Instrument reliability detection method, system, device and medium

Abstract

The application provides an instrument reliability detection method, system, device and medium, and relates to the technical field of instrument detection. The method comprises the following steps: acquiring an i-th detection instrument and an i-th detection strategy. 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 is a device in a grinding production line that affects the instrument value of the i-th detection instrument. An instrument data set of the i-th detection instrument is acquired. The instrument data set comprises a plurality of instrument values collected by the i-th 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, a reliability evaluation factor of the i-th detection instrument is determined. The reliability evaluation factor comprises at least one of the following: a communication state, a logic state and a value state. According to the reliability evaluation factor, a reliability state of the i-th detection instrument is determined. The application improves the detection efficiency of the detection instrument.

Description

Technical Field

[0001] This invention relates to the field of instrument testing technology, and more specifically, to an instrument reliability testing method, system, equipment, and medium. Background Technology

[0002] The grinding process in ball mills is complex and variable. The measuring instruments used in the grinding process come into direct contact with solid materials or slurry, affecting their stability and reliability. Current technologies typically require experienced operators to periodically observe instrument data and comprehensively analyze its historical distribution to determine its reliability in light of current operating conditions. This approach is inefficient and difficult to implement widely. Summary of the Invention

[0003] In view of this, the purpose of this invention is to overcome the shortcomings of the prior art and provide a method, system, device, and medium for testing the reliability of instruments. This invention provides the following technical solution:

[0004] In a first aspect, the present invention provides an instrument reliability testing method applied to a grinding production line, the grinding production line comprising: N testing instruments, N≥1, the method comprising:

[0005] 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;

[0006] 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;

[0007] 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.

[0008] 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.

[0009] In one embodiment, the i-th detection strategy is determined based on the meter value of the i-th detection instrument, and 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:

[0010] Determine whether each instrument value in the instrument dataset belongs to the i-th preset range;

[0011] If not, then the communication status of the i-th detection instrument is determined to be: abnormal status;

[0012] 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.

[0013] If it exists, then the communication status of the i-th detection instrument is determined to be: abnormal status;

[0014] If it does not exist, then the communication status of the i-th detection instrument is determined to be: normal status.

[0015] In one embodiment, the i-th detection strategy is determined based on the operating parameters of the linked equipment. The logical state of the i-th detection instrument is obtained based on the instrument dataset of the i-th detection instrument and the i-th detection strategy, including:

[0016] 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;

[0017] 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;

[0018] 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.

[0019] 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;

[0020] 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;

[0021] 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:

[0022] Obtain the dry ore density, and determine the overflow density based on the dry ore density and the overflow concentration;

[0023] The overflow mass is determined based on the overflow density and the overflow flow rate;

[0024] The amount of solids overflowed is determined based on the overflow mass and the overflow concentration.

[0025] 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.

[0026] 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;

[0027] 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:

[0028] The feed density is determined based on the dry ore density and the feed concentration;

[0029] The feed quality is determined based on the feed density and the feed flow rate;

[0030] The sedimentation mass is determined based on the ore feed mass and the overflow mass;

[0031] The amount of solids in the feed is determined based on the feed mass and the feed concentration.

[0032] The amount of settled solids is determined based on the amount of solids fed into the ore and the amount of solids overflowed.

[0033] The ratio of the amount of settled solids to the amount of overflow solids is determined as the actual ratio.

[0034] The ratio of the amount of solid sediment to the mass of sediment is defined as the sediment concentration.

[0035] 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.

[0036] 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:

[0037] 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;

[0038] 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:

[0039] If the communication state, the logic state, and the numerical state are all in normal condition, then the reliability state of the i-th detection instrument is determined to be: reliable.

[0040] The reliability evaluation factor includes any one of the following: the communication status, the logical status, and the numerical status;

[0041] 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.

[0042] In one embodiment, after determining that the numerical state of the feed flow meter is an abnormal state, the method further includes:

[0043] 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.

[0044] The deviation value is determined based on the predicted feed flow rate and the actual feed flow rate.

[0045] The feed flow rate is corrected based on the deviation value.

[0046] Secondly, the present invention provides an instrument reliability testing system, the system comprising:

[0047] 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.

[0048] 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;

[0049] 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.

[0050] 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.

[0051] Thirdly, the present invention provides an electronic device, including 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 detection method described in any of the foregoing embodiments.

[0052] Fourthly, the present invention provides a computer-readable storage medium storing a computer program, which, when executed by a processor, implements the instrument reliability detection method described in any of the foregoing embodiments.

[0053] This application provides a method, system, device, and medium for instrument reliability testing. The method involves obtaining an i-th testing strategy for the i-th testing instrument, 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 a device in the grinding production line that affects the instrument value of the i-th testing instrument. The method also involves obtaining an instrument dataset for the i-th testing instrument, which includes multiple instrument values ​​collected by the i-th testing instrument within a preset time period. Based on the instrument dataset and the i-th testing strategy, a reliability evaluation factor for the i-th testing instrument is determined, which includes at least one of the following: communication status, logic status, and numerical status. Finally, the reliability status of the i-th testing instrument is determined based on the reliability evaluation factor, where the reliability status includes reliable or unreliable. By evaluating the reliability of the testing instrument from three dimensions—communication status, logic status, and numerical status—automatic testing of instrument reliability is achieved, effectively improving the efficiency of instrument reliability testing.

[0054] To make the above-mentioned objects, features and advantages of the present invention more apparent and understandable, preferred embodiments are described below in detail with reference to the accompanying drawings. Attached Figure Description

[0055] To more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings used in the embodiments will be briefly introduced below. It should be understood that the following drawings only show some embodiments of the present invention and should not be regarded as a limitation on the scope. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort.

[0056] Figure 1 A flowchart of an instrument reliability testing method provided in an embodiment of this application is shown;

[0057] Figure 2 A schematic diagram of a grinding production line provided in an embodiment of this application is shown;

[0058] Figure 3 Another schematic flowchart of the instrument reliability testing method provided in this application embodiment is shown;

[0059] Figure 4 This paper illustrates another schematic flowchart of the instrument reliability testing method provided in the embodiments of this application;

[0060] Figure 5 This illustration shows another schematic flowchart of the instrument reliability testing method provided in the embodiments of this application;

[0061] Figure 6 A schematic diagram of another process of the instrument reliability testing method provided in the embodiments of this application is shown;

[0062] Figure 7 A schematic diagram of the instrument detection system provided in an embodiment of this application is shown;

[0063] Figure 8 A schematic diagram of the structure of an electronic device provided in an embodiment of this application is shown.

[0064] Explanation of key component symbols:

[0065] 700 - Instrument reliability testing system; 710 - First acquisition module; 720 - Second acquisition module; 730 - First determination module; 740 - Second determination module; 800 - Electronic equipment; 801 - Transceiver; 802 - Processor; 803 - Memory. Detailed Implementation

[0066] Embodiments of the present invention are described in detail below. Examples of these embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals denote 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 invention, and should not be construed as limiting the present invention.

[0067] Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature. In the description of this invention, "a plurality of" means two or more, unless otherwise explicitly specified.

[0068] 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 this application belongs. The terminology used herein in the template description is for the purpose of describing particular embodiments only and is not intended to limit the invention. The term "and / or" as used herein includes any and all combinations of one or more of the associated listed items.

[0069] Example 1

[0070] In the grinding process, the stability and reliability of monitoring instruments are crucial. Current technology typically requires experienced operators to periodically observe instrument data and comprehensively analyze its historical distribution and current operating conditions to evaluate the instrument's reliability. This method is inefficient and difficult to implement widely. For further information, please refer to [link to relevant documentation / reference]. Figure 1 This application provides an instrument reliability testing method, applicable to, for example... Figure 2 The grinding production line shown includes: N detection instruments, where N≥1, and the method includes: steps S110~S140.

[0071] Before introducing the instrument reliability testing method provided in the embodiments of this application, a brief introduction to the grinding production line is given below. Please refer to [link to relevant documentation]. Figure 2 The grinding production line includes: a powder ore bin, a belt scale, a ball mill, a grinding pump pool, a sand pump, and a hydrocyclone. Its workflow is as follows: ore in the powder ore bin is metered by the belt scale and fed into the ball mill. Simultaneously, the feed water to the ball mill participates in the grinding process. The slurry after grinding flows into the grinding pump pool and is then pumped to the hydrocyclone. The hydrocyclone performs classification and flotation on the slurry, returning larger particles to the ball mill for further grinding, while smaller particles are output through the flotation process. The grinding production line includes N monitoring instruments, specifically: a water flow meter installed at the feed water port of the grinding pump pool, a water flow meter installed at the feed water port before the ball mill, a feed flow meter and a feed concentration meter installed at the output port of the sand pump, and an overflow flow meter and an overflow concentration meter installed at the flotation output port of the hydrocyclone. The following describes the instrument reliability testing method provided in this application embodiment, which includes steps S110~S140.

[0072] Step S110: Obtain 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.

[0073] In this embodiment, the reliability status of the i-th detection instrument is determined according to a reliability factor, wherein the reliability factor includes at least one of the following: communication status, logic status, and numerical status, and the i-th detection strategy of the i-th detection instrument is used to determine at least one of the communication status, logic status, and numerical status.

[0074] It should be noted that the formulation of the i-th detection strategy is based on at least one type of data: first, the real-time measurement value of the i-th detection instrument itself, i.e., the instrument value; and second, the operating parameters of the linked equipment in the grinding production line that can affect the value of the i-th detection instrument. Taking a belt scale as an example, its linked equipment is the belt feeder. It can be understood that the value of the belt scale's instrument is related to the frequency of the belt feeder. The higher the frequency of the belt feeder, the higher the value of the belt scale's instrument; the lower the frequency of the belt feeder, the lower the value of the belt scale's instrument. When testing the reliability of the belt scale, the detection strategy can verify the logical rationality of the belt scale's feed rate based on the frequency change of the belt feeder, thereby determining whether the logical state of the instrument is normal.

[0075] Step S120: 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.

[0076] In this embodiment, the preset time period can be: the past 1 hour, 2 hours, etc. Within the preset time period, the i-th detection instrument continuously collects instrument values ​​at a preset frequency, and the instrument values ​​of each instrument constitute the instrument dataset of the i-th detection instrument.

[0077] Step S130: Based on the instrument dataset of the i-th detection instrument and the i-th detection strategy, determine the reliability evaluation factor of the i-th detection instrument. The reliability evaluation factor includes at least one of the following: communication status, logic status, and numerical status.

[0078] In this embodiment, by analyzing the numerical values, variation patterns, and logical correlations between the instrument data and the operating parameters of the linked equipment, reliability evaluation factors for the detection instruments are determined. The reliability evaluation factors include at least one or more of the following: communication status, logical status, and numerical status.

[0079] In one embodiment, the i-th detection strategy is determined based on the meter value of the i-th detection instrument; see [link to relevant documentation]. Figure 3 Based on the instrument dataset of the i-th detection instrument and the i-th detection strategy, the communication status of the i-th detection instrument is determined, including steps S301 to S305.

[0080] Step S301: Determine whether each of the instrument values ​​in the instrument dataset belongs to the i-th preset range.

[0081] It is understandable that, for multiple instrument values ​​in the instrument dataset of the i-th detection instrument, it is determined whether each instrument value falls within the i-th preset range of the i-th detection instrument. For example, taking a feed flow meter as an example, the preset range of the feed flow meter is 0~1000m³ / h. This step verifies the rationality of the instrument value of the i-th detection instrument and preliminarily determines the communication status of the i-th detection instrument. If it exceeds the preset range, the communication status of the i-th detection instrument is determined to be abnormal.

[0082] Step S302: If not, then determine the communication status of the i-th detection instrument as: abnormal status.

[0083] It is understandable that a normally functioning measuring instrument should always be within a physically feasible preset range. Values ​​exceeding the range are usually caused by communication terminal errors, data transmission errors, or instrument hardware failures.

[0084] Step S303: If yes, then determine whether there is a first sub-time period that satisfies the following conditions: whether the multiple instrument values ​​collected within 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.

[0085] In this embodiment, if all instrument values ​​are within a preset range, the instrument data set is further analyzed to see if multiple instrument values ​​belonging to the first sub-time period are identical. If so, it proves that the instrument value exceeds the first preset time threshold and remains unchanged. At this point, the communication status of the i-th detection instrument can be determined as an abnormal state. This step is understood to determine whether the i-th detection instrument is continuously updating, avoiding data freezing due to communication link interruptions.

[0086] Step S304: If it exists, then determine that the communication status of the i-th detection instrument is: abnormal status.

[0087] It is understandable that normally functioning testing instruments should update in real time as process parameters change. If the value of the i-th testing instrument does not change for a long time during normal production, then the communication status of the i-th testing instrument is determined to be abnormal.

[0088] Step S305: If it does not exist, then determine the communication status of the i-th detection instrument as: normal status.

[0089] If no first sub-time period meeting the conditions is found (i.e., all instrument values ​​fluctuate normally within the preset time period, or even if there are short periods of instability, the duration does not exceed the first preset threshold), then the communication status of the i-th detection instrument is determined to be: normal. This means that the instrument values ​​are within a reasonable range and can be updated in real time with process changes, and the communication link is working normally.

[0090] In one embodiment, the i-th detection strategy is determined based on the operating parameters of the linkage device; please refer to [link to relevant documentation]. Figure 4 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 steps S401 to S403.

[0091] S401, 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.

[0092] In this embodiment, the linkage device is the device in the grinding production line that affects the value of the i-th measuring instrument. Taking a belt scale as an example, the linkage device of the belt scale is a belt feeder; taking a water flow meter as an example, the linkage device of the water flow meter is a valve; taking a feed concentration meter and an overflow concentration meter as examples, the linkage device of the feed concentration meter and the overflow concentration meter is a ball mill; taking a feed flow meter and an overflow flow meter as examples, the linkage device of the feed flow meter and the overflow flow meter is a hydrocyclone.

[0093] 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.

[0094] 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.

[0095] 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.

[0096] 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.

[0097] 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.

[0098] 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.

[0099] 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.

[0100] 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:

[0101]

[0102] or,

[0103] 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.

[0104] 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:

[0105]

[0106] or,

[0107] 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.

[0108] 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:

[0109]

[0110] or,

[0111] 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.

[0112] 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:

[0113]

[0114] or,

[0115] 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.

[0116] 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;

[0117] 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 5 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 S501 to S504.

[0118] Step S501: Obtain the dry ore density, and determine the overflow density based on the dry ore density and the overflow concentration.

[0119] 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:

[0120]

[0121] in, Indicates the density of dry ore. Indicates the overflow concentration. This indicates the overflow density.

[0122] Step S502: Determine the overflow mass based on the overflow density and the overflow flow rate.

[0123] Calculate the overflow mass using the following formula:

[0124]

[0125] in, Indicates the overflow quality. This indicates the overflow flow rate.

[0126] Step S503: Determine the amount of overflow solids based on the overflow mass and the overflow concentration.

[0127] The amount of overflow solids is determined using the following formula:

[0128]

[0129] in, This indicates the amount of solids overflowing.

[0130] 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.

[0131] 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.

[0132] 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.

[0133] 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 6The 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.

[0134] 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.

[0135] Step S601: Determine the feed density based on the dry ore density and the feed concentration.

[0136] 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:

[0137]

[0138] in, , .

[0139] Step S602: Determine the feed quality based on the feed density and the feed flow rate.

[0140] Calculate the feed mass using the following formula:

[0141]

[0142] in, Indicates the quality of the ore supplied. This indicates the flow rate to the ore deposited.

[0143] Step S603: Determine the sedimentation mass based on the ore feed mass and the overflow mass.

[0144] Calculate the mass of settled sand using the following formula:

[0145]

[0146] in, Indicates the mass of sediment.

[0147] Step S604: Determine the amount of solids in the feed based on the feed quality and the feed concentration.

[0148] Calculate the amount of solids in the feed using the following formula:

[0149]

[0150] in, This indicates the amount of solids fed into the ore.

[0151] Step S605: Determine the amount of settled sand solids based on the amount of ore fed solids and the amount of overflow solids.

[0152] Calculate the amount of solid sediment using the following formula:

[0153]

[0154] in, This indicates the amount of solid sediment.

[0155] Step S606: Determine the ratio of the amount of settled solids to the amount of overflow solids as the actual ratio.

[0156] The actual ratio is determined using the following formula:

[0157]

[0158] in, This represents the actual ratio.

[0159] Step S607: The ratio of the amount of solid sediment to the mass of sediment is determined as the sediment concentration.

[0160] The sediment concentration is determined using the following formula:

[0161]

[0162] Where C represents the sediment concentration.

[0163] 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.

[0164] when At that time, the value status of the feed flow meter was determined to be: abnormal state.

[0165] 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.

[0166] Reliability evaluation factors include at least one of the following: communication status, logic status, and numerical status.

[0167] 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.

[0168] 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.

[0169] 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.

[0170] 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.

[0171] 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.

[0172] 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.

[0173] 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.

[0174] 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.

[0175] 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.

[0176] 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.

[0177] Example 2

[0178] In addition, please see Figure 7 This application also provides an instrument reliability testing system 700, comprising:

[0179] 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.

[0180] 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;

[0181] 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.

[0182] 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.

[0183] 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.

[0184] 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.

[0185] Example 3

[0186] 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.

[0187] 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.

[0188] 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.

[0189] 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.

[0190] Example 4

[0191] 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.

[0192] 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.

[0193] 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.

[0194] 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.

[0195] 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.

[0196] 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, the reliability evaluation factor of the i-th detection instrument is determined, and the reliability evaluation factor includes: communication status and logic 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; 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.

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 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.

4. The instrument reliability testing method according to claim 3, 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 solids fed into the ore and the amount of solids overflowed. 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.

5. The instrument reliability testing method according to claim 1, characterized in that, Determining the reliability status of the i-th detection instrument based on the reliability evaluation factor 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.

6. The instrument reliability testing method according to claim 4, 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 feed flow rate. The feed flow rate is adjusted based on the deviation value.

7. 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: communication status and logic 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; 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.

8. 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 1-6.

9. 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 1-6.

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