection instrument further includes a feed flow meter and a feed concentration meter, wherein the feed flow meter is used to detect the feed flow rate of the hydrocyclone, and the feed concentration meter is used to detect the feed concentration of the hydrocyclone; see also Figure 6 The step of obtaining the numerical status of the i-th detection instrument based on the instrument dataset of the i-th detection instrument and the i-th detection strategy includes steps S601 to S608.

[0073] It should be noted that the hydrocyclone's feed, overflow, and settling constitute a closed material circulation system. According to the law of conservation of mass, the mass of the feed should equal the sum of the overflow mass and the settling mass, and the amount of solids in the feed should equal the sum of the overflow solids and the settling solids. If the instrument readings break this balance, it indicates a possible malfunction in the instrument. Based on this law of conservation of mass, the numerical status of the measuring instrument can be determined.

[0074] Step S601: Determine the feed density based on the dry ore density and the feed concentration.

[0075] Obtain the dry ore density, and then, in conjunction with the ore concentration detected by the feed concentration meter, calculate the feed density using the following formula:

[0076] in, , .

[0077] Step S602: Determine the feed quality based on the feed density and the feed flow rate.

[0078] Calculate the feed mass using the following formula:

[0079] in, Indicates the quality of the ore supplied. This indicates the flow rate to the ore deposited.

[0080] Step S603: Determine the sedimentation mass based on the ore feed mass and the overflow mass.

[0081] Calculate the mass of settled sand using the following formula:

[0082] in, Indicates the mass of sediment.

[0083] Step S604: Determine the amount of solids in the feed based on the feed quality and the feed concentration.

[0084] Calculate the amount of solids in the feed using the following formula:

[0085] in, This indicates the amount of solids fed into the ore.

[0086] Step S605: Determine the amount of settled sand solids based on the amount of ore fed solids and the amount of overflow solids.

[0087] Calculate the amount of solid sediment using the following formula:

[0088] in, This indicates the amount of solid sediment.

[0089] Step S606: Determine the ratio of the amount of settled solids to the amount of overflow solids as the actual ratio.

[0090] The actual ratio is determined using the following formula:

[0091] in, This represents the actual ratio.

[0092] Step S607: The ratio of the amount of solid sediment to the mass of sediment is determined as the sediment concentration.

[0093] The sediment concentration is determined using the following formula:

[0094] Where C represents the sediment concentration.

[0095] Step S608: If the absolute value of the difference between the actual ratio and the preset theoretical ratio is greater than the second preset difference, or the absolute value of the difference between the sediment concentration and the preset theoretical sediment concentration is greater than the third preset difference, then the numerical state of the feed flow meter is determined to be: abnormal state.

[0096] when At that time, the value status of the feed flow meter was determined to be: abnormal state.

[0097] Step S140: Determine the reliability status of the i-th detection instrument based on the reliability evaluation factor, wherein the reliability status includes reliable or unreliable.

[0098] Reliability evaluation factors include at least one of the following: communication status, logic status, and numerical status.

[0099] In one embodiment, the reliability evaluation factor includes: communication status and logic status; determining the reliability status of the i-th detection instrument based on the reliability evaluation factor includes: if both the communication status and the logic status are normal, then the reliability status of the i-th detection instrument is determined to be: reliable.

[0100] For some measuring instruments, such as belt scales and water flow meters, the reliability status of the instrument is determined based on its communication status and logic status. Specifically, when both the communication status and the logic status are normal, the reliability status of the instrument is determined to be reliable; conversely, if either the communication status or the logic status is abnormal, the reliability status of the measuring instrument is determined to be unreliable.

[0101] The reliability evaluation factors include: communication status, logic status, and numerical status; determining the reliability status of the i-th detection instrument based on the reliability evaluation factors includes: if the communication status, logic status, and numerical status are all normal, then the reliability status of the i-th detection instrument is determined to be: reliable.

[0102] For some detection instruments, such as feed flow meters and overflow flow meters, it is necessary to further confirm whether their numerical status is normal. When the communication status, logic status, and numerical status are all normal, the reliability status of the detection instrument is confirmed as reliable. Conversely, if the communication status, logic status, or numerical status is abnormal, the reliability status of the detection instrument is determined to be unreliable.

[0103] The reliability evaluation factor includes any one of the following: the communication state, the logic state, and the numerical state; if any one of the communication state, the logic state, and the numerical state is an abnormal state, then the reliability state of the i-th detection instrument is determined to be: unreliable.

[0104] For the i-th testing instrument, if any one of the reliability evaluation factors—communication state, logic state, and numerical state—is in an abnormal state, then the reliability state of the i-th testing instrument is determined to be: unreliable.

[0105] In one embodiment, after determining that the numerical state of the feed flow meter is an abnormal state, the method further includes: performing a correlation analysis on the feed flow; if the correlation coefficient is greater than a preset coefficient, determining a predicted feed flow value based on the operating parameters of the linked equipment of the feed flow meter and the feed flow prediction model; determining a deviation value based on the predicted feed flow value and the feed flow value; and correcting the feed flow value based on the deviation value.

[0106] In this embodiment, the correlation between the feed flow rate and the operating parameters of the linked equipment (such as ball mills and belt scales) is calculated (e.g., Pearson coefficient). If the coefficient is greater than a preset coefficient, for example, 0.7, it indicates that the feed flow rate is significantly correlated with other parameters, and prediction correction can be performed using a feed flow rate prediction model. Furthermore, the feed flow rate prediction model (such as a regression model or neural network) trained based on historical data, combined with the current operating parameters of the linked equipment (such as belt speed and motor power), calculates the theoretical predicted value of the feed flow rate.

[0107] The deviation value is determined by the difference between the predicted feed flow rate and the actual feed flow rate. The deviation value is then superimposed on the actual feed flow rate using a compensation algorithm to obtain the corrected feed flow rate value.

[0108] The instrument reliability detection method provided in this application embodiment obtains the i-th detection strategy of the i-th detection instrument, where 1≤i≤N, and the i-th detection strategy is determined based on at least one of the following data: the instrument value of the i-th detection instrument and the operating parameters of the linked equipment, wherein the linked equipment is the equipment in the grinding production line that affects the instrument value of the i-th detection instrument; obtains the instrument dataset of the i-th detection instrument, the instrument dataset including: multiple instrument values ​​collected by the i-th detection instrument within a preset time period; determines the reliability evaluation factor of the i-th detection instrument based on the instrument dataset and the i-th detection strategy, the reliability evaluation factor including at least one of the following: communication status, logic status, and numerical status; determines the reliability status of the i-th detection instrument based on the reliability evaluation factor, the reliability status including reliable or unreliable, and evaluates the reliability of the detection instrument from three dimensions: communication status, logic status, and numerical status, thereby realizing automated detection of instrument reliability and effectively improving the reliability detection efficiency of the detection instrument.

[0109] Example 2 In addition, please see Figure 7 This application also provides an instrument reliability testing system 700, comprising: The first acquisition module 710 is used to acquire the i-th detection strategy of the i-th detection instrument, where 1≤i≤N, and the i-th detection strategy is determined based on at least one of the following data: the instrument value of the i-th detection instrument and the operating parameters of the linkage device, wherein the linkage device is the device in the grinding production line that affects the instrument value of the i-th detection instrument. The second acquisition module 720 is used to acquire the instrument dataset of the i-th detection instrument, the instrument dataset including: multiple instrument values ​​collected by the i-th detection instrument within a preset time period; The first determining module 730 is used to determine the reliability evaluation factor of the i-th detection instrument based on the instrument dataset of the i-th detection instrument and the i-th detection strategy. The reliability evaluation factor includes at least one of the following: communication status, logic status and numerical status. The second determining module 740 is used to determine the reliability status of the i-th detection instrument based on the reliability evaluation factor, wherein the reliability status includes reliable or unreliable.

[0110] The instrument reliability testing system 700 provided in this application embodiment can execute the instrument reliability testing method provided in the above method embodiment 1. To avoid repetition, it will not be described again here.

[0111] The instrument reliability testing system provided in this application embodiment acquires the i-th testing strategy of the i-th testing instrument through a first acquisition module, where 1≤i≤N. The i-th testing strategy is determined based on at least one of the following data: the instrument value of the i-th testing instrument and the operating parameters of the linked equipment, wherein the linked equipment is the equipment in the grinding production line that affects the instrument value of the i-th testing instrument. A second acquisition module acquires the instrument dataset of the i-th testing instrument, which includes multiple instrument values ​​collected by the i-th testing instrument within a preset time period. A first determination module determines the reliability evaluation factor of the i-th testing instrument based on the instrument dataset and the i-th testing strategy. The reliability evaluation factor includes at least one of the following: communication status, logic status, and numerical status. The second determination module determines the reliability status of the i-th testing instrument based on the reliability evaluation factor. The reliability status includes reliable or unreliable. The reliability of the testing instrument is evaluated from three dimensions: communication status, logic status, and numerical status, thereby realizing automated detection of instrument reliability and effectively improving the reliability detection efficiency of the testing instrument.

[0112] Example 3 Furthermore, embodiments of the present invention provide an electronic device, including a memory and a processor, wherein the memory stores a computer program, and the computer program executes the instrument reliability detection method provided in Embodiment 1 when running on the processor.

[0113] For details, please see Figure 8The electronic device 800 includes: a transceiver 801, a bus interface, and a processor 802. The processor 802 is used to acquire the i-th detection strategy of the i-th detection instrument, where 1 ≤ i ≤ N. The i-th detection strategy is determined based on at least one of the following data: the instrument value of the i-th detection instrument and the operating parameters of the linked equipment, wherein the linked equipment is the equipment in the grinding production line that affects the instrument value of the i-th detection instrument; acquire the instrument dataset of the i-th detection instrument, wherein the instrument dataset includes: multiple instrument values ​​collected by the i-th detection instrument within a preset time period; determine the reliability evaluation factor of the i-th detection instrument based on the instrument dataset and the i-th detection strategy, wherein the reliability evaluation factor includes at least one of the following: communication status, logic status, and numerical status; and determine the reliability status of the i-th detection instrument based on the reliability evaluation factor, wherein the reliability status includes reliable or unreliable.

[0114] In this embodiment of the invention, the electronic device 800 further includes a memory 803. Figure 8 In this context, the bus architecture can include any number of interconnected buses and bridges, specifically linking various circuits together, represented by one or more processors (processor 802) and memory (memory 803). The bus architecture can also link together various other circuits such as peripheral devices, voltage regulators, and power management circuits, which are well known in the art and therefore will not be described further herein. The bus interface provides an interface. The transceiver 801 can be multiple elements, including transmitters and receivers, providing a unit for communicating with various other devices over a transmission medium. The processor 802 is responsible for managing the bus architecture and general processing, and the memory 803 can store data used by the processor 802 during operation.

[0115] The electronic device 800 provided in this embodiment of the invention can execute the instrument reliability detection method provided in the above-described method embodiment 1. To avoid repetition, it will not be described again here.

[0116] Example 4 Furthermore, embodiments of the present invention provide a computer-readable storage medium storing a computer program, which, when executed by a processor, implements the instrument reliability detection method provided in Embodiment 1.

[0117] In this embodiment, the computer-readable storage medium may be a read-only memory (ROM), a random access memory (RAM), a magnetic disk, or an optical disk, etc.

[0118] The computer-readable storage medium provided in this embodiment can implement the instrument reliability testing method provided in Embodiment 1. To avoid repetition, it will not be described again here.

[0119] In all examples shown and described herein, any specific values ​​should be interpreted as merely exemplary and not as limitations; therefore, other examples of exemplary embodiments may have different values.

[0120] It should be noted that similar labels and letters in the following figures indicate similar items. Therefore, once an item is defined in one figure, it does not need to be further defined and explained in subsequent figures.

[0121] The above-described embodiments are merely illustrative of several implementations of the present invention, and while the descriptions are specific and detailed, they should not be construed as limiting the scope of the invention. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of the present invention, and these modifications and improvements all fall within the scope of protection of the present invention.

Claims

1. A method for testing the reliability of an instrument, characterized in that, The method is applied to a grinding production line, which includes N detection instruments, where N ≥ 1, and includes: Obtain the i-th detection strategy of the i-th detection instrument, where 1≤i≤N, and the i-th detection strategy is determined based on at least one of the following data: the instrument value of the i-th detection instrument and the operating parameters of the linkage device, wherein the linkage device is the device in the grinding production line that affects the instrument value of the i-th detection instrument; Obtain the instrument dataset of the i-th detection instrument, wherein the instrument dataset includes: multiple instrument values ​​collected by the i-th detection instrument within a preset time period; Based on the instrument dataset of the i-th detection instrument and the i-th detection strategy, a reliability evaluation factor for the i-th detection instrument is determined. The reliability evaluation factor includes at least one of the following: communication status, logic status, and numerical status. The reliability status of the i-th detection instrument is determined based on the reliability evaluation factor, wherein the reliability status includes reliable or unreliable.

2. The instrument reliability testing method according to claim 1, characterized in that, The i-th detection strategy is determined based on the meter value of the i-th detection instrument. The communication status of the i-th detection instrument is determined based on the meter dataset of the i-th detection instrument and the i-th detection strategy, including: Determine whether each instrument value in the instrument dataset belongs to the i-th preset range; If not, then the communication status of the i-th detection instrument is determined to be: abnormal status; If so, determine whether there is a first sub-time period that meets the following conditions: whether the multiple instrument values ​​collected in the first sub-time period are the same, wherein the first sub-time period belongs to the preset time period and the first sub-time period is greater than the first preset time threshold. If it exists, then the communication status of the i-th detection instrument is determined to be: abnormal status; If it does not exist, then the communication status of the i-th detection instrument is determined to be: normal status.

3. The instrument reliability testing method according to claim 1, characterized in that, The i-th detection strategy is determined based on the operating parameters of the linked equipment. Based on the instrument dataset of the i-th detection instrument and the i-th detection strategy, the logical state of the i-th detection instrument is obtained, including: Obtain the operating parameter set of the linkage device of the i-th detection instrument, the operating parameter set including: multiple operating parameter values ​​of the linkage device within a preset time period; The operating parameter curve of the linkage device is determined based on each operating parameter in the operating parameter set, and the instrument curve is determined based on each instrument value in the instrument dataset; If, during the second sub-time period, the operating parameter curve shows an increasing trend and the instrument curve shows a decreasing trend, or the operating parameter curve shows a decreasing trend and the instrument curve shows an increasing trend, then the logical state of the i-th detection instrument is determined to be: abnormal state, wherein the second sub-time period belongs to the preset time period and the second sub-time period is greater than the second preset time threshold.

4. The instrument reliability testing method according to claim 1, characterized in that, The i-th detection strategy is determined based on the meter value of the i-th detection instrument and the operating parameters of the linkage equipment; The grinding production line includes a hydrocyclone and a ball mill; the detection instruments include an overflow flow meter and an overflow concentration meter, wherein the overflow flow meter is used to detect the overflow flow rate of the hydrocyclone and the overflow concentration meter is used to detect the overflow concentration of the hydrocyclone; the operating parameters of the linkage equipment include the feed rate of the ball mill; The step of obtaining the numerical status of the i-th detection instrument based on the instrument dataset of the i-th detection instrument and the i-th detection strategy includes: Obtain the dry ore density, and determine the overflow density based on the dry ore density and the overflow concentration; The overflow mass is determined based on the overflow density and the overflow flow rate; The amount of solids overflowed is determined based on the overflow mass and the overflow concentration. The feed rate of the ball mill is obtained. If the absolute value of the difference between the overflow solids and the feed rate is greater than a first preset difference, the numerical status of the overflow flow meter is determined to be: abnormal state.

5. The instrument reliability testing method according to claim 4, characterized in that, The i-th detection strategy is determined based on the instrument value of the i-th detection instrument; the detection instrument further includes: a feed flow meter and a feed concentration meter, wherein the feed flow meter is used to detect the feed flow rate of the hydrocyclone, and the feed concentration meter is used to detect the feed concentration of the hydrocyclone; The step of obtaining the numerical status of the i-th detection instrument based on the instrument dataset of the i-th detection instrument and the i-th detection strategy includes: The feed density is determined based on the dry ore density and the feed concentration; The feed quality is determined based on the feed density and the feed flow rate; The sedimentation mass is determined based on the ore feed mass and the overflow mass; The amount of solids in the feed is determined based on the feed mass and the feed concentration. The amount of settled solids is determined based on the amount of ore fed solids and the amount of overflow solids. The ratio of the amount of settled solids to the amount of overflow solids is determined as the actual ratio. The ratio of the amount of solid sediment to the mass of sediment is defined as the sediment concentration. If the absolute value of the difference between the actual ratio and the preset theoretical ratio is greater than the second preset difference, or the absolute value of the difference between the sediment concentration and the preset theoretical sediment concentration is greater than the third preset difference, then the numerical state of the feed flow meter is determined to be: abnormal state.

6. The instrument reliability testing method according to claim 1, characterized in that, The reliability evaluation factors include: communication status and logic status; determining the reliability status of the i-th detection instrument based on the reliability evaluation factors includes: If both the communication state and the logic state are normal, then the reliability state of the i-th detection instrument is determined to be: reliable. The reliability evaluation factors include: communication status, logic status, and numerical status; determining the reliability status of the i-th detection instrument based on the reliability evaluation factors includes: If the communication status, the logic status, and the numerical status are all normal, then the reliability status of the i-th detection instrument is determined to be: reliable. The reliability evaluation factor includes any one of the following: the communication status, the logical status, and the numerical status; If any one of the communication state, the logic state, and the numerical state is an abnormal state, then the reliability state of the i-th detection instrument is determined to be: unreliable.

7. The instrument reliability testing method according to claim 5, characterized in that, After determining that the numerical state of the feed flow meter is abnormal, the method further includes: A correlation analysis is performed on the feed flow rate. If the correlation coefficient is greater than the preset coefficient, the predicted feed flow rate is determined based on the operating parameters of the linkage equipment of the feed flow meter and the feed flow rate prediction model. The deviation value is determined based on the predicted feed flow rate and the actual feed flow rate. The feed flow rate is corrected based on the deviation value.

8. An instrument reliability testing system, characterized in that, The system includes: The first acquisition module is used to acquire the i-th detection strategy of the i-th detection instrument, where 1≤i≤N. The i-th detection strategy is determined based on at least one of the following data: the instrument value of the i-th detection instrument and the operating parameters of the linkage device. The linkage device is the device in the grinding production line that affects the instrument value of the i-th detection instrument. The second acquisition module is used to acquire the instrument dataset of the i-th detection instrument, the instrument dataset including: multiple instrument values ​​collected by the i-th detection instrument within a preset time period; The first determining module is used to determine the reliability evaluation factor of the i-th detection instrument based on the instrument dataset of the i-th detection instrument and the i-th detection strategy. The reliability evaluation factor includes at least one of the following: communication status, logic status and numerical status. The second determining module is used to determine the reliability status of the i-th detection instrument based on the reliability evaluation factor, wherein the reliability status includes reliable or unreliable.

9. An electronic device, characterized in that, It includes a memory and a processor, wherein the memory stores a computer program, and the computer program, when run on the processor, executes the instrument reliability testing method according to any one of claims 1-7.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program that, when executed by a processor, implements the instrument reliability testing method according to any one of claims 1-7.

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