CN116184955A - Operation threshold setting method, monitoring method and monitoring system - Google Patents
Operation threshold setting method, monitoring method and monitoring system Download PDFInfo
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Abstract
The invention relates to the technical field of equipment monitoring, in particular to an operation threshold setting method, a monitoring method and a monitoring system, wherein the operation threshold setting method of equipment comprises the following steps: s1, acquiring operation data of equipment; s2, clustering the operation data through a classification algorithm; s3, finding out a target threshold value through a cyclic dichotomy; according to the obtained target threshold, then executing step S4 or S5; wherein: s4, executing a first verification process of performing reliability verification of the original threshold value of the equipment by using the obtained target threshold value; if the verification is passed, the equipment is set according to the original threshold value as an operation threshold value; s5, setting an obtained target threshold value as an operation threshold value of the equipment; by applying the method for setting the operation threshold of the equipment, the set operation threshold has the characteristic of high reliability, and the monitoring system is ensured to accurately verify the production state of the equipment.
Description
Technical Field
The invention relates to the technical field of equipment monitoring, in particular to an operation threshold setting method, a monitoring method and a monitoring system.
Background
The threshold value for judging whether the production line of the sewage unit is in a production state at present mainly depends on the power supply of the sewage unit according to the equipment production, and once the on-site monitoring power is greater than or equal to the set threshold value, the threshold value is judged to be on, otherwise the threshold value is judged to be off. In fact, the pollution discharge unit generally provides a threshold value based on the electric appliance nameplate, but a gap often exists in the actual use process, so that a certain influence is caused on the supervision result.
Secondly, the field working condition is complex, the pollution discharge unit equipment can have multiple working conditions, and for some equipment in standby and heat preservation states, the equipment is started and is not in a production state, so that whether the pollution discharge unit is producing pollution is difficult to judge. In addition, as the service time increases, the pollution discharge unit equipment can age to a certain extent after long-time working, energy consumption, power and the like can rise, and the continuous usability of the threshold value is difficult to ensure.
At present, whether the threshold value provided for the pollution discharge unit accords with the field actual condition is mainly found by technical manual verification in the project operation process, which has higher requirements on the professional level, data sensitivity and service of technicians, but the manual verification is difficult to avoid under the conditions of large quantity of the pollution discharge unit and large quantity of equipment.
The main difficulties encountered in the prior art for judging the threshold value of the production state are as follows:
(1) The collection of the threshold value has certain requirements on the coordination aggressiveness of the pollution discharge unit, and once the pollution discharge unit has the idea of avoiding monitoring, the pollution discharge unit is in pollution discharge production but the on-line monitoring is inconsistent with the on-site, and the like, the pollution discharge unit can be influenced by the environmental protection department on the control of the pollution discharge unit.
(2) The on-site production working condition is complex, the production equipment is started and is not in a pollution production state, more thresholds are collected in the early stage and are thresholds of the equipment starting state, and a scientific judgment threshold of the pollution production state of the production equipment needs to be found.
(3) The method has certain requirements on the professional level of the threshold rechecking technicians, needs to have professional knowledge, has high data sensitivity and is familiar with businesses, so that a great deal of effort and material resources are required to be invested in the early stage for professional and business training.
(4) Under the condition that the sample is small, the manual rechecking threshold value can be effective in a short time, but with the full coverage of online monitoring, under the condition that the number of pollution discharge units is increased, a large amount of manpower and time cost are required to be input for secondary checking, but the manual checking is not anyway, once omission and negligence occur, the judgment of the monitoring department on the state of the pollution discharge units can be influenced.
(5) With the increase of time, the production equipment ages, the energy consumption and the power rise, the continuous usability of the threshold value is difficult to ensure, and if the obtained historical experience value deviates from the current actual situation, the later supervision is influenced, and the labor cost is increased.
Disclosure of Invention
Aiming at the current situation of the whole process monitoring of the prior sewage disposal equipment, a complete equipment operation threshold setting method is needed to be provided, and the boundary between the production state operation data and the non-production state operation data of the equipment is found, so that the scientific and reasonable operation threshold of the equipment is further defined, and the operation threshold is accurately checked, so that the equipment operation threshold setting has accuracy.
Therefore, the invention aims to provide a method for setting the operation threshold of equipment, and simultaneously provides a monitoring method and a monitoring system so as to meet the condition supervision application requirements of the monitoring system on working equipment, particularly sewage disposal equipment.
An operation threshold setting method, comprising the steps of: s1, acquiring operation data of equipment; s2, clustering the operation data through a classification algorithm; s3, finding out a target threshold value through a cyclic dichotomy; according to the obtained target threshold, then executing step S4 or S5; wherein: s4, executing a first verification process of performing reliability verification of the original threshold value of the equipment by using the obtained target threshold value; if the verification is passed, setting the equipment according to the original threshold value as an operation threshold value; s5, setting the obtained target threshold value as an operation threshold value of the equipment.
In steps S2 to S3, the target threshold value obtaining process is as follows: s2-1, clustering the obtained operation data, and recording the number of clustering centers as k; s2-2, judging the condition of k; when k=2, the steps are performed: s2-2-1, i=1, and the clustering center is A i And A i+1 The method comprises the steps of carrying out a first treatment on the surface of the Then S2-3 is executed; s2-3, A i And A i+1 For the boundary, get set D i The method comprises the steps of carrying out a first treatment on the surface of the S3-1, pair set D by dichotomy i Dividing the same width, and taking A as a specific operation i And A i+1 Mean value (A) i +A i+1 ) 2 pairs D i Equal-width segmentation is carried out to obtain two sets, wherein the intervals of the sets are respectively [ A ] i ，(A i +A i+1 )/2)，[(A i +A i+1 )/2，A i+1 ]The method comprises the steps of carrying out a first treatment on the surface of the Comparing the data sizes of the two sets to obtain a set D with small data size mi The method comprises the steps of carrying out a first treatment on the surface of the S3-2, judge D mi Whether the data amount of (a) is smaller than D i A preset data proportion of the data amount; when D is mi The data amount of (2) is smaller than D i Executing S3-3 when the preset data proportion of the data quantity is preset; when D is mi The data amount of (2) is not less than D i Outputting D when the preset data proportion of the data quantity mi Order D i ＝D m i, and then returning to execute S3-1; s3-3, calculate D mi Mean value a of maximum and minimum values in set i The result a i Is the target threshold.
Further, in step S2-2, when k is greater than 2, the steps are performed: s2-2-2, initializing i=1; s2-2-3, selecting the ith and (i+1) th clustering centers A i And A i+1 The method comprises the steps of carrying out a first treatment on the surface of the Then S2-3 is executed; after the step S3-3 is executed, when k is greater than 2, executing a step S6; s6, judging whether i+1 is smaller than k; when i+1 is smaller than k, let i=i+1, and then return to step S2-2-3; and when i+1 is not less than k, acquiring a target threshold value.
According to the setting of the running threshold value in the equipment, the equipment and a corresponding monitoring system can be further associated; when the equipment is in the corresponding working state and generates specific operation data conditions, the corresponding operation threshold value can effectively enable the monitoring system to confirm the current working state conditions of the equipment, so that monitoring application can be effectively carried out aiming at the specific working state of the equipment.
Further, in step S1, the acquired operation data is subjected to data cleansing.
Further, in step S4, if the verification of the first verification process is not passed, a second verification process for performing reliability verification on the obtained target threshold is performed; if the second checking flow passes the checking, setting the obtained target threshold as an operation threshold of the equipment; and if the second checking flow does not pass the checking, marking the equipment.
Further, in step S5, a second verification process of verifying the reliability of the obtained target threshold is performed; and if the verification is passed, setting the obtained target threshold as the operation threshold of the equipment.
Further, the first checking procedure includes: verifying a first deviation rate of the obtained target threshold and an original threshold of the equipment, and judging that the verification is passed when the obtained first deviation rate is smaller than a first preset deviation value; the setting range of the first preset deviation value is 8% -12%.
Further, the first checking procedure includes: carrying out statistical comparison on the obtained research and judgment result generated by the target threshold value on the operation data and the research and judgment result generated by the original threshold value of the equipment on the operation data to obtain a third deviation rate; when the obtained third deviation rate is smaller than a third preset deviation value, judging that the verification passes; the setting range of the third preset deviation value is 8% -12%.
Further, the second checking flow includes: verifying the second deviation rate of the obtained target threshold and the real-time operation data of the equipment, and judging that the verification is passed when the obtained second deviation rate is smaller than a second preset deviation value; the setting range of the second preset deviation value is 8% -12%.
Further, the second checking flow includes: acquiring real-time operation data of the equipment in a unit time period under a fixed working state of the equipment, and counting the proportion of the data of which the real-time operation data is larger than an obtained target threshold value in the unit time period relative to the real-time operation data of the equipment in the unit time period, wherein when the proportion is larger than a verification proportion value, the verification is judged to pass; the setting range of the verification proportion value is 85% -95%.
Further, the operating data includes historical operating power data or historical operating current data or real-time operating power data or real-time operating current data of the device.
Further, when k is greater than 2, the number of obtained target thresholds is not less than two; screening standards are preset, screening of the obtained target threshold is carried out according to the screening standards, and the target threshold obtained through screening is used as the execution basis of the step S4 or the step S5.
When the number of obtained target thresholds is not less than two:
firstly, the equipment has a plurality of working state conditions, and the equipment has a plurality of corresponding original threshold values corresponding to each working state; in step S3, obtaining that the obtained target threshold has a corresponding relationship with the operating state preset threshold of the device; when executing the step S4, checking the reliability of one or more obtained target thresholds and one or more corresponding working state preset thresholds by using a first checking flow; when step S5 is executed, the obtained one or more target thresholds are set as operation thresholds of the device instead of the corresponding one or more operating state preset thresholds.
Secondly, the equipment has a plurality of working state conditions; in step S3, the obtained target threshold has a corresponding relationship with each working state condition of the device; presetting an operation threshold selection range according to operation data obtained in a target working state, and selecting an obtained target threshold in the operation threshold selection range to perform a first verification process of verifying the reliability of the original threshold of the equipment when executing the step S4; when step S5 is performed, the resulting target threshold value in the operation threshold value selection range is selected as the operation threshold value setting of the apparatus.
Further, the setting range of the preset data proportion is 8% -12%.
Under the condition that the corresponding verification flow in the process is not passed and no other description exists, the marking of the equipment is usually selected in practical application, and the marked equipment is re-verified one by one in the subsequent process. The re-verification process may be handled by experienced engineers or through other system procedures.
The equipment monitoring method is used for setting the operation threshold of the equipment by applying the operation threshold setting method to the equipment, and monitoring the equipment by using a monitoring system; the monitoring system compares the obtained operation data with an operation threshold value of the equipment and makes a research and judgment operation; when the operation data of the equipment is not less than the operation threshold value set by the equipment, the judging result is that the working state is started; and when the operation data of the equipment obtained by monitoring is smaller than the operation threshold value set by the equipment, the judging result is that the working state is closed.
The monitoring system of the equipment comprises a plurality of pieces of equipment and monitoring devices, wherein the monitoring devices are in communication connection with the pieces of equipment; the monitoring system monitors the equipment by applying the monitoring method; when the operation data of the equipment is not less than the operation threshold value of the production working state, which is set by the equipment, the operation data is monitored, the result of the research and judgment is that the production working state is started, and the equipment is in the production state; when the operation data of the equipment is monitored to be smaller than the operation threshold value of the production working state, the judgment result is that the production working state is closed, and the equipment is in a non-production state.
The invention has the beneficial effects that:
1. by applying the method for setting the operation threshold of the equipment, the set operation threshold has the characteristic of high reliability, the monitored equipment has the monitored reliability, the monitoring verification of the production state of the equipment by a monitoring system is ensured to be accurate, the monitoring auditor is not required to perform one-by-one manual confirmation and check on a large number of equipment regularly and quantitatively, and the manpower and material resources are effectively saved.
2. By setting different verification processes of the multi-level application, the application reliability of the target threshold and the original threshold as the operation threshold of the equipment can be effectively ensured, and the condition of setting deviation of the operation threshold of the equipment is avoided.
3. The operation threshold setting method is applied, so that a monitoring system applying the operation threshold setting method can effectively distinguish and identify the working states of different equipment in different processes and industries in the monitoring process, and can make targeted monitoring and judging operation according to the working states, thereby being beneficial to the accurate control of the working states of the monitored equipment by a supervisor; in particular to the problem that the pollution production condition of a pollution discharge unit is difficult to confirm in the existing pollution supervision field.
Drawings
FIG. 1 is a graph of real-time power trends for a vapor repair industry paint spray apparatus;
FIG. 2 is a real-time power scatter plot of a paint spray apparatus;
FIG. 3 is a violin diagram of the clustering result of the power data of the paint spraying device;
FIG. 4 is a view of a paint spray apparatus power data thresholding violin;
FIG. 5 is a graph of the threshold partitioning result of the power data of the paint spraying apparatus;
FIG. 6 is a flowchart of a target threshold determination method according to embodiment 1 of the present invention;
FIG. 7 is a verification flow chart of a first verification flow chart of embodiment 2 of the present invention;
FIG. 8 is a verification flow chart of a second verification flow in embodiment 3 of the present invention;
FIG. 9 is a verification flow chart of a second verification flow chart of embodiment 4 of the present invention;
FIG. 10 is a verification flow chart of a first verification flow chart of embodiment 5 of the present invention;
FIG. 11 is a trend graph of real-time power status of a device when the original threshold is not appropriate;
FIG. 12 is a schematic diagram of power conditions for different operating states of an injection molding apparatus;
FIG. 13 is a flowchart of a multi-objective threshold determination method according to embodiment 6 of the present invention;
FIG. 14 is a violin chart of clustering results of power data of an injection molding device;
FIG. 15 is a view of an injection molding apparatus power data thresholding violin;
FIG. 16 is a graph of threshold partitioning results for power data of an injection molding apparatus;
FIG. 17 is a view of an injection molding apparatus current data clustered violin of example 7 of the present invention;
Fig. 18 is a view of an injection molding apparatus current data thresholding violin of example 7 of the present invention.
Detailed Description
In order to make the technical scheme, the purpose and the advantages of the invention more clear, the invention is further explained below with reference to the drawings and the embodiments.
Example 1:
the invention provides a monitoring system of equipment, which comprises a plurality of pieces of equipment and monitoring devices, wherein the monitoring devices are in communication connection with the pieces of equipment, so that the monitoring devices can acquire data of the pieces of equipment and monitor and judge the data; the monitoring system is provided with a monitoring method of the equipment, and the monitoring system can conduct research and judgment operation on the working state of the equipment by setting the operation threshold of the equipment and comparing the operation data obtained by monitoring with the operation threshold.
In the monitoring method of the equipment, the operation threshold value of the equipment is set firstly, and then the equipment with the operation threshold value is monitored. The monitoring system compares the obtained operation data with an operation threshold value of the equipment and makes a research and judgment operation; when the operation data of the equipment is not less than the operation threshold value set by the equipment, the judging result is that the working state is started; and when the operation data of the equipment obtained by monitoring is smaller than the operation threshold value set by the equipment, the judging result is that the working state is closed.
Specifically, the equipment monitoring system is a monitoring system of the sewage disposal equipment so as to monitor whether the sewage disposal equipment is in a pollution production state really; when the operation data of the sewage disposal equipment obtained by monitoring is not less than the operation threshold value of the sewage disposal working state, judging that the sewage disposal working state is started, namely the sewage disposal equipment is in the sewage disposal production state; when the operation data of the equipment obtained by monitoring is smaller than the operation threshold value of the pollution production working state, judging that the pollution production working state is closed, and the pollution discharge equipment is in a non-production state.
Taking the power operation data of production equipment in a sewage unit production line as an example to judge whether the sewage is produced or not, the invention provides a method for solving a target threshold value, which can solve the power target threshold value of the production equipment.
The specific application of the method for solving the target threshold is as follows:
and step 1, acquiring and cleaning equipment operation data.
Acquiring equipment power operation data and corresponding working state condition data of the power operation data, and forming a data set monitored by production equipment in a period time, wherein the sampling frequency of the period data is 5 minutes; after the power operation data recorded in 5 minutes are input to the system, the system automatically eliminates the abnormal value, for example, eliminates the record of the negative power value.
Step 2: the classification algorithm automatically clusters.
During the operation and non-operation of the production equipment of the pollution discharge unit, the power distribution of the production equipment of the pollution discharge unit is characterized in that: for example, the power value may fluctuate intensively during operation in a certain interval. Therefore, according to the distribution condition of the data, the data can be divided into intervals.
As shown in fig. 1 to 3. Taking the paint spraying equipment in the automobile repair industry as an example, in general, the power set on site is set to be 0.2KW, and once the real-time power is not less than 0.2KW, the corresponding switching conversion quantity is judged to be on. From the data, it is not difficult to find that the power is distributed more around (0, 0.5), (3, 5).
In the figure, the state switching value 1 indicates that the apparatus is on, and 0 indicates that it is not on.
From a practical business perspective, the unit power during non-production is influenced by other lighting devices, so that the power data is not 0, but fluctuates around 0.4KW, and thus the state may be misjudged under non-production conditions. In fact, the normal production of the device fluctuates in (3, 5), so we find (0.4,3) a value between them as a boundary dividing production and non-production.
In the classification algorithm, the separated high-density regions are treated as a separate class by finding the high-density regions separated by the low-density regions in the dataset. Assuming that there are many points around the point x, it is denoted as x 1 、x 2 …x j We calculate each point x around which point x moves j The sum of the required offsets is averaged to obtain the average offset. In addition to the size, the offset also contains directions of dense surrounding distribution. And the next step of moving the point x towards the direction of the average offset, taking the point x as a new starting point, and continuously iterating until a certain condition is met.
The general flow is as follows:
1) Randomly selecting a point in the data set as a starting center point S;
2) Taking S as a center radius as r, finding out all data points appearing in the region, considering the points to belong to a cluster C, and simultaneously recording the number of times of data point appearance in the cluster plus 1;
3) Calculating vectors of each element from S to the data set by taking S as a center point, and adding to obtain a vector S;
4) S=s+s, i.e., S moves along the S direction by a distance of S.
5) Repeating steps 2), 3), 4) until S is small, remembering S at this time. The points encountered in this iterative process should all be categorized into cluster C;
6) If the distance between S of the current cluster C and the center of the other existing cluster C2 is smaller than a set threshold (the set threshold is determined by the data set, and 50% quantiles of the set of any pair of sample distances in the data set), then the C2 and the C are combined, and the occurrence times of the data points are correspondingly combined. Otherwise, C is used as a new cluster;
7) Repeating steps 1) through 5) until all points are marked as accessed;
8) Classification: according to each class, the class with the largest access frequency is taken as the belonging class of the current point set.
As shown in fig. 3, based on the application of the paint spraying apparatus in the automotive repair industry, it can be seen that the results of the pollution discharge unit have 2 categories, the first clustering center and the second clustering center are respectively 0.05 and 3.94.
Step 3: the loop dichotomy finds the appropriate power target threshold.
As shown in fig. 4 to 5, based on the cluster center result obtained in the previous step, two cluster centers A are used 1 A is a 2 As boundary condition, all the data in the interval are proposed as a data set D, and the data D is divided by a dichotomy to obtain 2 parts of data D with equal width 1 And D 2 . Taking a preset data proportion value of 8-12%, preferably 10%; comparison D 1 And D 2 Taking a small data size as D m If D m The data amount is smaller than (D) 1 +D 2 ) 10% taking the average of the maximum and minimum values of the data as the target threshold, if D m The data amount is larger than (D 1 +D 2 ) 10% of the total number, then the D m Further partitioning is performed until a data size smaller than (D 1 +D 2 ) 10% dataset D m Taking the average value of the maximum value and the minimum value of the data as a power target threshold.
Dividing power data between two clustering centers obtained by a classification algorithm of front steam repair industry paint spraying equipment into 2 parts with equal width by using a dichotomy, and selecting the part with the smallest data quantity as D m The smallest data amount at this time is D 1 And D 2 The total data amount ratio of (2) is less than 10%, based on D m And (3) obtaining an average value a of the maximum value and the minimum value, wherein the obtained average value a is used as a power target threshold output application of the equipment and is 2.23KW. Obviously, compared with the original power threshold value 0.2KW of the original equipment, the numerical application of the obtained power target threshold value 2.23KW can better divide production and non-production conditions.
The method for solving the target threshold of the equipment comprises the following steps:
s1, acquiring operation data of equipment;
s2, clustering the operation data through a classification algorithm;
and S3, finding out a target threshold value through a cyclic dichotomy.
According to the obtained target threshold value, the target threshold value can be selected as an operation threshold value setting of the equipment as a preferable target threshold value application mode.
Based on the obtained power target threshold value 2.23KW, replacing the original threshold value 0.2KW of the original equipment, and changing and setting the power operation threshold value of the actual production working state of the equipment; when the real-time power of the paint spraying device is not less than 2.23KW, the corresponding switching conversion value is judged to be on. The monitoring system can accurately and effectively monitor the actual production work of the equipment.
The target threshold value solving method is applied, and the power target threshold value of the equipment can be obtained from the actual production environment of the equipment based on the actual operation data of the equipment; the obtained corresponding target threshold value has the characteristic of being more accurate relative to the original threshold value of delivery. The above-mentioned target threshold value calculation method is applied to the calculation, and the flow is shown in fig. 6.
The invention relates to a method for setting an operation threshold of equipment, which can be used for replacing the original threshold of the equipment with a target threshold obtained by solving so as to be directly used as the operation threshold of the equipment; based on the adjustment setting of the operation threshold, the accurate research and judgment requirements of the monitoring system on the equipment working state can be met.
In the operation data acquisition and calculation conditions of the equipment, the real-time operation power data of the equipment under the real-time condition or the historical operation power data of the equipment under the past condition can be selected for application according to actual requirements.
Specifically, the specific process of obtaining the power target threshold is as follows:
s2-1, clustering the obtained operation data, and recording the number of clustering centers as k;
s2-2, judging the condition of k; in the case of a single operating state, two cluster centers will be generated;
When k=2, the steps are performed: s2-2-1, i=1, and the clustering center is A i And A i+1 The method comprises the steps of carrying out a first treatment on the surface of the Then S2-3 is executed;
s2-3, A i And A i+1 For the boundary, get set D i ；
S3-1, pair set D by dichotomy i Dividing into a specific operation of taking A i And A i+1 Mean value (A) i +A i+1 ) 2 pairs D i Equal-width segmentation is carried out to obtain two sets, wherein the intervals of the sets are respectively [ A ] i ，(A i +A i+1 )/2)，[(A i +A i+1 )/2，A i+1 ]The method comprises the steps of carrying out a first treatment on the surface of the Comparing the data sizes of the two sets to obtain a set D with small data size mi ；
S3-2, judge D mi Whether the data quantity is smaller than the preset data proportion of Di data quantity, wherein the setting range of the preset data proportion is 8% -12%;
when D is mi The data amount of (2) is smaller than D i Executing S3-3 when the preset data proportion of the data quantity is preset;
when D is mi The data amount of (2) is not less than D i Outputting D when the preset data proportion of the data quantity mi Order D i ＝D mi Then, returning to the execution S3-1;
s3-3, calculate D mi Mean value a of maximum and minimum values in set i The result a i Is the target threshold.
Example 2:
in the application of the target threshold value calculation method according to the above embodiment 1, another preferable application mode of the present embodiment is as follows: and on the premise that the obtained target threshold is obtained to have reliability based on an algorithm, the reliability of the original threshold of the equipment is verified through the obtained target threshold by a first verification process, so that whether the original threshold of the equipment has reliability can be determined. The verification process application of the first verification process is shown in fig. 7.
Based on the foregoing, the operation threshold of the production device is not a fixed value, but fluctuates in a section, so we can well divide the on-off state as long as we find a value in the section; if the original threshold value is within the threshold value interval of the operation threshold value, the deviation rate of the state result judged by the original threshold value and the state result judged by the target threshold value is basically small because the target threshold value obtained by the algorithm is also within the threshold value interval of the operation threshold value, but if the original threshold value is not within the threshold value interval, a certain deviation is generated between the state result judged by the target threshold value and the state result judged by the original threshold value. Therefore, if the difference between the calculated target threshold and the original threshold of the device is within a reasonable range, the original threshold of the device can be considered to be reliable. This is the basic setup idea of the present solution.
Under the condition that the original threshold value of the equipment is confirmed to be reliable, the original threshold value of the equipment is continuously used as the running threshold value of the equipment, so that the operation flow is reduced on the premise that the accurate application of monitoring work can be ensured.
The first verification process optionally includes: and verifying the first deviation rate of the obtained target threshold and the original threshold of the equipment, and judging that the verification passes when the obtained first deviation rate is smaller than a first preset deviation value. The value of the first preset deviation value ranges from 8% to 12%, and is preferably set to 10%.
Taking the application of the vapor repair industry paint spraying device as an example: if the original threshold value set by the original equipment is 2KW, when the first preset deviation value is 12%, the theoretical selection range of the target threshold value of which the value of the original threshold value floats up and down by 12% is between 1.76KW and 2.24 KW; therefore, when the obtained target threshold value is 2.23KW, the setting of the original threshold value is considered to be reliable. The painting installation can thus continue to use 2KW as the operating threshold and the production operating state can be continuously monitored by the monitoring device at 2 KW.
The setting steps of the first checking flow are as follows:
s4-1, comparing the obtained target threshold with an original threshold of equipment, and calculating a first deviation rate;
s4-2, judging whether the first deviation rate is smaller than a first preset deviation value;
and when the first deviation rate is smaller than a first preset deviation value, the verification of the first verification flow is passed.
Therefore, the operation threshold setting method of the equipment can select and execute the first checking flow for checking the reliability of the original threshold of the equipment by using the obtained target threshold; if the verification is passed, the equipment is continuously set according to the original threshold value as the running threshold value of the equipment, so that the accurate research and judgment requirements of the monitoring system on the working state of the equipment are met.
Example 3:
in order to avoid that a larger deviation exists in the calculation of the obtained target threshold value (such as the condition of data packet loss of operation data acquisition) caused by other conditions; and the second verification flow can be used for verifying the reliability of the obtained target threshold, and when the obtained target threshold passes verification, the obtained target threshold is used as the running threshold setting of the equipment or used as the original threshold reliability verification reference setting of the equipment. The verification process application of the second verification process is shown in fig. 8.
The second checking flow may optionally include: and verifying the second deviation rate of the obtained target threshold and the real-time operation data of the equipment, and judging that the verification passes when the obtained second deviation rate is smaller than a second preset deviation value. The value of the second preset deviation value ranges from 8% to 12%, and is preferably set to 10%.
Specifically, continuing to take the application of the vapor repair industry paint spraying device as an example: the real-time operational data may be selected as average power data over a periodic sampling time (5 min) of the device in the target operating state.
For example: for a target threshold value in a pollution production working state, under a definite pollution production working state (through manual confirmation or comprehensive analysis confirmation), acquiring operation data of the equipment in a period time period, and solving a data average value; in the paint spraying apparatus, when the real-time operation data of the average value obtained in the pollution-producing working state is 2.5KW, the second preset deviation value is set to be 12%, the current target threshold value obtained is calculated to be 2.23KW, and the second deviation rate between the target threshold value and the real-time operation data of the apparatus is smaller than the second preset deviation value, so that the verification is determined to pass.
On the premise of the application of embodiment 2, if the first verification flow is executed and the verification result is not passed, the target threshold may be found erroneously or the deviation between the original threshold and the found target threshold may be large (the target threshold is reasonable). A second checking flow of performing reliability check on the obtained target threshold value is executed subsequently; if the second checking flow passes the checking, judging that the deviation between the original threshold and the calculated target threshold is larger; the target threshold is a reasonable condition, and the obtained target threshold can be set as the operation threshold of the equipment. If the second checking flow is not checked, the possibility of solving errors by the target threshold exists, and the equipment is required to be marked; for subsequent verification.
Example 4:
based on the application of embodiment 3, a further preferred arrangement of embodiment 3 is described in this embodiment.
The second verification flow in the above embodiment 3 can be modified and applied as follows: and under the fixed working state of the equipment, acquiring real-time operation data of the equipment in a unit time period, counting the ratio of the real-time operation data of the equipment in the unit time period to the real-time operation data of the equipment in the unit time period, wherein the ratio is larger than a verification ratio value, and when the ratio is larger than the verification ratio value, the target threshold can be reliably set, and the verification is judged to be passed. The verification process application of the second verification process is described with reference to fig. 9.
For example:
in the case that the equipment is in a stable starting working state (such as a production state), the real-time power operation data of the starting working state of the equipment is compared with a target threshold value by taking 24 hours as a unit time period, and if more than 90% of the monitored power operation data exceeds the target threshold value within 24 hours, the verification is considered to be passed, and the obtained target threshold value is reliable.
Example 5:
based on the application of the above embodiments, this embodiment is further described as a preferred arrangement.
In the application of the above embodiment, the corresponding verification may be performed only based on the data situation generated by the device itself; in the application of the scheme of the embodiment, a simulated studying and judging action setting can be further combined, so that the corresponding verification process can have the characteristics of more accuracy and reliability in the whole life cycle.
The first verification process of performing the reliability verification of the device preset threshold by the obtained target threshold is applied as follows: simulating and generating a grinding result generated by a target threshold value on the operation data and a grinding result generated by an original threshold value of equipment on the operation data, and carrying out statistical comparison on the grinding result generated by the obtained target threshold value on the operation data and the grinding result generated by the original threshold value of the equipment on the operation data to obtain a third deviation rate; and when the obtained third deviation rate is smaller than a third preset deviation value, judging that the verification passes. The value of the third preset deviation value ranges from 8% to 12%, and is preferably set to 10%.
In the actual application process, the obtained target threshold value is obtained, and then the situation of the research and judgment result made in the corresponding operation data generation process is correspondingly counted according to the operation situation (or the historical operation data or the real-time operation data) of the selected operation data. Aiming at the working state situation (such as the pollution production working state of the paint spraying equipment in the automobile repair industry) which needs to be researched and judged, determining the condition that the pollution production working state is opened after the corresponding target threshold value is set in a data sampling period (5 min) and the condition that the pollution production working state is opened after the original threshold value is set, carrying out simulation statistics, and judging that the verification is passed and determining the reliability condition of the original threshold value when the deviation rate between the number of the research and judgment results obtained based on the target threshold value and the number of the research and judgment results obtained based on the original threshold value is smaller than a third preset deviation value. The verification process application of the first verification process is shown in fig. 10.
For example: and using the obtained target threshold value as an operation threshold value, judging the opening and closing states of the equipment at each monitoring time point by the monitoring system, and comparing the opening and closing states with the judgment result of the original preset value. When 100 time points are preset, the original preset value is judged to be on, but the obtained target threshold is selected to be used as the result of the operation threshold judgment, only 70 points are on, the error rate reaches 30%, the error rate exceeds 10% of the preset deviation, the original threshold is considered unreliable, the first checking flow is not checked to be passed, and a second checking flow process or a further checking process is needed to be carried out by personnel after equipment is marked.
As a true application case:
based on environmental protection monitoring data of a pollution discharge unit, 978 production lines are about 1750 ten thousand pieces of data, modeling learning is carried out on power operation threshold values of equipment by using the algorithm, the condition of the original threshold values of the equipment is verified, the deviation is about 719 pieces which are within 10%, and the current state judgment of most of the production line equipment is reasonable. And a total of 259 of deviations greater than 10% are determined as the failure of the reliability check of the original threshold value of the first check flow.
And for the condition that the verification of the first verification process is not passed, the reliability verification of the target threshold value can be carried out in a second verification process mode, or the verification can be directly carried out through a monitoring system or a manual mode. From the review, the same power value exists in 203 production lines in 259, but the situation of different states can be judged at different moments, and the total power value is about 20.8%; in this case, it is considered that the data generated by the device has a quality problem, and is not considered as a problem of accuracy of the target threshold value obtained in the present embodiment.
In addition, 33 production line power fluctuation is obvious, the identified target threshold value is not 0 or even larger, the actual state is always judged to be closed, and the total number is about 3.4%; this means that there is a problem with the original threshold value of the device, and in this case, it is necessary to change the operation threshold value originally preset for the device by the obtained power target threshold value.
As shown in fig. 11, after 8 points, the power fluctuation of the device is obvious, but the state is always closed, and the original threshold value of the device on the site is unreasonable, and may be set too high, so that the true state of the device cannot be accurately identified. In summary, the method can verify the existing state to obtain whether the original threshold state of the existing pollution discharge unit equipment is reasonable or not, the overall misjudgment rate is 2.4%, and the method is relatively small and has reliability.
Example 6:
in the above embodiment, taking the working condition of the paint spraying equipment in the automobile repair industry as an example, the power target threshold value solving condition of the equipment with single production working condition (pollution production working condition) is pointed out. In this embodiment, the power target threshold calculation of the corresponding multi-operating device will be described.
As shown in fig. 12, taking the injection molding industry as an example, the film blowing process has a heating working condition, and the production equipment has two different working conditions of a heating working condition and a production working condition except a shutdown condition. In the film blowing process, a certain power output is generated in the heating working process, but no waste gas is generated because the actual production is not performed. Therefore, from the perspective of environmental protection monitoring, we need to accurately find the production working state of the film blowing process equipment to monitor.
However, in practical applications, the original threshold value of the film blowing process equipment is generally set to be lower (or only set to be greater than 1 KW), and the original threshold value may cause the monitoring system to generate a monitored linkage alarm in the preheating state, which does not conform to the required practical monitoring situation.
Therefore, for the above application, the algorithm for solving the target threshold in this embodiment is further supplemented:
in the case of two operating states, the resulting operational data will have three cluster centers; therefore, in step S2-2, when k is greater than 2, the steps are performed: s2-2-2, initializing i=1; s2-2-3, selecting the ith and (i+1) th clustering centers A i And A i+1 The method comprises the steps of carrying out a first treatment on the surface of the Then executeRow S2-3;
after the step S3-3 is executed, when k is greater than 2, executing a step S6 to judge whether i+1 is less than k;
when i+1 is smaller than k, outputting i=i+1 to step S2-2-3, and sequentially repeating the above operation steps to obtain a plurality of target thresholds a i Until i+1 is not less than k;
when i+1 is not less than k, acquiring all target thresholds; at this time, the acquisition target threshold number is 2 or more.
In this embodiment, in the case of three cluster center applications generated based on the working conditions with two different working states, two target thresholds will be generated.
Each target threshold a i In the process of obtaining (a), according to different verification requirements, different first verification processes or second verification processes in the above embodiment can be selected to perform combined setting application respectively.
The flow setting of the multi-target threshold value calculation method is described with reference to fig. 13.
As shown in fig. 14 to 16, by applying the algorithm for obtaining the target threshold value of the apparatus, it can be found that the power of the injection production apparatus fluctuates in 3 intervals, which correspond to a shutdown concentration interval, a preheating concentration interval, and a production concentration interval, respectively, and two obtained target threshold values are obtained at this time, which are 1.6KW and 31.2KW, respectively; the obtained target threshold is not unique, and the obtained target threshold has corresponding relation with each working state of the equipment in quantity and numerical value selection range.
Screening standards are preset, the obtained target threshold value is screened according to the screening standards, and the target threshold value obtained by screening is used as an execution basis for monitoring the working state of the equipment.
Firstly, according to practical experience conditions, the equipment preheating state is a lower power output state, the equipment pollution production state is a higher power output state, and the power operation data in the application of the two working states have obvious differences; therefore, the screening standard is the obtained target threshold value with obvious difference in the number through big data or artificial intelligent identification, and the operation threshold values of different working states are divided and matched.
Therefore, according to the screening criteria, the embodiment selects the lower power output state value of 1.6KW as the operation threshold of the preheating state of the device, the higher power output state value of 31.15KW as the operation threshold of the pollution producing state of the device, and executes the first checking flow and the operation threshold setting application after checking or uses the obtained target threshold as the operation threshold setting application of the device based on the 31.15KW as the actual pollution producing state power operation threshold of the device, and then uses the actual monitoring situation obtained by the monitoring system to better meet the actual needs.
On the other hand, the above screening criteria may be set according to a selection range preset with an operation threshold according to the obtained operation data.
For example, in the application of film blowing process equipment, the reasonable range of the operating data conditions of different working states of the equipment (such as the reasonable range of the power output data in the preheating state and the reasonable range of the power output data in the pollution producing state of the equipment) can be known through manual confirmation or comprehensive analysis confirmation of other analysis system programs, and the reasonable range of the data can be set to be applied to the range of 10% of the upper and lower floating of the average operating data of the corresponding working states; therefore, on the basis, the operating threshold selection range of the equipment preheating state is below the reasonable range of the power output data of the preheating state, and the operating threshold selection range of the equipment pollution production state is below the reasonable range of the power output data of the pollution production state. According to the condition that the required monitoring target is the equipment pollution production state, selecting a target threshold value within a reasonable range of power output data in the equipment pollution production state from a plurality of target threshold values acquired by the algorithm as an operation threshold value setting in the equipment pollution production state.
In the application of different environments, for the condition of simultaneous monitoring of multiple working states, the device is provided with a plurality of corresponding original threshold values of the working states, the device obtains the obtained target threshold values through the setting method, and the device has one-to-one correspondence with the original threshold values of the working states in the application conditions of the number and the numerical value setting range.
Then, under the condition that a reasonable range of the power output data corresponding to the working state is preset, a plurality of target thresholds obtained through the algorithm are provided, and each obtained target threshold has a matching relation with the reasonable range of the power output data of each working state.
Correspondingly, in the process of setting the operation threshold, a first checking flow for checking the reliability of the original threshold of different working states of the equipment and/or a second checking flow for checking the reliability of each target threshold can be selectively executed, the operation threshold of each working state of the equipment is set by each target threshold meeting the checking passing condition, or the original threshold of each working state after the checking passing condition is used as the operation threshold of the equipment to be continuously set, so that the obtained target threshold and the corresponding working state situation can be effectively matched for guiding, and in the application of the monitoring system, the monitoring device is provided with different monitoring alarm measures for different standard situations of the operation threshold, and the requirement of the monitoring system on the respective monitoring application of the multiple working state situations of the equipment can be met.
Example 7:
in the above description of the embodiments, it is indicated that there is an operation threshold setting and a monitoring application condition of the device in the power operation data. In this embodiment, the operation of the corresponding current operation data in the setting and monitoring application condition will be described. As shown in fig. 17 to 18, by applying the algorithm for obtaining the target threshold value of the equipment, the corresponding historical current data of the paint spraying equipment is obtained and the algorithm operation is performed, so that when the production equipment performs the pollution production action in the production concentrated region, the running threshold value of the current is set to obtain the target threshold value 54.61a of the current to divide the pollution production, and the actual situation is more met. In the algorithm operation process of the present embodiment, the selected operation data includes historical operation current data or real-time operation current data of the device.
Example 8:
based on the application of the algorithm for calculating the target threshold in the above embodiment, those skilled in the art can understand that, in the approximate application field, the following are: the equipment monitoring system can accurately monitor and judge the use behavior state of corresponding illegal electric equipment, and meets the requirements of monitoring applications of other equipment except the field of pollution discharge monitoring.
The foregoing is merely a preferred embodiment of the present invention, and modifications of the embodiments described above can be made by those skilled in the art without departing from the implementation principles of the present invention, and the corresponding modifications should also be considered as the protection scope of the present invention.
Claims (14)
1. The operation threshold setting method is characterized by comprising the following steps:
s1, acquiring operation data of equipment;
s2, clustering the operation data through a classification algorithm;
s3, finding out a target threshold value through a cyclic dichotomy;
in steps S2 to S3, the target threshold value obtaining process is as follows:
s2-1, clustering the obtained operation data, and recording the number of clustering centers as k;
s2-2, judging the condition of k;
when k=2, the steps are performed: s2-2-1, i=1, and the clustering center is A i And A i+1 The method comprises the steps of carrying out a first treatment on the surface of the Then S2-3 is executed;
when k is greater than 2, the steps are performed: s2-2-2, initializing i=1; s2-2-3, selecting the ith and the (i+1) th clustering centers Ai and ai+1; then S2-3 is executed;
s2-3, A i And A i+1 For the boundary, get set D i ；
S3-1, pair set D by dichotomy i Performing equal-width division to obtain two sets; comparing the data sizes of the two sets to obtain a set D with small data size mi ；
S3-2, judge D mi Whether the data amount of (a) is smaller than D i A preset data proportion of the data amount;
when D is mi The data amount of (2) is smaller than D i Executing S3-3 when the preset data proportion of the data quantity is preset;
when D is mi The data amount of (2) is not less than D i Outputting D when the preset data proportion of the data quantity mi Order D i ＝D mi Then, returning to the execution S3-1;
s3-3, calculate D mi Mean value a of maximum and minimum values in set i The result a i Is a target threshold;
after the step S3-3 is executed, a step S6 is executed;
s6, judging whether i+1 is smaller than k;
when i+1 is smaller than k, let i=i+1, and then return to step S2-2-3;
when i+1 is not less than k, acquiring a target threshold value;
according to the obtained target threshold, then executing step S4 or S5;
s4, executing a first verification process of performing reliability verification of the original threshold value of the equipment by using the obtained target threshold value; if the verification is passed, setting the equipment according to the original threshold value as an operation threshold value;
s5, setting the obtained target threshold value as an operation threshold value of the equipment.
2. The operation threshold setting method according to claim 1, wherein in step S4, if the verification of the first verification process is not passed, a second verification process for performing reliability verification on the obtained target threshold is performed; if the second checking flow passes the checking, setting the obtained target threshold as an operation threshold of the equipment; and if the second checking flow does not pass the checking, marking the equipment.
3. The operation threshold setting method according to claim 1, wherein in step S5, a second check flow of checking the reliability of the obtained target threshold is performed; and if the verification is passed, setting the obtained target threshold as the operation threshold of the equipment.
4. A method of setting an operation threshold according to any one of claims 1 to 3, wherein the first verification process includes: verifying a first deviation rate of the obtained target threshold and an original threshold of the equipment, and judging that the verification is passed when the obtained first deviation rate is smaller than a first preset deviation value; the setting range of the first preset deviation value is 8% -12%.
5. A method of setting an operation threshold according to any one of claims 1 to 3, wherein the first verification process includes: carrying out statistical comparison on the obtained research and judgment result generated by the target threshold value on the operation data and the research and judgment result generated by the original threshold value of the equipment on the operation data to obtain a third deviation rate; when the obtained third deviation rate is smaller than a third preset deviation value, judging that the verification passes; the setting range of the third preset deviation value is 8% -12%.
6. The operation threshold setting method according to claim 2 or 3, wherein the second check flow includes: verifying the second deviation rate of the obtained target threshold and the real-time operation data of the equipment, and judging that the verification is passed when the obtained second deviation rate is smaller than a second preset deviation value; the setting range of the second preset deviation value is 8% -12%.
7. The operation threshold setting method according to claim 2 or 3, wherein the second check flow includes: acquiring real-time operation data of the equipment in a unit time period under a fixed working state of the equipment, and counting the proportion of the data of which the real-time operation data is larger than an obtained target threshold value in the unit time period relative to the real-time operation data of the equipment in the unit time period, wherein when the proportion is larger than a verification proportion value, the verification is judged to pass; the setting range of the verification proportion value is 85% -95%.
8. The operation threshold setting method according to claim 1, wherein the operation data includes historical operation power data or historical operation current data or real-time operation power data or real-time operation current data of the device.
9. The operation threshold setting method according to claim 1, wherein the device has a plurality of operation state conditions, and the device has a corresponding plurality of preset thresholds for each operation state; in step S3, obtaining that the obtained target threshold has a corresponding relationship with the operating state preset threshold of the device; when executing the step S4, checking the reliability of one or more obtained target thresholds and one or more corresponding working state preset thresholds by using a first checking flow; when step S5 is executed, the obtained one or more target thresholds are set as operation thresholds of the device instead of the corresponding one or more operating state preset thresholds.
10. The operation threshold setting method according to claim 1, wherein the device has a plurality of operating state conditions; in step S3, the obtained target threshold has a corresponding relationship with each working state condition of the device; presetting an operation threshold selection range according to operation data obtained in a target working state, and selecting an obtained target threshold in the operation threshold selection range to perform a first verification process of verifying the reliability of the original threshold of the equipment when executing the step S4; when step S5 is performed, the resulting target threshold value in the operation threshold value selection range is selected as the operation threshold value setting of the apparatus.
11. The operation threshold setting method according to claim 1, wherein when k is greater than 2, the number of obtained target thresholds is acquired to be not less than two; screening standards are preset, screening of the obtained target threshold is carried out according to the screening standards, and the target threshold obtained through screening is used as the execution basis of the step S4 or the step S5.
12. The operation threshold setting method according to claim 1, wherein the setting range of the preset data proportion is 8% to 12%.
13. A monitoring method, characterized in that the operation threshold setting method according to any one of claims 1 to 12 is applied to the equipment to set the operation threshold of the equipment, and the monitoring operation is performed on the equipment by a monitoring system; the monitoring system compares the obtained operation data with an operation threshold value of the equipment and makes a research and judgment operation; when the operation data of the equipment is not less than the operation threshold value set by the equipment, the judging result is that the working state is started; and when the operation data of the equipment obtained by monitoring is smaller than the operation threshold value set by the equipment, the judging result is that the working state is closed.
14. The monitoring system is characterized by comprising a plurality of devices and monitoring devices, wherein the monitoring devices are in communication connection with the devices; the monitoring system monitors equipment by applying the monitoring method as claimed in claim 13; when the operation data of the equipment is not less than the operation threshold value of the production working state, which is set by the equipment, the operation data is monitored, the result of the research and judgment is that the production working state is started, and the equipment is in the production state; when the operation data of the equipment is monitored to be smaller than the operation threshold value of the production working state, the judgment result is that the production working state is closed, and the equipment is in a non-production state.
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