A special transformer acquisition terminal operation data analysis method and storage medium

Abstract

The present invention belongs to the technical field of operation detection of special transformer acquisition terminals, and specifically relates to a special transformer acquisition terminal operation data analysis method and storage medium. The method carries out a self-inspection process for a preset self-inspection duration period on a target special transformer acquisition terminal on a current self-inspection date. On the one hand, the overall communication success rate, the overall communication delay rate and the overall communication packet loss rate are used as key communication indicators, and the data acquisition accuracy and data acquisition integrity are used as key data acquisition indicators. Fine-grained evaluations of communication and data acquisition abnormal risks within the current self-inspection duration period of the target special transformer acquisition terminal are respectively carried out to help more accurately reflect the potential problems of the current communication status and data acquisition status of the target special transformer acquisition terminal. On the other hand, forward-looking predictions are made for communication and data acquisition abnormal risks within a preset self-inspection interval period in the future, providing strong support for the formulation of response measures and preventive maintenance plans, thereby ensuring the normal operation of the power system.

Description

Technical Field

[0001] The present invention belongs to the technical field of operation detection of special transformer acquisition terminals, and specifically relates to a method and storage medium for analyzing operation data of special transformer acquisition terminals. Background Art

[0002] As an important part of smart grid, dedicated transformer data collection terminals play a key role in power system operation monitoring, power consumption information collection, etc. However, since dedicated transformer data collection terminals are usually deployed in various complex environments, they may encounter problems such as hardware aging and software failures after long-term operation. If they are not discovered in time, they may affect the accuracy of data collection and thus affect the overall operation efficiency of the power system. Therefore, it is crucial to establish an efficient and reliable operation data analysis method to timely discover and solve problems that may arise during terminal operation.

[0003] The existing technology for the operation self-check processing of the special transformer acquisition terminal is mainly focused on the data acquisition quality detection and correction level, such as the invention patent application of a power quality monitoring method and system based on a special transformer acquisition terminal with Chinese patent number CN2022114118145, which determines the data acquisition source of the special transformer acquisition terminal according to the monitoring indicators of the power quality assessment and constructs a corresponding data transmission channel, performs data feature recognition on the data acquisition source, outputs the abnormal recognition result, performs data correction on the abnormal recognition result to obtain the data conversion result, and transmits the data conversion result to the power quality monitoring system for power quality assessment. The technical problem that the power quality assessment process for special transformer users in the existing technology is insufficient in the accuracy of power quality assessment data collection, resulting in low reference value of power quality assessment results in power operation and maintenance.

[0004] Although it can guarantee the data collection accuracy of the dedicated transformer collection terminal to a certain extent, it still lacks the ability to detect the operation safety of the dedicated transformer collection terminal itself. On the one hand, it does not involve the communication risk detection and data collection risk detection during the actual operation of the dedicated transformer collection terminal, making it impossible to timely understand the communication quality and data collection accuracy during the operation of the dedicated transformer collection terminal, which in turn leads to low operation reliability of the dedicated transformer collection terminal. On the other hand, it is limited to real-time detection of the operating status of the dedicated transformer collection terminal, and lacks the ability to predict future potential risks based on historical data and trend analysis, resulting in communication operation abnormalities or data collection abnormalities can only be identified when they occur or are about to occur, and preventive measures cannot be taken in advance, thereby increasing the risk and cost of unexpected failures. Summary of the invention

[0005] In order to overcome the shortcomings of the background technology, an embodiment of the present invention provides a method and storage medium for analyzing operation data of a special variable acquisition terminal, which can effectively solve the problems involved in the above-mentioned background technology.

[0006] The purpose of the present invention can be achieved through the following technical solutions: The first aspect of the present invention provides a method for analyzing the operation data of a special transformer collection terminal, including: S1. Recording the target special transformer collection terminal as the target terminal, and formulating a self-inspection plan for it, including a preset self-inspection date sequence, a preset self-inspection duration period and a preset self-inspection interval period.

[0007] S2. On the current self-inspection date, a self-inspection process is carried out on the target terminal for a preset self-inspection duration period, and the state quantity data and collection quantity data of each detection period of each day in the current self-inspection duration period of the target terminal are collected, wherein the state quantity data includes communication state data and environmental state data.

[0008] S3. Analyze the performance values ​​of each key communication indicator and each key data acquisition indicator in each detection period of each day during the current self-test duration period of the target terminal, and evaluate the communication abnormality risk and data acquisition abnormality risk during the current self-test duration period of the target terminal.

[0009] S4. Construct the direct correlation coefficient of each environmental parameter for each key communication indicator of the target terminal, and predict the communication anomaly risk of the target terminal within the preset self-check interval period in the future.

[0010] S5. Construct direct correlation coefficients of various environmental parameters and communication key indicators for each key data acquisition indicator of the target terminal, and predict the data acquisition abnormality risk of the target terminal within the preset self-test interval period in the future.

[0011] S6. Provide feedback and warning on the communication abnormality risk and data acquisition abnormality risk within the current self-test duration period of the target terminal and within the future preset self-test interval period.

[0012] A second aspect of the present invention provides a storage medium, which stores one or more programs. The one or more programs can be executed by one or more processors to implement the steps in the special transformer acquisition terminal operation data analysis method described in the present invention.

[0013] Compared with the prior art, the embodiments of the present invention have at least the following advantages or beneficial effects: (1) The present invention uses the overall communication success rate, the overall communication delay rate and the overall communication packet loss rate as key communication indicators to carry out a fine-grained assessment of the communication anomaly risk during the current self-test duration period of the target dedicated variable acquisition terminal, thereby helping to more accurately reflect the changing trends and potential problems of the communication status of the target dedicated variable acquisition terminal, and improving the accuracy and reliability of risk assessment.

[0014] (2) The present invention uses data acquisition accuracy and data acquisition completeness as key indicators of data acquisition, and conducts precise assessment of data acquisition abnormality risks within the current self-test period of the target dedicated variable acquisition terminal, which helps to discover potential data acquisition problems and prevent the problems from expanding, thereby improving the reliability and accuracy of data acquisition.

[0015] (3) The present invention comprehensively considers the impact of environmental changes on the communication performance of the target dedicated transformer acquisition terminal, and makes a forward-looking prediction of the risk of communication anomalies within the future preset self-test interval period, which helps operation and maintenance personnel to promptly discover and deal with potential problems, avoid the occurrence of serious faults such as communication interruption or data loss, and thus improve the communication stability and reliability of the dedicated transformer acquisition terminal, thereby ensuring the normal operation of the power system.

[0016] (4) The present invention combines the impact of environmental changes and communication performance changes on the data collection of the target dedicated variable acquisition terminal to make a forward-looking prediction of the data collection abnormality risk within the future preset self-test interval period, so that operation and maintenance personnel can understand possible data collection problems in advance, providing strong support for the formulation of response measures and preventive maintenance plans. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] The present invention is further described using the accompanying drawings, but the embodiments in the accompanying drawings do not constitute any limitation to the present invention. A person skilled in the art can obtain other drawings based on the following drawings without creative work.

[0018] Figure 1 It is a schematic diagram of the real-time step flow of the method of the present invention.

[0019] Figure 2 It is a communication diagram of the dedicated transformer acquisition terminal of the present invention.

[0020] Figure 3 It is a schematic diagram of the storage medium structure of the present invention. DETAILED DESCRIPTION

[0021] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0022] See also Figure 1 As shown, the purpose of the present invention can be achieved through the following technical solutions: The first aspect of the present invention provides a method for analyzing the operation data of a special transformer acquisition terminal, the method comprising: S1. Recording the target special transformer acquisition terminal as the target terminal, and formulating a self-inspection plan for it, including a preset self-inspection date sequence, a preset self-inspection duration period and a preset self-inspection interval period.

[0023] S2. On the current self-inspection date, a self-inspection process is carried out on the target terminal for a preset self-inspection duration period, and the state quantity data and collection quantity data of each detection period of each day in the current self-inspection duration period of the target terminal are collected, wherein the state quantity data includes communication state data and environmental state data.

[0024] See also Figure 2 As shown, specifically, the communication status data includes the total amount of information transmitted between the user end and the terminal, the amount of information successfully transmitted, the total amount of data packets transmitted, the amount of data packets successfully transmitted, and the average transmission delay time of successfully transmitted data packets between the terminal and the main station.

[0025] The collected data includes collected monitoring values ​​of each power usage parameter at each unit time point.

[0026] The environmental status data includes an environmental temperature value, an environmental humidity value, and an environmental electromagnetic interference intensity.

[0027] It should be noted that the above-mentioned communication status data is obtained by extracting the communication log content of the target special transformer collection terminal, where the user end refers to the special transformer user end corresponding to the target special transformer collection terminal, and the master station refers to the core system or platform for collecting and processing the data collected by the special transformer collection terminal.

[0028] The collected data is obtained by extracting the log content of the master station database of the target dedicated variable collection terminal.

[0029] The environmental status data is obtained through monitoring by the temperature and humidity sensors and electromagnetic interference meters deployed in the target dedicated acquisition terminal. The ambient temperature value, ambient humidity value and ambient electromagnetic interference intensity are the average values ​​of the corresponding environmental parameters during the detection period.

[0030] S3. Analyze the performance values ​​of each key communication indicator and each key data acquisition indicator in each detection period of each day during the current self-test duration period of the target terminal, and evaluate the communication abnormality risk and data acquisition abnormality risk during the current self-test duration period of the target terminal.

[0031] Specifically, the evaluation of the communication anomaly risk of the target terminal during the current self-test duration period includes: taking the ratio of the amount of successfully transmitted information to the total amount of transmitted information as the communication success rate, taking the ratio of the difference between the total amount of transmitted data packets and the amount of successfully transmitted information to the total amount of transmitted data packets as the communication packet loss rate, and taking the ratio of the average delayed transmission time of successfully transmitted data packets to a reasonable threshold of a preset data packet transmission time as the communication delay rate.

[0032] The communication success rate, packet loss rate and delay rate between the user terminal and the terminal, and between the terminal and the main station are obtained in each detection period of each day during the current self-test duration of the target terminal. Based on the communication link influence weights between the user terminal and the terminal, and between the terminal and the main station, the overall communication success rate of each detection period of each day during the current self-test duration of the target terminal is calculated. , overall communication delay rate and the overall communication packet loss rate , as the performance value of each key communication indicator in each detection period of each day during the current self-test duration period of the target terminal, It is the number of each day in the current self-test duration cycle. , is the number of each detection period, .

[0033] It should be noted that the influence weights of the communication links between the user end and the terminal, and between the terminal and the main station are obtained by considering a series of factors such as the service requirements of the communication link, bandwidth capacity, etc. In the present invention, the influence weights of the communication links between the user end and the terminal, and between the terminal and the main station are specifically set to 0.5 and 0.5.

[0034] From this above The calculation process is to multiply the communication success rates between the user end and the terminal, and between the terminal and the main station by the corresponding communication link influence weights in each detection period of each day in the current self-test duration period. and .

[0035] By formula Obtain the communication anomaly risk assessment index within the current self-check duration period of the target terminal, where The number of days for the current self-test cycle. is the number of detection periods, is a natural constant, They are respectively the reasonable threshold of the overall communication success rate, the permitted threshold of the overall communication delay rate and the permitted threshold of the overall communication packet loss rate within the preset special transformer acquisition terminal detection period.

[0036] It should be noted that the above It is the detection setting standard for the self-test plan of the dedicated transformer acquisition terminal. For details, please refer to the technical planning requirements of the dedicated transformer acquisition terminal manufacturer.

[0037] The embodiment of the present invention uses the overall communication success rate, the overall communication delay rate and the overall communication packet loss rate as key communication indicators to carry out a fine-grained assessment of the communication anomaly risk within the current self-test duration period of the target dedicated variable acquisition terminal, thereby helping to more accurately reflect the changing trends and potential problems of the communication status of the target dedicated variable acquisition terminal and improve the accuracy and reliability of risk assessment.

[0038] Specifically, the evaluation of the data acquisition abnormality risk within the current self-test duration period of the target terminal includes: obtaining the actual monitoring value of each power consumption parameter at each unit time point in each detection period of each day in the current self-test duration period of the user terminal, comparing it with the corresponding collected monitoring value of the target terminal, and analyzing the data acquisition accuracy of each detection period of each day in the current self-test duration period of the target terminal. and data acquisition completeness , and use it as the key indicator performance value of each data acquisition period in each day during the current self-test duration period of the target terminal.

[0039] It should be noted that the actual monitoring values ​​of each power consumption parameter at each unit time point in each detection period on each day during the current self-inspection period of the above-mentioned user end are collected through high-precision metering tools such as metering secondary conductors and smart meters deployed on the electric energy metering equipment corresponding to the special transformer user on the target special transformer collection terminal.

[0040] It should also be noted that the above The calculation process is as follows: by performing difference processing between the actual monitoring value and the collected monitoring value, the absolute monitoring deviation value between the actual monitoring value of each power consumption parameter at each unit time point in each detection period of each day during the current self-test duration period of the user end and the corresponding collected monitoring value of the target terminal is obtained; by analyzing the ratio of the absolute monitoring deviation value to the actual monitoring value, the actual monitoring value of each power consumption parameter at each unit time point in each detection period of each day during the current self-test duration period of the user end and the absolute monitoring deviation value ratio of the corresponding collected monitoring value of the target terminal are obtained; and then the average monitoring deviation ratio of each power consumption parameter at each unit time point in each detection period of each day during the current self-test duration period of the user end is obtained. , is the number of each power parameter, , according to the formula Obtain the data acquisition accuracy of each detection period on each day during the current self-test duration period of the target terminal.

[0041] Above The calculation process is as follows: check the collected monitoring values ​​of each power consumption parameter at each unit time point in each detection period of each day during the current self-test duration period of the target terminal, compare them with the invalid monitoring values ​​of each power consumption parameter stored in the WEB cloud, filter out the unit time points where the collected monitoring values ​​of each power consumption parameter in each detection period of each day during the current self-test duration period of the target terminal are invalid monitoring values, count the corresponding duration of the invalid monitoring values ​​of each power consumption parameter in each detection period of each day during the current self-test duration period of the target terminal, perform ratio analysis on it with the unit detection period duration, and obtain the corresponding duration ratio of the invalid monitoring values ​​of each power consumption parameter in each detection period of each day during the current self-test duration period of the target terminal. , according to the formula Get the data collection completeness of each detection period on each day during the current self-test duration period of the target terminal.

[0042] Exemplarily, the invalid monitoring value of the electricity usage parameter is specifically NULL.

[0043] By formula Obtain the data acquisition abnormality risk assessment index within the current self-check duration period of the target terminal.

[0044] The embodiment of the present invention uses data acquisition accuracy and data acquisition completeness as key indicators of data acquisition, and carries out precise assessment of data acquisition abnormality risks within the current self-test duration period of the target dedicated variable acquisition terminal, which helps to discover potential data acquisition problems and prevent the problems from expanding, thereby improving the reliability and accuracy of data acquisition.

[0045] S4. Construct the direct correlation coefficient of each environmental parameter for each key communication indicator of the target terminal, and predict the communication anomaly risk of the target terminal within the preset self-check interval period in the future.

[0046] Specifically, the direct correlation coefficient of each environmental parameter for each key communication indicator of the target terminal is constructed, including: extracting the ambient temperature value of each detection period of each day within the current self-test duration period of the target terminal, finding the overall communication success rate of the target terminal in the corresponding detection period of the corresponding day to form an observation pair, arranging the positions in numerical order to obtain the rank level of the ambient temperature value and the overall communication success rate in the observation pair, subtracting the rank level of the ambient temperature value and the overall communication success rate in the observation pair to obtain the rank difference of the observation pair, and calculating the rank difference of the observation pair corresponding to each detection period of each day within the current self-test duration period of the target terminal. , according to the formula Get the direct correlation coefficient of the ambient temperature value to the overall communication success rate of the target terminal, It is the correlation correction factor of the ambient temperature value to the overall communication success rate of the target terminal.

[0047] It should be noted that the formation process of the above observation pair is: extract the ambient temperature value and the overall communication success rate of each detection period of each day in the current self-test duration period of the target terminal, and form the ambient temperature value and the overall communication success rate of the same detection period of the same day into an observation pair. The observation pair can be specifically expressed as ,in The target terminal is the first Tiandi The ambient temperature value during the detection period.

[0048] According to the direct correlation coefficient analysis method of the ambient temperature value for the overall communication success rate of the target terminal, the direct correlation coefficient of each environmental parameter for each key communication indicator of the target terminal is constructed.

[0049] Specifically, the The acquisition process includes: extracting the direct correlation coefficient of the ambient temperature value recorded in each historical self-test duration period of the target terminal stored in the WEB cloud for the overall communication success rate of the target terminal, substituting it into a rectangular coordinate system with time as the horizontal axis, a preset self-test duration period as the unit horizontal axis span, and the direct correlation coefficient of the ambient temperature value for the overall communication success rate of the target terminal as the vertical axis, obtaining the change fitting function of the direct correlation coefficient of the ambient temperature value for the overall communication success rate of the target terminal and substituting it into the current self-test duration period, obtaining the reference direct correlation coefficient of the ambient temperature value of the current self-test duration period for the overall communication success rate of the target terminal , according to the formula The correlation correction factor of the ambient temperature value for the overall communication success rate of the target terminal is obtained.

[0050] It should be noted that the above-mentioned fitting function of the change of the direct correlation coefficient of the ambient temperature value to the overall communication success rate of the target terminal is obtained by importing the change curve of the direct correlation coefficient of the ambient temperature value to the overall communication success rate of the target terminal in the rectangular coordinate system into Matlab software and using its best fitting function tool.

[0051] Specifically, the prediction of the communication abnormality risk of the target terminal within the preset self-check interval period in the future includes: extracting the performance value of each key communication indicator of each detection period of each day in the current self-check duration period of the target terminal, and using the formula , , Calculate the average performance value of each key communication indicator during the current self-test duration period of the target terminal.

[0052] The environmental status data of each detection period on each day during the current self-test duration period of the target terminal are extracted. The average monitoring value of each environmental parameter during the current self-test duration period of the target terminal is calculated in the same way as the average performance value of each key communication indicator during the current self-test duration period of the target terminal.

[0053] The year-on-year deviations of the environmental parameters in the future preset self-check interval period of the target terminal relative to the average monitoring values ​​of the corresponding environmental parameters in the current self-check duration period are respectively recorded as , combined with the direct correlation coefficient of each environmental parameter for each key communication indicator of the target terminal, the predicted performance value of each key communication indicator of the target terminal in the future preset self-test interval period is calculated, which are recorded as , according to the formula Obtain the communication anomaly risk prediction index of the target terminal within the future preset self-check interval period.

[0054] It should be noted that the specific process of predicting the year-on-year deviation value of each environmental parameter in the future preset self-test interval period of the target terminal relative to the average monitoring value of the corresponding environmental parameter in the current self-test duration period includes: obtaining the start date and end date of the future preset self-test interval period, finding the maximum ambient temperature value, minimum ambient temperature value and average ambient temperature value of a single day from the same start date to the same end date of each historical year of the target terminal, further calculating the mean of the maximum ambient temperature value, the minimum ambient temperature value and the average ambient temperature value, and obtaining the reference ambient temperature value from the same start date to the same end date of each historical year of the target terminal, and subtracting the difference from the corresponding average monitoring value of the ambient temperature in the current self-test duration period to obtain the year-on-year deviation value of the ambient temperature in the future preset self-test interval period of the target terminal relative to the corresponding average monitoring value of the ambient temperature in the current self-test duration period. Similarly, obtaining the year-on-year deviation value of the ambient humidity in the future preset self-test interval period of the target terminal relative to the corresponding average monitoring value of the ambient humidity in the current self-test duration period.

[0055] Retrieve the environmental electromagnetic interference intensity of each detection period on each day within each historical self-test duration cycle of the target terminal, combine it with the environmental electromagnetic interference intensity of each detection period on each day within the current self-test duration cycle of the target terminal, substitute it into a rectangular coordinate system with time as the horizontal axis, unit detection period duration as the unit horizontal axis span, and environmental electromagnetic interference intensity as the vertical axis, draw a curve of the change of environmental electromagnetic interference intensity of the target terminal and obtain its corresponding best fitting function, so as to obtain the predicted environmental electromagnetic interference intensity of each detection period on each day of the future preset self-test interval period of the target terminal, and average it after subtracting it from the average monitored value of the corresponding environmental electromagnetic interference intensity in the current self-test duration cycle, so as to obtain the year-on-year deviation value of the environmental electromagnetic interference intensity in the future preset self-test interval period of the target terminal relative to the average monitored value of the corresponding environmental electromagnetic interference intensity in the current self-test duration cycle.

[0056] It should also be noted that the calculation process of the predicted performance value of each key communication indicator within the future preset self-test interval period of the target terminal can refer to the calculation process of the predicted performance value of the communication success rate within the future preset self-test interval period of the target terminal, and the calculation formula is: ,in They are the direct correlation coefficients of the ambient temperature value, ambient humidity value, and ambient electromagnetic interference intensity for the communication success rate of the target terminal.

[0057] The embodiment of the present invention comprehensively considers the impact of environmental changes on the communication performance of the target dedicated transformer acquisition terminal, and makes a forward-looking prediction of the risk of communication anomalies within a future preset self-test interval period, which helps operation and maintenance personnel to promptly discover and deal with potential problems, avoid the occurrence of serious faults such as communication interruption or data loss, and thus improve the communication stability and reliability of the dedicated transformer acquisition terminal, and ensure the normal operation of the power system.

[0058] S5. Construct direct correlation coefficients of various environmental parameters and communication key indicators for each data acquisition key indicator of the target terminal, and predict the data acquisition abnormality risk of the target terminal within the preset self-test interval period in the future.

[0059] Specifically, the direct correlation coefficients of each environmental parameter and each communication key indicator for each data acquisition key indicator of the target terminal are constructed, which are consistent with the direct correlation coefficient analysis method of each environmental parameter for each communication key indicator of the target terminal, and the direct correlation coefficients of each environmental parameter for each data acquisition key indicator of the target terminal and each communication key indicator for each data acquisition key indicator of the target terminal are constructed, which are respectively recorded as ,in is the number of each environmental parameter, , is the number of each key indicator of the data collection, , is the number of each key communication indicator, .

[0060] Extract the direct correlation coefficient of each environmental parameter for each key communication indicator of the target terminal , combined with , expand the product calculation in matrix form to obtain the indirect correlation coefficient of each environmental parameter for each key indicator of the target terminal ,Depend on and The difference between the two values ​​can be used to obtain the direct correlation coefficient of each environmental parameter for each key indicator of the target terminal.

[0061] It should be noted that after the product calculation is expanded in matrix form, each element in the new matrix after the product calculation needs to be normalized so that the value range of each positive element is within Between, so that the value range of each negative element is between between.

[0062] Specifically, the prediction of the data acquisition abnormality risk of the target terminal within a future preset self-test interval period includes: calculating the average performance value of each key data acquisition indicator within the current self-test duration period of the target terminal, combining the average monitoring value of each environmental parameter within the current self-test duration period of the target terminal and the direct correlation coefficient of each environmental parameter to each key data acquisition indicator of the target terminal, and calculating the first-order prediction performance value of each key data acquisition indicator within the future preset self-test interval period of the target terminal.

[0063] Extract the predicted performance value of each key communication indicator within the preset self-test interval period of the target terminal in the future, calculate the year-on-year deviation value of each key communication indicator within the preset self-test interval period of the target terminal for the average performance value of the corresponding key communication indicator within the current self-test duration period, combine the direct correlation coefficient of each key communication indicator with each key data acquisition indicator of the target terminal, calculate the second-order predicted performance value of each key data acquisition indicator within the preset self-test interval period of the target terminal in the future, calculate the average of the first-order and second-order predicted performance values, and obtain the predicted performance value of each key data acquisition indicator within the preset self-test interval period of the target terminal, which are recorded as , according to the formula Obtain the data acquisition abnormal risk prediction index of the target terminal within the future preset self-check interval period.

[0064] The embodiment of the present invention combines the impact of environmental changes and communication performance changes on the data collection of the target dedicated variable acquisition terminal, and makes a forward-looking prediction of the data collection abnormality risks within the future preset self-test interval period, so that operation and maintenance personnel can understand possible data collection problems in advance, and provide strong support for formulating response measures and preventive maintenance plans.

[0065] S6. Provide feedback and warning on the communication abnormality risk and data acquisition abnormality risk within the current self-test duration period of the target terminal and within the future preset self-test interval period.

[0066] See also Figure 3 As shown, the second aspect of the present invention provides a storage medium, which stores one or more programs. The one or more programs can be executed by one or more processors to implement the steps in the special transformer acquisition terminal operation data analysis method described in the present invention.

[0067] The above contents are merely examples and explanations of the structure of the present invention. The technicians in this technical field may make various modifications or additions to the specific embodiments described or replace them in a similar manner. As long as they do not deviate from the structure of the invention or exceed the scope defined by the present invention, they should all fall within the protection scope of the present invention.

Claims

1. A method for analyzing operation data of a dedicated transformer collection terminal, characterized in that: The method includes: S1. Record the target special variable acquisition terminal as the target terminal, and formulate a self-inspection plan for it, including a preset self-inspection date sequence, a preset self-inspection duration period, and a preset self-inspection interval period; S2. Conduct a self-inspection process for the target terminal for a preset self-inspection duration period on the current self-inspection date, and collect state data and collection data for each test period on each day of the current self-inspection duration period of the target terminal, where the state data includes communication state data and environmental state data; S3. Analyze the performance values ​​of each key communication indicator and each key data acquisition indicator in each detection period of each day during the current self-test duration period of the target terminal, and evaluate the communication abnormality risk and data acquisition abnormality risk of the target terminal during the current self-test duration period; S4. Construct the direct correlation coefficient of each environmental parameter for each key communication indicator of the target terminal, and predict the communication abnormality risk of the target terminal within the preset self-check interval period in the future; S5. Construct direct correlation coefficients of each environmental parameter and each key communication indicator for each key data acquisition indicator of the target terminal, and predict the abnormal data acquisition risk of the target terminal within the preset self-test interval period in the future; S6. Provide feedback and warning on the communication abnormality risk and data acquisition abnormality risk within the current self-test duration period of the target terminal and within the future preset self-test interval period; The communication status data includes the total amount of information transmitted between the user terminal and the target terminal, the amount of information successfully transmitted, the total amount of data packets transmitted, the amount of data packets successfully transmitted, and the average transmission delay time of successfully transmitted data packets; The collected data includes the collected monitoring values ​​of each power consumption parameter at each unit time point; The environmental status data includes environmental temperature value, environmental humidity value and environmental electromagnetic interference intensity; The evaluation of the communication abnormality risk within the current self-check duration period of the target terminal includes: taking the ratio of the amount of successfully transmitted information to the total amount of transmitted information as the communication success rate, taking the ratio of the difference between the total amount of transmitted data packets and the amount of successfully transmitted data packets to the total amount of transmitted data packets as the communication packet loss rate, and taking the ratio of the average transmission delay time of successfully transmitted data packets to a preset reasonable threshold value of data packet transmission time as the communication delay rate; The communication success rate, packet loss rate and delay rate between the user terminal and the target terminal, and between the target terminal and the main station are obtained in each detection period of each day during the current self-test period of the target terminal. Based on the communication link influence weights between the user terminal and the target terminal, and between the target terminal and the main station, the overall communication success rate of each detection period of each day during the current self-test period of the target terminal is calculated. , overall communication delay rate and the overall communication packet loss rate , as the performance value of each key communication indicator in each detection period of each day during the current self-test duration period of the target terminal, It is the number of each day in the current self-test duration cycle. , is the number of each detection period, ; By formula Obtain the communication anomaly risk assessment index within the current self-check duration period of the target terminal, where The number of days for the current self-test cycle. is the number of detection periods, is a natural constant, They are respectively a reasonable threshold value of the overall communication success rate, an allowable threshold value of the overall communication delay rate and an allowable threshold value of the overall communication packet loss rate within the preset detection period of the dedicated transformer acquisition terminal; The evaluation of the data acquisition abnormality risk during the current self-test duration period of the target terminal includes: obtaining the actual monitoring value of each power consumption parameter at each unit time point during each test period of each day during the current self-test duration period of the user terminal, comparing it with the corresponding collected monitoring value of the target terminal, and analyzing the data acquisition accuracy of each test period of each day during the current self-test duration period of the target terminal. and data acquisition completeness , and use it as the key indicator performance value of each data acquisition period in each day during the current self-test duration period of the target terminal; By formula Obtain the data acquisition abnormality risk assessment index within the current self-check duration period of the target terminal; The direct correlation coefficient of each environmental parameter for each key communication indicator of the target terminal is constructed, including: extracting the ambient temperature value of each detection period of each day in the current self-test duration period of the target terminal, finding the overall communication success rate of the target terminal in the corresponding detection period of the corresponding day to form an observation pair, arranging the positions in numerical order to obtain the rank level of the ambient temperature value and the overall communication success rate in the observation pair, and calculating the rank difference of the corresponding observation pair of each detection period of each day in the current self-test duration period of the target terminal. , according to the formula Get the direct correlation coefficient of the ambient temperature value to the overall communication success rate of the target terminal, is the correlation correction factor of the ambient temperature value to the overall communication success rate of the target terminal; According to the direct correlation coefficient analysis method of the ambient temperature value for the overall communication success rate of the target terminal, the direct correlation coefficient of each environmental parameter for each key communication indicator of the target terminal is constructed; Said The acquisition process includes: extracting the direct correlation coefficient of the ambient temperature value recorded in each historical self-test duration period of the target terminal stored in the WEB cloud for the overall communication success rate of the target terminal, substituting it into a rectangular coordinate system with time as the horizontal axis, a preset self-test duration period as the unit horizontal axis span, and the direct correlation coefficient of the ambient temperature value for the overall communication success rate of the target terminal as the vertical axis, obtaining the change fitting function of the direct correlation coefficient of the ambient temperature value for the overall communication success rate of the target terminal and substituting it into the current self-test duration period, obtaining the reference direct correlation coefficient of the ambient temperature value of the current self-test duration period for the overall communication success rate of the target terminal , according to the formula Obtaining a correlation correction factor of the ambient temperature value with respect to the overall communication success rate of the target terminal; The predicting of the communication abnormality risk of the target terminal within a preset self-check interval period in the future includes: calculating the average performance value of each key communication indicator and the average monitoring value of each environmental parameter within the current self-check duration period of the target terminal; Predict the year-on-year deviation of each environmental parameter in the future preset self-test interval period of the target terminal for the average monitoring value of the corresponding environmental parameter in the current self-test duration period, and combine the direct correlation coefficient of each environmental parameter for each key communication indicator of the target terminal to calculate the predicted performance value of each key communication indicator in the future preset self-test interval period of the target terminal, which are recorded as , according to the formula Obtaining a communication anomaly risk prediction indicator for the target terminal within a preset self-check interval period in the future; The direct correlation coefficients of each environmental parameter and each communication key indicator for each data acquisition key indicator of the target terminal are constructed, which are consistent with the direct correlation coefficient analysis method of each environmental parameter for each communication key indicator of the target terminal, and the direct correlation coefficients of each environmental parameter for each data acquisition key indicator of the target terminal and each communication key indicator for each data acquisition key indicator of the target terminal are constructed, which are respectively recorded as ,in is the number of each environmental parameter, , is the number of each key indicator of the data collection, , is the number of each key communication indicator, ; Extract the direct correlation coefficient of each environmental parameter for each key communication indicator of the target terminal , combined with , expand the product calculation in matrix form to obtain the indirect correlation coefficient of each environmental parameter for each key indicator of the target terminal ,Depend on and The difference between the two values ​​is used to obtain the direct correlation coefficient of each environmental parameter for each key indicator of data acquisition of the target terminal; The method of predicting the data acquisition abnormality risk of the target terminal within a preset self-check interval period in the future includes: calculating the average performance value of each key data acquisition indicator within the current self-check duration period of the target terminal, combining the average monitoring value of each environmental parameter within the current self-check duration period of the target terminal and the direct correlation coefficient of each environmental parameter with respect to each key data acquisition indicator of the target terminal, and calculating the first-order prediction performance value of each key data acquisition indicator within the preset self-check interval period of the target terminal in the future; Extract the predicted performance value of each key communication indicator within the preset self-test interval period of the target terminal in the future, calculate the year-on-year deviation value of each key communication indicator within the preset self-test interval period of the target terminal for the average performance value of the corresponding key communication indicator within the current self-test duration period, combine the direct correlation coefficient of each key communication indicator with each key data acquisition indicator of the target terminal, calculate the second-order predicted performance value of each key data acquisition indicator within the preset self-test interval period of the target terminal in the future, calculate the average of the first-order and second-order predicted performance values, and obtain the predicted performance value of each key data acquisition indicator within the preset self-test interval period of the target terminal, which are recorded as , according to the formula Obtain the data acquisition abnormal risk prediction index of the target terminal within the future preset self-check interval period.

2. A storage medium, characterized in that: The storage medium stores one or more programs, and the one or more programs can be executed by one or more processors to implement the steps in the special transformer acquisition terminal operation data analysis method as claimed in claim 1.

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