Multi-state operation threshold setting method, monitoring method and monitoring system of device

Abstract

The present application relates to the technical field of device monitoring, and relates to a device multi-working state running threshold setting method, a device multi-working state running threshold monitoring method, and a device multi-working state running threshold monitoring system.The method comprises the following steps: S3, finding a target threshold; according to the target threshold, executing step S4 or S5; S4, executing a first verification process; if the verification is passed, setting the device to run according to the original threshold as a running threshold; S5, setting the obtained target threshold as a running threshold; the device has multiple working states, and the device has multiple original thresholds corresponding to each working state; in S3, the target threshold has a corresponding relationship with the original threshold; when S4 is executed, the target threshold and each corresponding original threshold are verified by the first verification process; when S5 is executed, the target threshold replaces each corresponding original threshold as a running threshold; through the application of the device running threshold setting method, the set running threshold has the characteristic of high reliability, and the monitoring and verification of the monitoring system on the production state of the device is accurate.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of device monitoring, in particular to a multi-state running threshold setting method and monitoring method, monitoring system of device. BACKGROUND

[0002] Currently, the threshold for determining whether the production line of a pollution discharge unit is in a production state mainly relies on the power provided by the pollution discharge unit during device production. Once the on-site monitoring power is greater than or equal to the set threshold, it is determined to be on, otherwise it is determined to be off. In fact, the pollution discharge unit generally provides the threshold based on the electrical nameplate, but there is often a gap in actual use, which affects the supervision results.

[0003] Secondly, the on-site working condition is complex, and the equipment of the pollution discharge unit may have multiple working conditions. For some standby and heat preservation devices, turning on the device is not in a production state, and it is difficult to determine whether the pollution discharge unit is really producing pollution. In addition, with the increase of use time, the equipment of the pollution discharge unit will age to some extent after a long time of work, and the energy consumption, power and other factors will increase, and the continuous availability of the threshold cannot be guaranteed.

[0004] Currently, whether the threshold provided for the pollution discharge unit conforms to the actual situation on site is mainly found by technical manual verification during project operation, which has high requirements on the professional level, data sensitivity and business of technical personnel. However, in the case of a large number of pollution discharge units and equipment, manual verification negligence is difficult to avoid.

[0005] The main difficulties encountered in the current production state determination threshold are:

[0006] (1) The collection of threshold values requires the cooperation of pollution discharge units to some extent. If the pollution discharge unit has the idea of avoiding monitoring, there may be false reporting of power threshold values, which may lead to situations where the pollution discharge unit is in pollution production but the online monitoring does not match the on-site situation, and so on, which may affect the control of the pollution discharge unit by the environmental protection department.

[0007] (2) The on-site production working condition is complex, and the production equipment is not necessarily in a pollution production state. The threshold values collected in the early stage are more of the threshold values of the device opening state, and it is necessary to find a scientific threshold value for the production equipment pollution production state.

[0008] (3) The professional level of the technical personnel for threshold review has certain requirements, which requires professional knowledge, high data sensitivity, and familiarity with business. Therefore, a large amount of energy and resources need to be invested in professional and business training in the early stage.

[0009] (4) When the sample size is small, manual verification of the threshold may be very effective in a short period of time. However, with the full coverage of online monitoring and the increase in the number of sewage discharge units, a lot of manpower and time costs are required for secondary verification. However, manual verification is not foolproof. Once there is an omission or oversight, it will affect the regulatory authorities' judgment on the status of sewage discharge units.

[0010] (5) As time goes by, production equipment ages, energy consumption and power increase, and the continuous availability of thresholds is difficult to guarantee. If the historical experience value obtained deviates from the current actual situation, it will also affect the later supervision, and the labor cost will also increase. Summary of the Invention

[0011] In view of the current situation of full-process monitoring of sewage discharge equipment, it is necessary to provide a complete method for setting equipment operating thresholds, identify the boundary between the equipment's production status operating data and non-production status operating data, thereby clarifying its scientific and reasonable operating thresholds and accurately verifying them to ensure the accuracy of the equipment's operating threshold settings.

[0012] Therefore, the purpose of this invention is to provide a method for setting the operating threshold of a device, and at the same time, to provide a monitoring method and a monitoring system to meet the application requirements of the monitoring system for monitoring the status of working equipment, especially sewage discharge equipment.

[0013] A method for setting multi-state operating thresholds for equipment includes the following steps: S1, acquiring equipment operating data; S2, clustering the operating data using a classification algorithm; S3, finding the target threshold using a cyclic binary search method; and then executing step S4 or S5 based on the obtained target threshold. Specifically: S4, executing a first verification process to check the reliability of the original equipment threshold using the obtained target threshold; if the verification passes, setting the equipment operating threshold according to the original threshold; and S5, setting the equipment operating threshold using the obtained target threshold.

[0014] When the number of obtained target thresholds is no less than two:

[0015] First, the device has multiple operating states, and the device has multiple default thresholds corresponding to each operating state. In step S3, the obtained target thresholds are correlated with the default thresholds of the device's operating states. When step S4 is executed, one or more obtained target thresholds and the corresponding one or more default thresholds of each operating state are verified for reliability using a first verification process. When step S5 is executed, the obtained one or more target thresholds replace the corresponding one or more default thresholds of each operating state as the device's operating threshold settings.

[0016] For the application of the device with multiple working states, the corresponding different state monitoring will be provided with multiple original set thresholds corresponding to each working state; therefore, based on the correspondence between the obtained target threshold and each original set threshold in each working state of the device, the different case running threshold settings of multiple working states in the device can be selected according to actual needs by executing step S4 or S5, which meets the requirement of running threshold setting in actual application.

[0017] Secondly, the device has multiple working state cases; in step S3, the obtained target threshold has a corresponding relationship with each working state case of the device; according to the running data of the target working state, the running threshold selection range is preset, when step S4 is executed, the obtained target threshold in the running threshold selection range is selected to perform the first verification process of the reliability verification of the original set threshold of the device; when step S5 is executed, the obtained target threshold in the running threshold selection range is selected as the running threshold setting of the device.

[0018] According to the setting of the running threshold in the device, the device can be further associated with the corresponding monitoring system; when the device is in the corresponding working state and generates specific running data, the corresponding running threshold setting can effectively confirm the current working state of the device by the monitoring system, thereby effectively monitoring the specific working state of the device.

[0019] Further, in step S1, the obtained running data is cleaned.

[0020] Further, in step S4, if the first verification process fails, a second verification process of the reliability verification of the obtained target threshold is executed; if the second verification process passes, the obtained target threshold is set as the running threshold of the device; if the second verification process fails, the device is marked for processing.

[0021] Further, in step S5, a second verification process of the reliability verification of the obtained target threshold is executed; if the verification passes, the obtained target threshold is set as the running threshold of the device.

[0022] Further, the first verification process includes: verifying the first deviation rate of the obtained target threshold and the original set threshold of the device, when the obtained first deviation rate is less than the first preset deviation value, it is determined that the verification passes; the setting range of the first preset deviation value is 8% to 12%.

[0023] Furthermore, the first verification process includes: statistically comparing the judgment result of the obtained target threshold on the operating data with the judgment result of the original threshold of the device on the operating data to obtain a third deviation rate; when the obtained third deviation rate is less than a third preset deviation value, it is determined that the verification is passed; the setting range of the third preset deviation value is 8% to 12%.

[0024] Furthermore, the second verification process includes: verifying the obtained target threshold and the real-time operating data of the device with a second deviation rate; when the obtained second deviation rate is less than a second preset deviation value, the verification is deemed to have passed; the setting range of the second preset deviation value is 8% to 12%.

[0025] Furthermore, the second verification process includes: under the fixed working state of the device, acquiring the real-time operating data of the device within a unit time period, calculating the proportion of the real-time operating data of the device within the unit time period that is greater than the obtained target threshold relative to the real-time operating data of the device within the unit time period, and determining that the verification is passed when the proportion is greater than the verification ratio value; the setting range of the verification ratio value is 85% to 95%.

[0026] Furthermore, the operating data includes the device's historical operating power data, historical operating current data, real-time operating power data, or real-time operating current data.

[0027] Further, in steps S2 to S3, the target threshold calculation process is as follows: S2-1, cluster the obtained running data, and denote the number of cluster centers as k; S2-2, determine the case of k; when k = 2, execute the following step: S2-2-1, denote i = 1, and the cluster center is A. i and A i+1 Then execute S2-3; S2-3, with A i and A i+1 Using the boundary as the boundary, we obtain set D. i S3-1. Use the bisection method on set D. i To perform equal-width partitioning, the specific operation is to take A. i and A i+1 The mean (A) i +A i+1 ) / 2 pairs of D i By performing equal-width partitioning, we obtain two sets with intervals [A and [B]. i , (A i +A i+1 ) / 2), [(A i +A i+1 ) / 2, A i+1 Compare the data sizes of the two sets and obtain the set D with the smaller data size. mi S3-2, Determine Dmi whether the data amount is less than D i a preset data ratio of the data amount; when D mi the data amount is less than D i a preset data ratio of the data amount, S3-3 is executed; when D mi the data amount is not less than D i a preset data ratio of the data amount, D mi is outputted, D i i is set as D m i, and then the execution of S3-1 is returned; S3-3, the average a mi of the maximum value and the minimum value in the set D i is calculated, and the obtained a i is the target threshold value.

[0028] Further, when k is greater than 2, the following steps are executed in S2-2: S2-2-2, initializing i = 1; S2-2-3, selecting the i th and the i + 1 th clustering centers A i and A i+1 ; and then S2-3 is executed; after S3-3 is executed, when k is greater than 2, S6 is executed; S6, judging whether i + 1 is less than k; when i + 1 is less than k, i = i + 1 is set, and then the execution of S2-2-3 is returned; when i + 1 is not less than k, the target threshold value is obtained.

[0029] Further, when k is greater than 2, the number of the obtained target threshold values is not less than two; there is a preset screening standard, and the obtained target threshold values are screened according to the screening standard, and the screened target threshold values are used as the execution basis of S4 or S5.

[0030] Further, the preset data ratio is set in the range of 8% to 12%.

[0031] For the case that the corresponding verification process in the above process does not pass, without other instructions, in actual application, the device is usually marked, and the marked device is re-verified one by one in the subsequent process. The re-verification process can be processed by experienced engineers or verified by other system programs.

[0032] A device monitoring method, which sets the running threshold value of the device by using the running threshold value setting method described above, and monitors the device by using a monitoring system; the monitoring system compares the obtained running data with the running threshold value of the device, and makes a judgment; when the obtained running data of the device is not less than the set running threshold value, the judgment result is that the working state is opened; when the obtained running data of the device is less than the set running threshold value, the judgment result is that the working state is closed.

[0033] The monitoring system of the device comprises a plurality of devices and a monitoring device, the monitoring device is in communication connection with each of the devices; the monitoring system applies the monitoring method to monitor the device; when the running data of the device obtained by monitoring is not less than the running threshold of the set production working state, the research result is that the production working state is opened, and the device is in a production state; when the running data of the device obtained by monitoring is less than the running threshold of the set production working state, the research result is that the production working state is closed, and the device is in a non-production state.

[0034] The beneficial effects of the present application are that:

[0035] 1. By applying the running threshold setting method, the set running threshold has high reliability, the monitored device has high reliability, the monitoring system can accurately monitor and verify the production state of the device, and manual confirmation and investigation of a large number of devices by monitoring auditors are not required, thereby effectively saving manpower and resources.

[0036] 2. By setting different verification processes in multiple stages, the target threshold and the original threshold can be reliably applied as the running threshold of the device, and the deviation of the running threshold of the device can be avoided.

[0037] 3. The running threshold setting method can effectively distinguish and identify the working state of different devices in different processes and different industries in the monitoring process of the monitoring system, and can make targeted monitoring and research and judgment operations, which is helpful for the supervisor to accurately control the working state of the monitored device; and can especially solve the problem that the pollution production of the pollution discharge unit is difficult to confirm in the existing pollution supervision field. BRIEF DESCRIPTION OF DRAWINGS

[0038] Figure 1 The real-time power trend chart for the paint spraying equipment in the automotive repair industry;

[0039] Figure 2 The real-time power scatter plot of the paint spraying equipment;

[0040] Figure 3 The violin plot of the clustering result of the power data of the paint spraying equipment;

[0041] Figure 4 The violin plot of the threshold division of the power data of the paint spraying equipment;

[0042] Figure 5 The result chart of the threshold division of the power data of the paint spraying equipment;

[0043] Figure 6 The flowchart of the target threshold obtaining method of embodiment 1 of the present application;

[0044] Figure 7 The check flow chart for the first check flow of the embodiment 2 of the present application;

[0045] Figure 8 The check flow chart for the second check flow of the embodiment 3 of the present application;

[0046] Figure 9 The check flow chart for the second check flow of the embodiment 4 of the present application;

[0047] Figure 10 The check flow chart for the first check flow of the embodiment 5 of the present application;

[0048] Figure 11 The real-time power state trend chart of the equipment when the original threshold is inappropriate;

[0049] Figure 12 The power situation schematic diagram of the injection molding equipment in different working states;

[0050] Figure 13 The flow chart of the multi-target threshold obtaining method of the embodiment 6 of the present application;

[0051] Figure 14 The violin chart of the injection molding equipment power data clustering result;

[0052] Figure 15 The violin chart of the injection molding equipment power data threshold division;

[0053] Figure 16 The injection molding equipment power data threshold division result chart;

[0054] Figure 17 The injection molding equipment current data clustering violin chart of the embodiment 7 of the present application;

[0055] Figure 18 The injection molding equipment current data threshold division violin chart of the embodiment 7 of the present application. DETAILED DESCRIPTION

[0056] In order to make the technical solutions, objectives and advantages of the present application clearer, the following further explains and describes the present application in combination with the drawings and embodiments.

[0057] Embodiment 1:

[0058] The present application provides a kind of monitoring system of equipment, the monitoring system includes several equipment and monitoring device, the monitoring device is connected with each described equipment, so that monitoring device realizes the data acquisition and monitoring research of each equipment;The monitoring system applies a kind of equipment monitoring method in it, by setting the running threshold of equipment, and according to the comparison of monitoring obtained running data and running threshold, so that the monitoring system can carry out research and judge operation to the working state of equipment.

[0059] The monitoring method for this device first sets an operating threshold for the device, and then monitors the device with the set operating threshold. The monitoring system compares the obtained operating data with the device's operating threshold and makes a judgment; when the monitored operating data is not less than the set operating threshold, the judgment result is that the device is in operation; when the monitored operating data is less than the set operating threshold, the judgment result is that the device is in operation.

[0060] Specifically, the equipment monitoring system is a monitoring system for sewage discharge equipment to monitor whether the sewage discharge equipment is actually in a sewage-generating state; when the monitored operating data of the sewage discharge equipment is not less than the operating threshold of the sewage-generating working state, it is judged that the sewage-generating working state is turned on, that is, the sewage discharge equipment is in a sewage-generating production state; when the monitored operating data of the equipment is less than the operating threshold of the sewage-generating working state, it is judged that the sewage-generating working state is turned off, and the sewage discharge equipment is in a non-production state.

[0061] Taking the power operation data of production equipment in the production line of a pollution discharge unit as an example to determine whether the working status is polluting, this invention provides a method for obtaining a target threshold, which can be used to obtain the power target threshold of the production equipment.

[0062] The specific application settings for determining this target threshold are as follows:

[0063] Step 1: Acquisition and cleaning of equipment operation data.

[0064] The system acquires equipment power operation data and corresponding working status data, forming a dataset for production equipment monitoring with a periodic sampling frequency of 5 minutes. After the power operation data recorded in these 5 minutes is input into the system, the system will automatically perform data cleaning processing to remove outliers, such as removing records with negative power values.

[0065] Step 2: Automatic clustering using classification algorithms.

[0066] The power distribution of production equipment in wastewater discharge units exhibits characteristics during both operation and non-operation: for example, during operation, power values ​​fluctuate within a certain range. Therefore, based on the data distribution, the data can be divided into intervals.

[0067] like Figures 1 to 3 As shown. Taking paint spraying equipment in the auto repair industry as an example, under normal circumstances, the original power threshold set on site is 0.2KW. Once the real-time power is not less than 0.2KW, the corresponding switching conversion is judged to be turned on. From the data, it is not difficult to find that its power is mostly distributed around (0,0.5) and (3,5).

[0068] In the figure, state switch value 1 represents the device is on, and 0 represents the device is off.

[0069] From the actual business point of view, the unit power during non-production fluctuates around 0.4 KW due to the influence of other lighting devices, so the power data is not 0, which leads to the possibility of misjudgment of the state in the non-production situation. In fact, the normal production situation of the device fluctuates between (3, 5), so we find a value between (0.4, 3) as the boundary between production and non-production.

[0070] In the classification algorithm, high-density areas separated by low-density areas are found in the data set, and the separated high-density areas are taken as an independent class. Suppose there are many points around point x, denoted as x1, x2…x j , we calculate the movement of point x to each point x j around it. The sum of the required offsets is averaged to obtain the average offset. In addition to the size, the offset also contains the direction of the surrounding dense distribution. In the next step, point x moves in the direction of the average offset, and this is taken as a new starting point, and the iteration is continuously performed until a certain condition is met.

[0071] The general process is as follows:

[0072] 1) Randomly select a point in the data set as the starting center point S;

[0073] 2) Take S as the center and r as the radius, find all data points in the region, and consider these points to belong to the same cluster C. At the same time, record the number of data points appearing in the cluster as 1;

[0074] 3) Take S as the center point, calculate the vector from S to each element in the data set, and add it to get the vector s;

[0075] 4) S=S+s, that is, S moves in the direction of s, and the moving distance is ||s||;

[0076] 5) Repeat steps 2), 3), and 4) until s is small, and record S at this time. At this time, all the points encountered in this iteration process should be classified into cluster C;

[0077] 6) If the distance between the current cluster C and the center of the existing cluster C2 is less than the set threshold (the set threshold is determined by the data set, which is the 50% quantile of the distance set of any pair of samples in the data set), then C2 and C are merged, and the data point occurrence frequency is also merged. Otherwise, C is taken as a new cluster;

[0078] 7) Repeat steps 1) to 5) until all points are marked as visited;

[0079] 8) Classification: According to each class, the access frequency of each point, take the access frequency of the largest class as the class to which the current point set belongs.

[0080] As Figure 3 shown, based on the application of the paint spraying equipment in the automotive repair industry, it can be seen that the results of the pollution unit have two categories, and the first and second cluster centers are 0.05 and 3.94, respectively.

[0081] Step 3: Find the appropriate power target threshold by binary search.

[0082] As Figures 4 to 5 shown, based on the cluster center results obtained in the previous step, take the two cluster centers A1 and A2 as boundary conditions, and propose all data in this interval as data set D. Use binary search to divide D into two equal-width data sets D1 and D2. Take the preset data proportion value as 8% to 12%, preferably 10%. Compare D1 and D2, and take the one with smaller data volume as D m , if the data volume of D m is less than (D1+D2)*10%, take the average of the maximum and minimum values of this data as the target threshold, if the data volume of D m is greater than (D1+D2)*10%, further divide D m by binary search until a data set D m with a data volume less than (D1+D2)*10% is found, and take the average of the maximum and minimum values of this data as the power target threshold.

[0083] Use binary search to divide the power data between the two cluster centers obtained by the classification algorithm of the paint spraying equipment in the automotive repair industry into two equal-width parts, and select the one with the smallest data volume as D m . At this time, the data volume of the one with the smallest data volume accounts for less than 10% of the total data volume of D1 and D2. Based on D m , find the average of the maximum and minimum values a, and output the average value a as the power target threshold of the equipment, which is 2.23KW. Obviously, the numerical application of the obtained power target threshold 2.23KW can better divide the production and non-production situations than the original power original threshold 0.2KW of the equipment.

[0084] The flow of the steps of the above-mentioned target threshold finding method of the equipment is as follows:

[0085] S1, obtain the running data of the equipment;

[0086] S2, cluster the running data by a classification algorithm;

[0087] S3, find the target threshold by binary search.

[0088] According to the obtained target threshold value, as a preferred application mode of the target threshold value, the target threshold value can be selected as the running threshold value of the equipment.

[0089] Based on the obtained power target threshold value 2.23KW, the original threshold value 0.2KW of the original equipment is replaced, and the power running threshold value of the actual production working state of the equipment is changed; that is, when the real-time power of the paint spraying equipment is not less than 2.23KW, the corresponding switch conversion amount is determined to be turned on. The monitoring system accurately and effectively monitors the actual production working state of the equipment.

[0090] The above-mentioned target threshold value obtaining method can obtain the power target threshold value of the equipment from the actual production environment of the equipment based on the actual running data of the equipment. The obtained corresponding target threshold value can have more accurate characteristics relative to the original threshold value of the factory. The obtaining and application of the above-mentioned target threshold value obtaining method are shown in the flowchart of Figure 6 .

[0091] The running threshold value setting method of the equipment of the present application can select the obtained target threshold value to replace the original threshold value of the equipment to directly serve as the running threshold value of the equipment. Based on the adjustment and setting of the running threshold value, the accurate judgment demand of the monitoring system for the working state of the equipment can be met.

[0092] In the above-mentioned obtaining and calculation of the running data of the equipment, real-time running power data of the equipment in real time or historical running power data of the equipment in the past can be selected for application according to actual demand.

[0093] Specifically, the specific obtaining process of the above-mentioned power target threshold value is as follows:

[0094] S2-1, clustering the obtained running data, and recording the number of clustering centers as k;

[0095] S2-2, judging the condition of k; in the case of a single working state, two clustering centers will be generated;

[0096] When k=2, the following step is performed: S2-2-1, recording i=1, and the clustering centers are A i and A i+1 ; and then S2-3 is performed;

[0097] S2-3, taking A i and A i+1 as the boundary to obtain the set D i ;

[0098] S3-1, dividing the set D i by using the bisection method, and the specific operation is to take A i and A i+1The mean (A) i +A i+1 ) / 2 pairs of D i By performing equal-width partitioning, we obtain two sets with intervals [A and [B]. i , (A i +A i+1 ) / 2), [(A i +A i+1 ) / 2, A i+1 Compare the data sizes of the two sets and obtain the set D with the smaller data size. mi ;

[0099] S3-2, Determine D mi Whether the amount of data is less than the preset data ratio of the Di data amount, wherein the preset data ratio is set in the range of 8% to 12%;

[0100] When D mi The amount of data is less than D i When the preset data ratio is used, execute S3-3;

[0101] When D mi The amount of data is not less than D i When the preset data ratio is used, the output D is... mi , making D i =D mi Then return to execute S3-1;

[0102] S3-3, Calculate D mi The average of the maximum and minimum values ​​in the set, a i The result is a i The target threshold.

[0103] Example 2:

[0104] Based on the target threshold determination method of Embodiment 1 above, another preferred application of this solution is as follows: Given that the target threshold obtained by the algorithm is reliable, the original threshold of the device is verified using a first verification process through the obtained target threshold, thereby determining whether the original threshold of the device is reliable. The application of this first verification process is described in reference to... Figure 7 As shown.

[0105] Based on the foregoing, the running threshold of the production equipment is not a fixed value, but fluctuates in an interval, so we can well divide the on-off state as long as we find a value in this interval; Assuming that the original set threshold is in the threshold interval of the running threshold, since the target threshold obtained by the algorithm is also in the threshold interval of the running threshold, the state result deviation rate of the original set threshold and the state result deviation rate of the target threshold will be basically small at this time, but if the original set threshold is not in the threshold interval, the state result of the target threshold and the state result of the original set threshold will produce a certain deviation. Therefore, if the numerical difference between the target threshold and the original set threshold of the equipment is within a reasonable range, it can be considered that the original set threshold of the equipment is reliable. This is the basic setting idea of the scheme.

[0106] In the case of confirming that the original set threshold of the equipment is reliable, the original set threshold of the equipment will continue to be used as the running threshold of the equipment, so as to ensure the accurate application premise of the monitoring work and reduce the operation process.

[0107] The first verification process can be selected to include: verifying the first deviation rate of the obtained target threshold and the original set threshold of the equipment, and when the obtained first deviation rate is less than the first preset deviation value, it is determined that the verification is passed. The value range of the first preset deviation value is 8-12%, and it is preferably set to 10%.

[0108] Taking the application of the paint spraying equipment in the above-mentioned automobile repair industry as an example: if the original set threshold set by the equipment is 2KW, when the first preset deviation value is 12%, the theoretical selection range of the target threshold of the original set threshold is between 1.76KW and 2.24KW; Therefore, in the case that the obtained target threshold is 2.23KW, it can be considered that the setting of the original set threshold is reliable. Therefore, the paint spraying equipment can continue to use 2KW as the running threshold, and the monitoring device can continuously monitor the production working state at 2KW.

[0109] The setting steps of the above-mentioned first verification process are as follows:

[0110] S4-1, comparing the obtained target threshold with the original set threshold of the equipment, and calculating the first deviation rate;

[0111] S4-2, determining whether the first deviation rate is less than the first preset deviation value;

[0112] When the first deviation rate is less than the first preset deviation value, the verification of the first verification process is passed.

[0113] Therefore, the operation threshold setting method of the device of the present application can select to execute the first verification process to verify the reliability of the original set threshold of the device with the obtained target threshold. If the verification is passed, the device continues to set the original set threshold as its own operation threshold, which meets the accurate judgment demand of the monitoring system for the working state monitoring of the device.

[0114] Embodiment 3:

[0115] In order to avoid the deviation of the obtained target threshold caused by other conditions (such as the data packet loss of the obtained running data), the second verification process can be used to verify the reliability of the obtained target threshold. When the obtained target threshold passes the verification, the obtained target threshold is set as the operation threshold of the device or as the reliability verification reference of the original set threshold of the device. The application of the second verification process is shown in the following figure. Figure 8

[0116] The second verification process can select to include the verification of the second deviation rate between the obtained target threshold and the real-time running data of the device. When the obtained second deviation rate is less than the second preset deviation value, it is determined that the verification is passed. The value range of the second preset deviation value is 8-12%, and it is preferably set to 10%.

[0117] Specifically, taking the application of the above-mentioned paint spraying device in the automotive repair industry as an example, the real-time running data can be the average power data within the periodic sampling time (5 min) of the device in the target working state.

[0118] For example, if the target threshold in the pollution production working state is required, the running data of the device within the periodic time period is collected in the clear pollution production working state (confirmed by manual confirmation or comprehensive analysis), and the average value is obtained. For example, in the above-mentioned paint spraying device, the real-time running data of the obtained average value in the pollution production working state is 2.5 KW, the second preset deviation value is set to 12%, the obtained target threshold is 2.23 KW, the second deviation rate between the obtained target threshold and the real-time running data of the device is less than the second preset deviation value, and it is determined that the verification is passed.

[0119] ​In the application premise of the above embodiment 2, if the first verification process is not passed, there is a possibility that the target threshold is incorrect or the original set threshold and the target threshold are greatly deviated (the target threshold is reasonable). Therefore, the second verification process for the reliability of the target threshold is performed. If the second verification process is passed, it is judged that the original set threshold and the target threshold are greatly deviated, and the target threshold is reasonable, so that the target threshold can be set as the running threshold of the equipment. If the second verification process is not passed, the target threshold is incorrect, and the equipment needs to be marked for subsequent inspection.

[0120] Embodiment 4:

[0121] Based on the application of the above embodiment 3, the embodiment 3 is further explained in the preferred setting mode.

[0122] The second verification process in the above embodiment 3 can be changed to: in the fixed working state of the equipment, the real-time running data of the equipment in a unit time period is obtained, the proportion of the data greater than the target threshold in the real-time running data of the equipment in the unit time period is calculated, and when the proportion is greater than the verification proportion value, it is considered that the setting of the target threshold is reliable, and the verification is passed. The application of the second verification process is shown in the following Figure 9 .

[0123] For example:

[0124] In the stable open working state (such as production state) of the equipment, the real-time power running data of the equipment in the open working state is compared with the target threshold in 24 hours as a unit time period. If more than 90% of the monitored power running data exceeds the target threshold in 24 hours, it is considered that the verification is passed, and the target threshold is reliable.

[0125] Embodiment 5:

[0126] Based on the application of the above embodiments, the embodiment is further explained in the preferred setting mode.

[0127] In the application of the above embodiments, the corresponding verification can be performed only based on the data generated by the equipment itself. In the application of the scheme of the embodiment, a simulated research and judgment action setting can be further combined, so that the corresponding verification process can be more accurate and reliable in the whole life cycle.

[0128] The first verification process of the reliability verification of the device original threshold value with the obtained target threshold value is applied as follows: the judgment results generated by the target threshold value on the operation data and the judgment results generated by the device original threshold value on the operation data are simulated, the judgment results generated by the target threshold value on the operation data are statistically compared with the judgment results generated by the device original threshold value on the operation data, and a third deviation rate is obtained; when the obtained third deviation rate is less than a third preset deviation value, it is determined that the verification is passed. The value range of the third preset deviation value is 8-12%, preferably 10%.

[0129] In actual application, after the obtained target threshold value is obtained, the corresponding judgment result situation in the corresponding operation data generation process is correspondingly counted according to the operation situation of the selected operation data (or historical operation data or real-time operation data). For the working state situation (such as the paint production working state of the paint spraying device in the above-mentioned automobile repair industry) that we need to judge, the opening situation of the paint production working state obtained after the corresponding target threshold value is set in the data sampling period (5 min) is simulated and counted, and the opening situation of the paint production working state obtained after the original threshold value is set. When the deviation rate between the number of judgment results obtained based on the target threshold value setting and the number of judgment results obtained based on the original threshold value setting is less than a third preset deviation value, it is determined that the verification is passed, and the reliability of the original threshold value is determined. The verification process application of the first verification process is shown in Figure 10 .

[0130] For example: using the obtained target threshold value as the running threshold value, the monitoring system judges the opening and closing state of the device at each monitoring time point, and then compares it with the result of the original preset value judgment. When there are 100 time points preset, the original preset value judgment is all open, but the result of the judgment using the obtained target threshold value as the running threshold value is that only 70 points are open, and the error rate reaches 30%, which has exceeded the preset deviation of 10%. Therefore, it is considered that the original threshold value is unreliable, the first verification process is not passed, and the second verification process needs to be processed or the device is marked for further confirmation by manual work.

[0131] As a real application case:

[0132] Based on the environmental protection monitoring data of the pollution discharge unit, a total of 978 production lines and about 17.5 million data are used to obtain the power running threshold value of the device by using the above algorithm, and the original threshold value of the device is verified. A total of 719 are within 10%, accounting for about 73.6%, indicating that the current state judgment of most production line devices is reasonable. A total of 259 are greater than 10%, which is determined as the first verification process of the original threshold value reliability verification not passed.

[0133] For the above first check process, the check does not pass, the target threshold reliability check can be carried out by the second check process, or directly via monitoring system or artificial way to check. After checking, 203 of 259 lines are generally the same power value, but at different times, it may be identified as different states, accounting for about 20.8% of the total; In this case, it can be considered that the data generated by the device has quality problems, and it is not considered that the target threshold accuracy problem of the scheme is solved.

[0134] In addition, 33 lines of production line power fluctuation is obvious, the identified target threshold is not 0 or even larger, and the actual state is always judged as off, accounting for about 3.4% of the total; It shows that the original preset threshold of the device is a problem, and in this case, the obtained power target threshold needs to be changed to set the original preset running threshold of the device.

[0135] As shown in Figure 11 After 8 o'clock, the device power fluctuates obviously, but the state is always off, and the original preset threshold of the device in the field is unreasonable, which may be set too high, resulting in failure to accurately identify the true state of the device. Overall, this method can check the existing state to determine whether the original preset threshold state of the device of the current pollution unit is reasonable, and the overall misjudgment rate is 2.4%, which is relatively small and has reliability.

[0136] Type Record number Proportion Passes verification 719 73.6％ Data quality has problems 203 20.7％ Unreasonable running threshold set on site (original threshold) 33 3.3％ Unsuitable running threshold calculated by algorithm (target threshold) 23 2.4％ Total number 978 100％

[0137] Example 6:

[0138] In the above examples, the working condition of the paint spraying device in the automotive repair industry is taken as an example to point out the power target threshold of the single production condition (pollution working state) device. In this embodiment, the power target threshold of the corresponding multi-condition device is further described.

[0139] As shown in Figure 12 , taking the injection molding industry as an example, its blown film process has a heating condition, and the production device has two different working conditions of heating working condition and production working condition in addition to shutdown state. In the blown film process, the heating working process will produce a certain power output, but since it does not actually produce, it will not produce waste gas. Therefore, from the perspective of environmental protection monitoring, we need to accurately find out the production working condition of the blown film process device for monitoring.

[0140] However, in actual application, the original preset threshold of the blown film process device is generally set low (or only set to more than 1KW), which may cause the monitoring system to produce a monitoring linkage alarm in the preheating state, which does not meet the actual monitoring requirements.

[0141] Therefore, for the above-mentioned application, the algorithm for calculating the target threshold in the embodiment is further supplemented:

[0142] In the case of having two working states, the obtained operation data will have three cluster centers; therefore, in step S2-2, when k is greater than 2, the following steps are performed: S2-2-2, initializing i = 1; S2-2-3, selecting the i, i+1thcluster center A i and A i+1 ; and then performing S2-3;

[0143] After step S3-3 is performed, when k is greater than 2, step S6 is performed, that is, judging whether i+1 is less than k;

[0144] When i+1 is less than k, i = i+1 is output to step S2-2-3, and the above-mentioned operation steps are sequentially repeated, and a plurality of target thresholds a i are obtained until i+1 is not less than k.

[0145] When i+1 is not less than k, all target thresholds are obtained; at this time, the number of obtained target thresholds is greater than or equal to 2.

[0146] In the embodiment, two target thresholds will be generated based on the application of three cluster centers generated in the case of having two different working states.

[0147] In the calculation process of the above-mentioned target thresholds a i , different first verification processes or second verification processes in the above-mentioned embodiments can be selected and combined for application according to different verification requirements.

[0148] The flow setting situation of the multi-target threshold calculation method is shown in Figure 13 .

[0149] As shown in Figures 14 to 16 , through the application of the above-mentioned device target threshold calculation algorithm, it can be found that the power of the injection molding production equipment fluctuates in three intervals, which respectively correspond to the shutdown concentrated interval, the preheating concentrated interval, and the production concentrated interval; at this time, two target thresholds are obtained, which are 1.6KW and 31.2KW respectively; the obtained target thresholds are not unique, and the obtained target thresholds have a corresponding relationship with the number and the value selection range of the working states of the equipment.

[0150] There is a preset screening standard, and the obtained target thresholds are screened according to the screening standard, and the screened target thresholds are used as the execution basis for the monitoring of the working state of the equipment.

[0151] First, according to actual experience, the equipment preheating state is a lower power output state, and the equipment pollution producing state is a higher power output state, and the power running data in the application of the two working states will have a significant difference; therefore, the screening standard is to divide and match the running threshold values of different working states by identifying the target threshold value with a significant difference in numerical value through big data or artificial intelligence.

[0152] Therefore, according to the screening standard, the lower power output state value 1.6KW is selected as the running threshold value of the equipment preheating state, and the higher power output state value 31.15KW is selected as the running threshold value of the equipment pollution producing state. Based on 31.15KW as the actual pollution producing state power running threshold value of the equipment, the above-mentioned first verification process and the running threshold value setting application after verification are executed, or the obtained target threshold value is used as the running threshold value setting application of the equipment, and the subsequent actual monitoring situation obtained by the monitoring system will be more in line with the actual needs.

[0153] On the other hand, the screening standard can also set the selection range of the running threshold value according to the obtained running data.

[0154] For example, in the application of a film blowing process equipment, through artificial confirmation or comprehensive analysis and confirmation of other analysis system programs, it can be known that there is a reasonable range of running data of different working states of the equipment (such as the reasonable range of preheating state power output data, and the reasonable range of equipment pollution producing state power output data, which can be set as a 10% range of the upper and lower floating of the corresponding working state running data mean); therefore, on this basis, the running threshold value of the equipment preheating state is selected in the lower range of the above-mentioned preheating state power output data, and the running threshold value of the equipment pollution producing state is selected in the lower range of the pollution producing state power output data. According to the monitoring target we need, which is the equipment pollution producing state, among the multiple target threshold values obtained by the above-mentioned algorithm, the target threshold value within the reasonable range of the above-mentioned equipment pollution producing state power output data is selected as the running threshold value setting of the equipment pollution producing state.

[0155] In different environment applications, for the simultaneous monitoring of multiple working states, the equipment will have multiple original threshold values of corresponding working states, and the equipment will obtain target threshold values through the setting method, which will have a one-to-one correspondence with the original threshold values of the working states in terms of quantity and numerical value setting range.

[0156] Therefore, among the multiple target threshold values obtained by the above-mentioned algorithm, each obtained target threshold value will have a matching relationship with the power output data reasonable range of each working state.

[0157] Accordingly, during the setting of the operating threshold, a first verification process for verifying the reliability of the original thresholds for different operating states of the equipment and / or a second verification process for verifying the reliability of each target threshold can be selected. The target thresholds that meet the verification conditions are used to set the operating thresholds for each operating state of the equipment, or the original thresholds in each operating state after verification are used as the operating thresholds of the equipment for further setting. This allows the obtained target thresholds to provide effective matching guidance with the corresponding operating state. In the application of the monitoring system, the monitoring device can set different monitoring and alarm measures for different operating threshold standards, which can meet the monitoring system's need to monitor multiple operating states of the equipment separately.

[0158] Example 7:

[0159] The descriptions of the above embodiments indicate the application of setting and monitoring operating thresholds for power operation data. This embodiment will further describe the operation, setting, and monitoring of corresponding current operation data. Figures 17 to 18 As shown, by applying the above-mentioned algorithm for determining the target threshold of the equipment, acquiring the corresponding historical current data of the painting equipment and performing algorithm calculations, it can be concluded that when the production equipment engages in pollution-generating behavior in a concentrated production area, its current operating threshold is set to the obtained target current threshold of 54.61A to classify pollution generation, which is more in line with the actual situation. In the algorithm calculation process of this embodiment, the selected operating data includes the equipment's historical operating current data or real-time operating current data.

[0160] Example 8:

[0161] Based on the application of the target threshold calculation algorithm in the above embodiments, those skilled in the art will understand that in similar application areas, such as monitoring whether there is any illegal use of electrical appliances in school dormitories, the equipment monitoring system of the present invention will also be able to accurately monitor and judge the usage status of the corresponding illegal electrical appliances, meeting the needs of other equipment monitoring applications besides sewage monitoring.

[0162] The above description is only a preferred embodiment of the present invention. For those skilled in the art, modifications can still be made to the embodiments without departing from the implementation principle of the present invention, and the corresponding modifications should also be considered within the protection scope of the present invention.

Claims

1. A method of setting a multi-state operating threshold of a device, characterized by, The method comprises the following steps: S1, obtaining operation data of the device; S2, clustering the operation data by a classification algorithm; S3, finding a target threshold value by dichotomy; According to the target threshold value, then performing step S4 or S5; S4, performing a first verification process for verifying the reliability of the device original threshold value with the target threshold value; If the verification passes, the device is set with the original threshold value as the operation threshold value; if the verification of the first verification process fails, a second verification process for verifying the reliability of the target threshold value is performed; If the second verification process passes, the target threshold value is set as the operation threshold value of the device; If the second verification process fails, the device is marked for processing; The first verification process comprises: comparing the judgment result of the target threshold value on the operation data with the judgment result of the original threshold value of the device on the operation data to obtain a third deviation rate; when the third deviation rate is less than a third preset deviation value, it is determined that the verification passes; The second verification process comprises: verifying a second deviation rate of the target threshold value and the real-time operation data of the device; when the second deviation rate is less than a second preset deviation value, it is determined that the verification passes; S5, setting the target threshold value as the operation threshold value of the device; The device has multiple working states, and the device has corresponding multiple original threshold values for each working state; in step S3, the target threshold value obtained has a corresponding relationship with the working state original threshold value of the device; When step S4 is performed, one or more target threshold values and the original threshold values of one or more corresponding working states are verified for reliability by the first verification process; When step S5 is performed, the target threshold value or more replaces the original threshold value of each working state corresponding to one or more as the operation threshold value of the device.

2. The multi-state operating threshold setting method of claim 1, wherein, In step S5, the second verification process for verifying the reliability of the target threshold value is performed; If the verification passes, the target threshold value is set as the operation threshold value of the device.

3. The multi-state operating threshold setting method of claim 1 or 2, wherein, The first verification process comprises: verifying a first deviation rate of the target threshold value and the original threshold value of the device; when the first deviation rate is less than a first preset deviation value, it is determined that the verification passes; the setting range of the first preset deviation value is 8% to 12%.

4. The multi-state operating threshold setting method of claim 1 or 2, wherein, The setting range of the third preset deviation value is 8% to 12%.

5. The multi-state operating threshold setting method of claim 1 or 2, wherein, The setting range of the second preset deviation value is 8% to 12%.

6. The multi-state operating threshold setting method of claim 1 or 2, wherein, The second verification process comprises: obtaining real-time operation data of the device in a unit time period under a fixed working state of the device, and calculating a proportion of the real-time operation data of the device greater than the target threshold value in the unit time period; when the proportion is greater than a verification proportion value, it is determined that the verification passes; the setting range of the verification proportion value is 85% to 95%.

7. The multi-state operating threshold setting method of claim 1, wherein, The operation data comprises historical operation power data or historical operation current data or real-time operation power data or real-time operation current data of the device.

8. A monitoring method, characterized in that, The method is applied to set the operation threshold of the equipment, and the monitoring system monitors the operation of the equipment; the monitoring system compares the obtained operation data with the operation threshold of the equipment, and makes a judgment; when the monitored operation data of the equipment is not less than the set operation threshold, the judgment result is that the working state is opened; when the monitored operation data of the equipment is less than the set operation threshold, the judgment result is that the working state is closed.

9. A monitoring system, characterized by The monitoring system applies the monitoring method of claim 8 to monitor the equipment; when the monitored operation data of the equipment is not less than the set operation threshold of the production working state, the judgment result is that the production working state is opened, and the equipment is in the production state; when the monitored operation data of the equipment is less than the set operation threshold of the production working state, the judgment result is that the production working state is closed, and the equipment is in the non-production state.

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