Data quality monitoring storage system based on equipment electrical status assessment

Abstract

The present invention discloses a data quality monitoring and storage system based on equipment electrical state evaluation, and relates to the technical field of data quality monitoring and storage. The data quality monitoring and storage system based on equipment electrical state evaluation includes: an environmental state evaluation module, a cabinet state interference evaluation module, a cabinet defect evaluation module and a data storage module. The present invention performs environmental state evaluation and determines whether to perform environmental interference adjustment, then performs cabinet state interference evaluation and determines whether to perform cabinet state interference adjustment, then performs cabinet defect evaluation to obtain cabinet heating defect evaluation coefficient and determines whether to perform defect optimization, and finally stores the obtained qualified cabinet data, thereby achieving the effect of improving the accuracy of electrical state data acquisition and storage quality monitoring of high-voltage switch cabinets, and solving the problem of low accuracy of electrical state data acquisition and storage quality monitoring of high-voltage switch cabinets in the prior art.

Description

Technical Field

[0001] The present invention relates to the technical field of data quality monitoring storage, and in particular to a data quality monitoring storage system based on equipment electrical state evaluation. Background Art

[0002] With the advancement of smart grid construction, online monitoring of power equipment has been greatly developed and has become a trend. The monitoring data has become increasingly large, gradually forming big data for power equipment monitoring. This brings great technical challenges to the online monitoring system of power equipment in terms of data storage and processing. Therefore, efficient data storage technology is needed to meet the storage needs of massive data. Data quality monitoring is an important link to ensure data accuracy, integrity, timeliness and consistency. Equipment electrical status assessment refers to the dynamic monitoring of various parameters, working conditions and life of electrical equipment, and the evaluation of its reliability and safety. High-voltage switchgear is indeed prone to internal insulation degradation after long-term operation in harsh environments such as high temperature, high humidity, and haze. This degradation will cause the insulation performance of the switchgear electrical equipment to deteriorate and the voltage tolerance to decrease, thereby increasing the risk of failure. With the rapid development of modern power systems, the status assessment and prediction technology of power equipment has become an important research direction in the power industry. In the electrical status assessment of equipment, data quality directly affects the accuracy and reliability of the assessment results.

[0003] The existing system mainly installs sensors on key electrical equipment to collect the electrical status data of the equipment, such as current, voltage, power factor, etc. The data output by the sensor is collected in real time through a data collector or monitoring system and transmitted to a data storage system.

[0004] For example, the invention patent application with publication number: CN112561226A discloses a novel comprehensive evaluation method for the operating status of a high-voltage switchgear, comprising: step one, setting the operating status level of the high-voltage switchgear and constructing an operating status evaluation index system for the high-voltage switchgear; step two, using the fuzzy set value statistical method to determine the subjective weight of the evaluation index, obtaining the initial weight, and dynamically correcting the initial weight using the entropy method; step three, establishing a standard matrix for evaluating the operating status of the switchgear, and using the Gaussian kernel function to map the evaluation samples of the input space to the high-dimensional feature space, establishing a vector space model in the high-dimensional feature space, and using the vector space model to obtain the closeness between the input sample and the standard sample, and obtaining the comprehensive evaluation result of the high-voltage switchgear status according to the closeness.

[0005] For example, the invention patent application with publication number CN116050888A discloses a method for health status assessment of sensors in intelligent high-voltage switchgear, including: obtaining sensor data, cleaning and processing the data; using an unsupervised clustering algorithm to distinguish different health status data based on the data collected by the sensor, and constructing a health status assessment data set; using a tensor fusion network to perform multimodal information learning based on the processed sensor data to obtain the correlation between different modal data; and evaluating the historical working status of the high-voltage switchgear through a health status assessment inference sub-network to determine whether it can continue to operate healthily.

[0006] However, in the process of implementing the technical solution of the invention in the embodiments of the present application, the present application found that the above technology has at least the following technical problems:

[0007] In the prior art, due to the existence of an electromagnetic interference environment, the quality of feature extraction based on detection data of the high-voltage switchgear is affected, resulting in the problem of low accuracy in the quality monitoring of the electrical status data collection and storage of the high-voltage switchgear. Summary of the invention

[0008] The embodiment of the present application solves the problem of low accuracy of electrical status data collection and storage quality monitoring of high-voltage switchgear in the prior art by providing a data quality monitoring and storage system based on equipment electrical status assessment, thereby improving the accuracy of electrical status data collection and storage quality monitoring of high-voltage switchgear.

[0009] The embodiment of the present application provides a data quality monitoring and storage system based on equipment electrical status evaluation, including an environmental status evaluation module, a cabinet status interference evaluation module, a cabinet defect evaluation module and a data storage module: wherein the environmental status evaluation module is used to monitor the high-voltage switch cabinet to obtain live detection parameters and environmental detection parameters, perform environmental status evaluation based on the acquired data and determine whether to perform environmental interference adjustment; the cabinet status interference evaluation module is used to obtain cabinet status interference data based on the acquired cabinet status parameters and qualified environmental evaluation coefficients, perform cabinet status interference evaluation based on the cabinet status interference data and determine whether to perform cabinet status interference Disturbance adjustment; the cabinet defect assessment module is used to obtain cabinet heating defect assessment data according to the acquired cabinet defect parameters and the qualified cabinet state assessment coefficient, and perform cabinet defect assessment based on the cabinet heating defect assessment data to obtain the cabinet heating defect assessment coefficient and determine whether to perform defect optimization. The qualified cabinet state assessment coefficient represents a cabinet state assessment coefficient that is not lower than a preset cabinet state assessment threshold. The cabinet heating defect assessment coefficient is used to evaluate the abnormal heating condition of the high-voltage switchgear during the monitoring process of the high-voltage switchgear; the data storage module is used to store the acquired qualified cabinet data, and the qualified cabinet data is used for electrical state assessment.

[0010] Furthermore, the live detection parameters include the short-circuit current of the switch cabinet and the magnetic field strength of the switch cabinet; the environmental detection parameters include the external ambient temperature, the external ambient humidity and the cabinet load rate; the cabinet status parameters include the cabinet leakage current, the cabinet stop operation time and the insulation resistance; the cabinet defect parameters include the internal temperature of the cabinet, the heating power of the switch cabinet and the cabinet loop resistance.

[0011] Furthermore, the specific process of conducting environmental status assessment based on the acquired data is as follows: obtaining an interference influence factor by processing the live detection parameters and the preset interference threshold; obtaining environmental detection influence data by processing the environmental detection parameters, the preset environmental detection threshold and the interference influence factor; obtaining an environmental assessment coefficient by processing the environmental detection influence data and the preset environmental detection weight factor obtained from the database; the interference influence factor is used to reflect the degree of electromagnetic interference within a preset time period; the preset interference threshold includes a preset short-circuit current maximum value and a preset magnetic field strength maximum value; the environmental detection influence data includes a temperature influence assessment value, a humidity influence assessment value and a load rate influence assessment value; the environmental detection influence data is used to reflect the influence of the environmental detection parameters by the interference influence factor; the preset environmental detection threshold includes a preset external temperature maximum value, a preset external humidity maximum value and a preset load rate maximum value; the preset environmental detection weight factor includes a temperature weight factor, a humidity weight factor and a load rate weight factor; the environmental assessment coefficient is used to evaluate the degree of environmental monitoring qualification during the monitoring of the high-voltage switchgear.

[0012] Furthermore, the switch cabinet short-circuit current represents the maximum value of the short-circuit current formed by the high-voltage switch cabinet circuit within a preset time period; the cabinet leakage current represents the maximum value of the current leaked by the insulating material of the high-voltage switch cabinet within a preset time period; the cabinet stop operation duration represents the maximum value of the duration during which the high-voltage switch cabinet stops operating due to an abnormality within a preset time period.

[0013] Furthermore, the specific process of determining whether to perform environmental interference adjustment is as follows: determining whether the obtained environmental assessment coefficient is not lower than a preset environmental interference threshold in a database; when the environmental assessment coefficient is not lower than a preset environmental interference threshold, marking the corresponding environmental assessment coefficient as a qualified environmental assessment coefficient, otherwise performing environmental interference adjustment; when the environmental assessment coefficient after environmental interference adjustment is still lower than the preset environmental interference threshold, sending an alarm to a preset person; the environmental interference adjustment includes anti-interference of live detection values ​​and structural shielding.

[0014] Furthermore, the specific process of cabinet state interference assessment based on cabinet state interference data is as follows: cabinet state interference data is obtained by processing environmental interference factors, cabinet state parameters and preset cabinet state thresholds, and the environmental interference factors are obtained by processing qualified environmental assessment coefficients; cabinet state assessment coefficients are obtained by processing cabinet state interference data and preset cabinet state weight factors; the cabinet state interference data include leakage current assessment values, cabinet interruption assessment values ​​and cabinet insulation assessment values; the cabinet state interference data is used to reflect the influence of cabinet state parameters by environmental interference factors; the preset cabinet state threshold includes a preset leakage current maximum value, a preset stop operation time maximum value, and a preset insulation resistance maximum value; the preset cabinet state weight factors include leakage current weight factors, cabinet interruption weight factors and cabinet insulation weight factors; the cabinet state assessment coefficient is used to evaluate the cabinet state qualification degree of the high-voltage switchgear during the monitoring process of the high-voltage switchgear.

[0015] Furthermore, the specific process of determining whether to perform cabinet state interference adjustment is as follows: determining whether the obtained cabinet state assessment coefficient is not lower than the preset cabinet state assessment threshold in the database; if the cabinet state assessment coefficient is not lower than the preset cabinet state assessment threshold, the corresponding cabinet state assessment coefficient is marked as a qualified cabinet state assessment coefficient, otherwise the cabinet state interference adjustment is performed; if the cabinet state assessment coefficient is still lower than the preset cabinet state assessment threshold after the cabinet state interference adjustment, an alarm is sent to the preset personnel; the cabinet state interference adjustment includes insulation defect marking and air gap adjustment.

[0016] Furthermore, the specific process of cabinet defect assessment based on cabinet heating defect assessment data is as follows: obtain cabinet state influencing factor, the cabinet state influencing factor is obtained by processing qualified cabinet state assessment coefficient; obtain cabinet heating defect assessment data by processing cabinet state influencing factor, cabinet defect parameter and preset cabinet defect threshold, the cabinet heating defect assessment data includes cabinet internal temperature assessment value, heating power assessment value and cabinet loop resistance assessment value; the cabinet heating defect assessment data is used to reflect the degree of influence of cabinet defect parameters by cabinet state influencing factor; obtain cabinet heating defect assessment coefficient by processing cabinet heating defect assessment data and preset heating defect weight factor; the preset heating defect weight factor includes cabinet internal temperature weight factor, heating power weight factor and cabinet loop resistance weight factor; the preset cabinet defect threshold includes preset cabinet internal temperature maximum value, preset heating power maximum value and preset cabinet loop resistance maximum value; the cabinet heating defect assessment coefficient is used to evaluate the abnormal heating situation of high-voltage switchgear.

[0017] Furthermore, the specific process of defect optimization is as follows: determine whether the cabinet heating defect assessment coefficient is not higher than the preset heating threshold in the database; when the cabinet heating defect assessment coefficient is not higher than the preset heating threshold, no defect optimization is performed, otherwise defect optimization is performed; when the cabinet heating defect assessment coefficient is still higher than the preset heating threshold after defect optimization, an alarm is sent to the preset personnel; the defect optimization includes node decoupling and overload protection.

[0018] Furthermore, the qualified cabinet data includes qualified environmental detection impact data, qualified cabinet state interference data and qualified cabinet heating defect assessment data; the qualified environmental detection impact data represents the environmental detection impact data corresponding to the cabinet state assessment coefficient which is not lower than the preset cabinet state assessment threshold; the qualified cabinet state interference data represents the cabinet state interference data corresponding to the cabinet state assessment coefficient which is not lower than the preset cabinet state assessment threshold; the qualified cabinet heating defect assessment data represents the cabinet heating defect assessment data corresponding to the cabinet heating defect assessment coefficient which is not higher than the preset heating threshold.

[0019] One or more technical solutions provided in the embodiments of the present application have at least the following technical effects or advantages:

[0020] 1. By performing environmental status assessment and determining whether to perform environmental interference adjustment, then performing cabinet status interference assessment and determining whether to perform cabinet status interference adjustment, then performing cabinet defect assessment to obtain the cabinet heating defect assessment coefficient and determine whether to perform defect optimization, and finally storing the acquired qualified cabinet data, the accuracy of storage of qualified cabinet data is improved, thereby achieving the improvement of the accuracy of electrical status data collection and storage quality monitoring of high-voltage switchgear, and effectively solving the problem of low accuracy of electrical status data collection and storage quality monitoring of high-voltage switchgear in the prior art.

[0021] 2. By processing the environmental detection parameters, preset environmental detection thresholds and interference influencing factors, the environmental detection impact data is obtained, and then the environmental detection impact data and the preset environmental detection weight factors are processed to obtain the environmental assessment coefficient, thereby improving the reliability of evaluating the environmental monitoring qualification level, and further realizing the accurate quantification of the environmental monitoring qualification level during the monitoring process of the high-voltage switchgear.

[0022] 3. By marking the cabinet state assessment coefficient that is not lower than the preset cabinet state assessment threshold as a qualified cabinet state assessment coefficient, the cabinet state assessment coefficient that is lower than the preset cabinet state assessment threshold is adjusted for cabinet state interference, thereby improving the cabinet state qualification degree of the high-voltage switch cabinet, and further improving the accuracy of evaluating the cabinet state qualification degree of the high-voltage switch cabinet. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] Figure 1 A schematic diagram of the structure of a data quality monitoring storage system based on equipment electrical status evaluation provided in an embodiment of the present application;

[0024] Figure 2 A statistical diagram of changes in external environment temperature-temperature impact assessment value provided in an embodiment of the present application;

[0025] Figure 3 A schematic diagram of a multivariate data fusion state assessment model provided in an embodiment of the present application. DETAILED DESCRIPTION

[0026] The embodiment of the present application solves the problem of low accuracy of electrical status data collection and storage quality monitoring of high-voltage switchgear in the prior art by providing a data quality monitoring and storage system based on equipment electrical status assessment. The system monitors the high-voltage switchgear to obtain live detection parameters and environmental detection parameters, then performs environmental status assessment based on the acquired data and determines whether to perform environmental interference adjustment. Subsequently, cabinet status interference data is obtained based on the acquired cabinet status parameters and qualified environmental assessment coefficients. Cabinet status interference assessment is performed based on the cabinet status interference data and determines whether to perform cabinet status interference adjustment. Cabinet heating defect assessment data is obtained based on the acquired cabinet defect parameters and qualified cabinet status assessment coefficients. Cabinet defect assessment is performed based on the cabinet heating defect assessment data to obtain cabinet heating defect assessment coefficients and determine whether to perform defect optimization. Finally, the acquired qualified cabinet data is stored, thereby improving the accuracy of electrical status data collection and storage quality monitoring of the high-voltage switchgear.

[0027] The technical solution in the embodiment of the present application is to solve the problem of low accuracy of electrical state data collection and storage quality monitoring of the above-mentioned high-voltage switch cabinet. The overall idea is as follows:

[0028] By performing an environmental status assessment and determining whether to make environmental interference adjustments, then performing a cabinet status interference assessment and determining whether to make cabinet status interference adjustments, then performing a cabinet defect assessment to obtain the cabinet heating defect assessment coefficient and determine whether to perform defect optimization, and finally storing the acquired qualified cabinet data, the accuracy of electrical status data collection and storage quality monitoring of the high-voltage switchgear is achieved.

[0029] In order to better understand the above technical solution, the above technical solution will be described in detail below in conjunction with the accompanying drawings and specific implementation methods.

[0030] like Figure 1As shown, it is a structural schematic diagram of the data quality monitoring and storage system based on equipment electrical status evaluation provided by an embodiment of the present application, including an environmental status evaluation module, a cabinet status interference evaluation module, a cabinet defect evaluation module and a data storage module: wherein the environmental status evaluation module is used to monitor the high-voltage switch cabinet to obtain live detection parameters and environmental detection parameters, perform environmental status evaluation based on the acquired data and determine whether to perform environmental interference adjustment; the cabinet status interference evaluation module is used to obtain cabinet status interference data based on the acquired cabinet status parameters and the qualified environmental evaluation coefficient, perform cabinet status interference evaluation based on the cabinet status interference data and determine whether to perform cabinet status interference adjustment, and the qualified The environmental assessment coefficient represents an environmental assessment coefficient that is not lower than a preset environmental interference threshold; the cabinet defect assessment module is used to obtain cabinet heating defect assessment data based on the acquired cabinet defect parameters and the qualified cabinet state assessment coefficient, and perform cabinet defect assessment based on the cabinet heating defect assessment data to obtain the cabinet heating defect assessment coefficient and determine whether to perform defect optimization. The qualified cabinet state assessment coefficient represents a cabinet state assessment coefficient that is not lower than a preset cabinet state assessment threshold. The cabinet heating defect assessment coefficient is used to evaluate the abnormal heating condition of the high-voltage switchgear during the monitoring process of the high-voltage switchgear; the data storage module is used to store the acquired qualified cabinet data, and the qualified cabinet data is used for electrical state assessment.

[0031] It should be added that the live detection parameters include the short-circuit current of the switch cabinet and the magnetic field strength of the switch cabinet; the environmental detection parameters include the external ambient temperature, the external ambient humidity and the cabinet load rate; the cabinet status parameters include the cabinet leakage current, the cabinet shutdown time and the insulation resistance; the cabinet defect parameters include the internal temperature of the cabinet, the heating power of the switch cabinet and the cabinet loop resistance; the switch cabinet short-circuit current represents the maximum value of the short-circuit current formed by the high-voltage switch cabinet circuit within the preset time period; the cabinet leakage current represents the maximum value of the current leaked by the insulating material of the high-voltage switch cabinet within the preset time period; the cabinet shutdown time represents the maximum value of the duration of the high-voltage switch cabinet stopping operation due to an abnormality within the preset time period; the live detection parameters are the maximum values ​​of the data obtained within the preset time period, and none of them is 0; the environmental detection parameters are the maximum values ​​of the data obtained within the preset time period, and none of them is 0; the cabinet status parameters are the maximum values ​​of the data obtained within the preset time period, and none of them is 0; the cabinet defect parameters are all the maximum values ​​of the data obtained within the preset time period, and none of them is 0.

[0032] Among them, the maximum value of the short-circuit current of the high-voltage switchgear within a preset time period is analyzed and counted by an ammeter and an oscilloscope to obtain the short-circuit current of the switchgear; the magnetic field induction intensity at a preset position point outside the high-voltage switchgear is measured by a gaussmeter, and its maximum value is counted to obtain the magnetic field strength of the switchgear; the temperature of the preset position point outside the high-voltage switchgear within a preset time period is measured by a temperature sensor, and its maximum value is counted to obtain the external ambient temperature; the humidity of the preset position point outside the high-voltage switchgear within a preset time period is measured by a humidity sensor, and its maximum value is counted to obtain the external ambient humidity; the current and voltage at the preset position point of the outlet end of the high-voltage switchgear within a preset time period are monitored by a power quality analyzer and the maximum value of the load rate of the high-voltage switchgear is obtained to obtain the cabinet load rate.

[0033] The current at a preset position point on the insulation layer of the high-voltage switchgear in a preset time period is measured by a leakage current tester, and its maximum value is counted to obtain the cabinet leakage current; the maximum value of the high-voltage switchgear stopping operation in a preset time period is recorded by a timer to obtain the cabinet stopping operation duration; the resistance at a preset position point between the conductive circuit of the high-voltage switchgear and the ground in a preset time period is measured by an insulation resistance tester, and its maximum value is counted to obtain the insulation resistance.

[0034] The temperature of a preset position point inside the high-voltage switchgear within a preset time period is measured by a temperature sensor, and its maximum value is counted to obtain the temperature inside the cabinet; the heating power of the high-voltage switchgear within a preset time period is analyzed by an electric power monitor, and its maximum value is counted to obtain the heating power of the switchgear; the loop resistance of the high-voltage switchgear within a preset time period is measured by a loop resistance tester, and its maximum value is counted to obtain the cabinet loop resistance.

[0035] In this embodiment, when the environmental assessment coefficient obtained by the environmental status assessment module is lower than the preset environmental interference threshold, environmental interference adjustment needs to be performed; the cabinet state interference assessment module further obtains the cabinet state assessment coefficient through the environmental assessment coefficient obtained after environmental interference adjustment, and when the cabinet state assessment coefficient is lower than the preset cabinet state assessment threshold in the database, cabinet state interference adjustment needs to be performed; the cabinet defect assessment module further obtains the cabinet heating defect assessment coefficient through the cabinet state assessment coefficient obtained after cabinet state interference adjustment, and when the cabinet heating defect assessment coefficient is higher than the preset heating threshold, defect optimization needs to be performed, and finally the acquired qualified cabinet data is stored through the data storage module. The environmental status assessment module, the cabinet state interference assessment module, the cabinet defect assessment module and the data storage module jointly complete the comprehensive monitoring, evaluation and adjustment of the high-voltage switch cabinet through data transmission and interaction, thereby realizing the improvement of the accuracy of the electrical state data acquisition and storage quality monitoring of the high-voltage switch cabinet.

[0036] It needs to be explained that the high-voltage switchgear in the present embodiment may be a pneumatic ring network switchgear. By storing the qualified cabinet data corresponding to the pneumatic ring network switchgear, it is possible to establish an equipment database corresponding to the pneumatic ring network switchgear, and perform data statistics and data analysis on the detection data and overall situation of the switchgear in the entire power grid. The stored qualified cabinet data will be used as historical data for the next status assessment of the pneumatic ring network switchgear, which is beneficial for the power-related departments to grasp the overall operating status of the equipment.

[0037] Furthermore, the specific process of evaluating the environmental status according to the acquired data is as follows: the interference influence factor is obtained by processing the live detection parameters and the preset interference threshold; the environmental detection influence data is obtained by processing the environmental detection parameters, the preset environmental detection threshold and the interference influence factor; the environmental assessment coefficient is obtained by processing the environmental detection influence data and the preset environmental detection weight factor obtained from the database; the interference influence factor is used to reflect the degree of electromagnetic interference within a preset time period; the preset interference threshold includes the preset short-circuit current maximum value and the preset magnetic field strength maximum value obtained from the database; the environmental detection influence data includes the temperature influence assessment value, the humidity influence assessment value and the load rate influence assessment value; the environment The environmental detection impact data is used to reflect the influence of interference factors on environmental detection parameters; the preset environmental detection threshold includes the preset external temperature maximum value, the preset external humidity maximum value and the preset load rate maximum value obtained from the database; the preset environmental detection weight factors include temperature weight factor, humidity weight factor and load rate weight factor; the temperature weight factor is used to describe the influence of the temperature impact assessment value on the environmental assessment coefficient; the humidity weight factor is used to describe the influence of the humidity impact assessment value on the environmental assessment coefficient; the load rate weight factor is used to describe the influence of the load rate impact assessment value on the environmental assessment coefficient; the environmental assessment coefficient is used to evaluate the environmental monitoring qualification degree during the monitoring of high-voltage switchgear.

[0038] Among them, the restricted expression of the environmental assessment coefficient is as follows:

[0039] ;

[0040] ;

[0041] ;

[0042] ;

[0043] In the formula, Indicates Environmental assessment coefficient within a preset time period, , Indicates the number of the preset time period, Indicates the total number of preset time periods. Indicates The temperature impact assessment value within a preset time period, Indicates The humidity impact assessment value within a preset time period, Indicates The load factor in a preset time period affects the evaluation value. represents the temperature weight factor, represents the humidity weight factor, represents the load rate weight factor, e represents the natural constant, Indicates The interference factor within a preset time period, Indicates The short-circuit current of the switch cabinet within a preset time period, Indicates The magnetic field strength of the switch cabinet within a preset time period, Indicates The external environment temperature within a preset time period, Indicates The external environment humidity within a preset time period, Indicates The cabinet load rate within a preset time period, Indicates the preset maximum short-circuit current. Indicates the preset maximum magnetic field strength. Indicates the preset maximum external temperature. Indicates the preset maximum external humidity. Indicates the preset maximum load factor.

[0044] In this embodiment, the aforementioned database is a database for storing various types of setting data in the data quality monitoring storage system based on equipment electrical status assessment provided in the embodiment of the present application. The database includes but is not limited to a preset maximum external temperature, a preset maximum external humidity, and a preset maximum load rate, etc., wherein various numerical values ​​are directly set by technical personnel; for example, the preset maximum short-circuit current is represented by the maximum value of the short-circuit current of the high-voltage switch cabinet loop in the historical time period, the preset maximum magnetic field strength is represented by the maximum value of the magnetic field strength corresponding to the high-voltage switch cabinet in the historical time period, the preset maximum external temperature is represented by the maximum value of the external temperature corresponding to the high-voltage switch cabinet in the historical time period, the preset maximum external humidity is represented by the maximum value of the external humidity corresponding to the high-voltage switch cabinet in the historical time period, and the preset maximum load rate is represented by the maximum value of the load rate corresponding to the high-voltage switch cabinet in the historical time period.

[0045] Specifically, assuming the interference factor Fixed to 0.15, external ambient temperature The range is 40-45 (Celsius), the preset maximum external temperature Fixed to 45 degrees Celsius, such as Figure 2 As shown, it is a statistical diagram of the change of the external environment temperature-temperature impact evaluation value provided in the embodiment of the present application, which is composed of Figure 2 It can be seen that as the external ambient temperature gradually increases, the temperature impact assessment value gradually increases, which means that the degree to which the high-voltage switchgear is affected by external temperature and electromagnetic interference gradually increases.

[0046] It should be explained that the present embodiment provides a mapping set, which is obtained from a database. The mapping relationship in the mapping set can be a one-to-one correspondence or a many-to-one relationship. The mapping relationship in the mapping set is: the temperature impact assessment value, the humidity impact assessment value and the load rate impact assessment value correspond to the temperature weight factor, the humidity weight factor and the load rate weight factor respectively. By inputting the real-time temperature impact assessment value, the humidity impact assessment value and the load rate impact assessment value into the mapping set, the corresponding temperature weight factor, humidity weight factor and load rate weight factor can be obtained; for example, in the present embodiment, the value range of the weights involved is 0-1.

[0047] The algorithm of this embodiment combines the environmental detection impact data analysis to obtain the environmental assessment coefficient. The greater the short-circuit current of the switch cabinet and the magnetic field strength of the switch cabinet, the greater the impact of electromagnetic interference on the external environment of the high-voltage switch cabinet, resulting in a decrease in the environmental assessment coefficient; the greater the external environmental temperature and the external environmental humidity, the greater the possibility of failure of the high-voltage switch cabinet, resulting in a decrease in the environmental assessment coefficient; the greater the cabinet load rate, the greater the possibility of overload of the high-voltage switch cabinet, resulting in a decrease in the environmental assessment coefficient. In summary, the environmental detection impact data is inversely proportional to the environmental assessment coefficient.

[0048] The environmental detection impact data in the algorithm of this embodiment does not exist independently, and the variables are interrelated, which requires comprehensive analysis. When the magnetic field strength of the high-voltage switch cabinet is stronger, the short-circuit current of the high-voltage switch cabinet may increase, which may in turn aggravate electromagnetic interference; when the current passes through the conductor of the high-voltage switch cabinet, heat will be generated, and the increase in magnetic field strength may also lead to increased electromagnetic loss, further generating heat, resulting in an increase in the internal and external environmental temperature of the high-voltage switch cabinet; and when the high temperature time is longer, the external environmental humidity may be lower; when the cabinet load rate increases, the short-circuit current in the high-voltage switch cabinet may also increase, thereby generating a stronger magnetic field. By analyzing the comprehensive influence between the parameters, an accurate assessment of the degree of detection qualification during the monitoring process of the high-voltage switch cabinet is achieved, thereby improving the accuracy of the electrical status data acquisition and storage quality monitoring of the high-voltage switch cabinet.

[0049] Furthermore, the specific process of determining whether to perform environmental interference adjustment is as follows: determining whether the obtained environmental assessment coefficient is not lower than the preset environmental interference threshold in the database; when the environmental assessment coefficient is not lower than the preset environmental interference threshold, marking the corresponding environmental assessment coefficient as a qualified environmental assessment coefficient, otherwise performing environmental interference adjustment; when the environmental assessment coefficient after environmental interference adjustment is still lower than the preset environmental interference threshold, sending an alarm to the preset personnel; environmental interference adjustment includes live detection value anti-interference and structural shielding; live detection value anti-interference means reducing electromagnetic interference through a live detection value anti-interference algorithm; structural shielding means sending a prompt to the preset personnel to isolate the electromagnetic interference source (such as contact action, insulating discharge) from sensitive equipment (such as control circuit).

[0050] In this embodiment, the preset environmental interference threshold is represented by an average value of environmental assessment coefficients in a historical time period.

[0051] The impact of electromagnetic interference is reduced by isolating the electromagnetic interference source from sensitive equipment. In high-voltage switchgear, the electromagnetic interference source may include contact action, insulation discharge, etc., while the sensitive equipment may be the control circuit, etc. In order to reduce electromagnetic interference, the electromagnetic interference source is physically isolated from the sensitive equipment by setting a metal shielding layer at a preset position by preset personnel.

[0052] By using an anti-interference algorithm for live detection values, such as an anti-interference algorithm based on digital filtering technology, the digital signal of the high-voltage switchgear is filtered through this algorithm, which can significantly reduce the impact of electromagnetic interference, improve the accuracy and reliability of detection, and thereby achieve improved accuracy in the electrical status data collection and storage quality monitoring of the high-voltage switchgear.

[0053] Furthermore, the specific process of cabinet state interference evaluation based on cabinet state interference data is as follows: the cabinet state interference data is obtained by processing the environmental interference factor, the cabinet state parameter and the preset cabinet state threshold, and the environmental interference factor is obtained by processing the qualified environment assessment coefficient; the cabinet state assessment coefficient is obtained by processing the cabinet state interference data and the preset cabinet state weight factor obtained from the database; the cabinet state interference data includes the leakage current assessment value, the cabinet interruption assessment value and the cabinet insulation assessment value, and the cabinet state interference data are not 0; the cabinet state interference data is used to reflect the influence of the environmental interference factor on the cabinet state parameters; the preset cabinet state The thresholds include the preset maximum leakage current value, the preset maximum shutdown time value, and the preset maximum insulation resistance value obtained from the database; the preset cabinet state weight factors include the leakage current weight factor, the cabinet interruption weight factor, and the cabinet insulation weight factor; the cabinet state evaluation coefficient is used to evaluate the cabinet state qualification degree of the high-voltage switchgear during the monitoring process of the high-voltage switchgear; the leakage current weight factor is used to reflect the influence of the leakage current evaluation value on the cabinet state evaluation coefficient; the cabinet interruption weight factor is used to reflect the influence of the cabinet interruption evaluation value on the cabinet state evaluation coefficient; the cabinet insulation weight factor is used to reflect the influence of the cabinet insulation evaluation value on the cabinet state evaluation coefficient.

[0054] Among them, the cabinet status assessment coefficient is obtained by the following method:

[0055] ;

[0056] ;

[0057] ;

[0058] ;

[0059] In the formula, Indicated in The cabinet status evaluation coefficient within the first preset qualified time period, , represents the number of the first preset qualified time period, represents the total number of first preset qualified time periods, the first preset qualified time period represents the preset time period corresponding to the qualified environmental assessment coefficient, Indicated in a leakage current evaluation value within a first preset qualified time period, Indicated in The cabinet interruption evaluation value within the first preset qualified time period, Indicated in The cabinet insulation evaluation value within the first preset qualified time period, represents the leakage current weight factor, represents the cabinet interruption weight factor, represents the cabinet insulation weight factor, and e represents a natural constant.

[0060] Indicated in A qualified environmental assessment coefficient within the first preset qualified time period, Indicated in The cabinet leakage current within the first preset qualified time period, Indicated in The duration of cabinet stopping operation within the first preset qualified time period, Indicated in The insulation resistance within a first preset qualified time period, Indicates the preset maximum leakage current. Indicates the maximum preset stop time. Indicates the preset maximum insulation resistance.

[0061] In this embodiment, the preset maximum leakage current value is represented by the maximum leakage current value corresponding to the high-voltage switchgear circuit in the historical time period, the preset maximum stop operation time value is represented by the maximum stop operation time value corresponding to the high-voltage switchgear circuit in the historical time period, and the preset maximum insulation resistance value is represented by the maximum insulation resistance value corresponding to the high-voltage switchgear circuit in the historical time period.

[0062] Specifically, assuming the leakage current evaluation value The range is 0.5-0.8, the cabinet interruption assessment value The range is 0.5-0.8, the cabinet insulation evaluation value The range is 0.5-0.8, and the leakage current weight factor Fixed to 0.4, cabinet interruption weight factor Fixed to 0.2, cabinet insulation weight factor It is fixed at 0.4, as shown in Table 1, which is a statistical table of changes in the cabinet state evaluation coefficient provided in the embodiment of the present application:

[0063] Table 1 Statistics of changes in cabinet status evaluation coefficients

[0064]

[0065] It can be seen from the above table that as the leakage current assessment value, cabinet interruption assessment value and cabinet insulation assessment value gradually increase, the cabinet status assessment coefficient gradually decreases, which means that the high-voltage switchgear is increasingly affected by the leakage current, cabinet interruption and insulation performance, and the qualification degree of the high-voltage switchgear gradually decreases.

[0066] It should be explained that the present embodiment provides a mapping set, which is obtained from a database. The mapping relationship in the mapping set can be a one-to-one correspondence or a many-to-one relationship. The mapping relationship in the mapping set is: the leakage current evaluation value, the cabinet interruption evaluation value and the cabinet insulation evaluation value correspond to the leakage current weight factor, the cabinet interruption weight factor and the cabinet insulation weight factor respectively. By inputting the real-time leakage current evaluation value, the cabinet interruption evaluation value and the cabinet insulation evaluation value into the mapping set, the corresponding leakage current weight factor, the cabinet interruption weight factor and the cabinet insulation weight factor can be obtained; for example, in the present embodiment, the value range of the weights involved is 0-1.

[0067] The algorithm of this embodiment combines the cabinet state interference data analysis to obtain the cabinet state evaluation coefficient. The larger the environmental evaluation coefficient, the higher the qualified degree of environmental monitoring during the monitoring process of the high-voltage switchgear, which is conducive to improving the monitoring accuracy of the cabinet leakage current, cabinet interruption time and insulation resistance, resulting in an increase in the cabinet state evaluation coefficient; the larger the cabinet leakage current and the cabinet interruption time, the greater the possibility of abnormality of the high-voltage switchgear, resulting in a decrease in the cabinet state evaluation coefficient; the larger the insulation resistance, the better the insulation performance of the high-voltage switchgear, resulting in an increase in the cabinet state evaluation coefficient. In summary, the cabinet state interference data is inversely proportional to the cabinet state evaluation coefficient.

[0068] In the algorithm of this embodiment, the cabinet status interference data does not exist independently, and each variable is interrelated, which requires comprehensive analysis. The larger the environmental assessment coefficient is, the higher the degree of environmental monitoring qualification is, and the better the insulation performance may be, which is usually conducive to the normal operation of the high-voltage switchgear; when the insulation resistance decreases, the cabinet leakage current may increase, because the decrease in insulation performance will cause the current to pass through the insulation layer more easily, thereby forming a leakage current; the reduction in insulation resistance may cause the failure rate of the high-voltage switchgear to increase, thereby increasing the duration of the cabinet outage. By analyzing the comprehensive influence between the parameters, an accurate assessment of the degree of qualification of the cabinet status of the high-voltage switchgear during the monitoring process of the high-voltage switchgear is achieved, thereby improving the accuracy of the electrical status data acquisition and storage quality monitoring of the high-voltage switchgear.

[0069] Furthermore, the specific process of judging whether to perform cabinet state interference adjustment is as follows: judging whether the obtained cabinet state evaluation coefficient is not lower than the preset cabinet state evaluation threshold in the database; if the cabinet state evaluation coefficient is not lower than the preset cabinet state evaluation threshold, the corresponding cabinet state evaluation coefficient is marked as a qualified cabinet state evaluation coefficient, otherwise the cabinet state interference adjustment is performed; if the cabinet state evaluation coefficient is still lower than the preset cabinet state evaluation threshold after the cabinet state interference adjustment, an alarm is sent to the preset personnel; the cabinet state interference adjustment includes insulation defect marking and air gap adjustment; the insulation defect marking indicates that the local discharge amount and the number of local discharges in the high-voltage switch cabinet are monitored by the local discharge detection method and the preset personnel are prompted to make abnormal markings; the air gap adjustment indicates that a prompt is sent to the preset personnel to adjust the air gap between the live part and the grounded part in the high-voltage switch cabinet.

[0070] In this embodiment, the preset cabinet state assessment threshold is represented by the average value of the cabinet state assessment coefficient in the historical time period; through partial discharge detection equipment, such as ultrasonic sensors and ultra-high frequency sensors, the preset position of the high-voltage switch cabinet is monitored and the partial discharge amount and partial discharge frequency in the high-voltage switch cabinet are obtained. When the monitored partial discharge amount and partial discharge frequency in the high-voltage switch cabinet exceed the safety range set by the preset personnel, an abnormal mark is made; the preset personnel reduces the risk of electrical breakdown by setting partitions at preset positions between the live parts and the grounded parts in the high-voltage switch cabinet, thereby improving the accuracy of electrical state data collection and storage quality monitoring of the high-voltage switch cabinet.

[0071] Furthermore, the specific process of cabinet defect assessment based on cabinet heating defect assessment data is as follows: obtain cabinet state influencing factors, which are obtained by processing qualified cabinet state assessment coefficients; obtain cabinet heating defect assessment data by processing cabinet state influencing factors, cabinet defect parameters and preset cabinet defect thresholds, and the cabinet heating defect assessment data includes cabinet internal temperature assessment value, heating power assessment value and cabinet loop resistance assessment value; cabinet heating defect assessment data is used to reflect the degree of influence of cabinet defect parameters by cabinet state influencing factors; obtain cabinet heating defect assessment coefficients by processing cabinet heating defect assessment data and preset heating defect weight factors; preset heating defect thresholds are used to calculate cabinet heating defect parameters. The thermal defect weight factors include the cabinet internal temperature weight factor, the heating power weight factor and the cabinet loop resistance weight factor; the preset cabinet defect threshold includes the preset cabinet internal temperature maximum value, the preset heating power maximum value and the preset cabinet loop resistance maximum value obtained from the database; the cabinet internal temperature weight factor is used to describe the influence of the cabinet internal temperature evaluation value on the cabinet heating defect assessment coefficient; the heating power weight factor is used to reflect the influence of the heating power evaluation value on the cabinet heating defect assessment coefficient; the cabinet loop resistance weight factor is used to reflect the influence of the cabinet loop resistance evaluation value on the cabinet heating defect assessment coefficient; the cabinet heating defect assessment coefficient is used to evaluate the abnormal heating of the high-voltage switchgear.

[0072] Among them, the cabinet heating defect assessment coefficient is obtained by the following method:

[0073] ;

[0074]

[0075] ;

[0076] ;

[0077] In the formula, Indicates The cabinet heating defect assessment coefficient within the second preset qualified time period, , represents the number of the second preset qualified time period, represents the total number of second preset qualified time periods, where the second preset qualified time period represents the preset time period corresponding to the qualified cabinet state evaluation coefficient, Indicates The cabinet internal temperature evaluation value within the second preset qualified time period, Indicates A heating power evaluation value within a second preset qualified time period, Indicates The cabinet loop resistance evaluation value within the second preset qualified time period, represents the weight factor of the cabinet internal temperature, represents the heating power weight factor, represents the cabinet loop resistance weight factor, e represents the natural constant, Indicates The cabinet status influencing factor within the second preset qualified time period, Indicates The qualified cabinet status evaluation coefficient within the second preset qualified time period, Indicates The internal temperature of the cabinet within the second preset qualified time period, Indicates The heating power of the switch cabinet within the second preset qualified time period, Indicates The cabinet loop resistance within the second preset qualified time period, Indicates the maximum preset cabinet internal temperature. Indicates the preset maximum heating power. Indicates the preset maximum value of the cabinet loop resistance.

[0078] In this embodiment, the preset maximum value of the internal temperature of the cabinet is represented by the maximum value of the internal temperature of the cabinet corresponding to the high-voltage switch cabinet circuit in the historical time period, the preset maximum value of the heating power is represented by the maximum value of the heating power corresponding to the high-voltage switch cabinet circuit in the historical time period, and the preset maximum value of the cabinet circuit resistance is represented by the maximum value of the cabinet circuit resistance corresponding to the high-voltage switch cabinet circuit in the historical time period.

[0079] It should be explained that the present embodiment provides a mapping set, which is obtained from a database. The mapping relationship in the mapping set can be a one-to-one correspondence or a many-to-one relationship. The mapping relationship in the mapping set is: the cabinet internal temperature evaluation value, the heat power evaluation value and the cabinet loop resistance evaluation value correspond to the cabinet internal temperature weight factor, the heat power weight factor and the cabinet loop resistance weight factor respectively. By inputting the real-time cabinet internal temperature evaluation value, the heat power evaluation value and the cabinet loop resistance evaluation value into the mapping set, the corresponding cabinet internal temperature weight factor, the heat power weight factor and the cabinet loop resistance weight factor can be obtained; for example, in the present embodiment, the value range of the weights involved is 0-1.

[0080] The algorithm of this embodiment combines the cabinet heating defect assessment data analysis to obtain the cabinet heating defect assessment coefficient. The greater the cabinet internal temperature, the switch cabinet heating power and the cabinet circuit resistance, the greater the possibility of abnormal heating of the high-voltage switch cabinet, which leads to an increase in the cabinet heating defect assessment coefficient; the higher the cabinet state assessment coefficient, the lower the possibility of defects in the high-voltage switch cabinet, which leads to a decrease in the cabinet heating defect assessment coefficient. In summary, the cabinet heating defect assessment data is directly proportional to the cabinet heating defect assessment coefficient.

[0081] In the algorithm of this embodiment, the cabinet heating defect assessment data does not exist independently, and each variable has mutual correlation, which requires comprehensive analysis. When the heating power of the switch cabinet increases, the internal temperature of the cabinet will increase accordingly. This is because the increase in the heating power of the switch cabinet means that the heat generated per unit time increases. If the heat dissipation conditions remain unchanged, the internal temperature of the cabinet will rise; when the cabinet loop resistance increases, the heat generated when the current passes through the loop resistance will also increase, resulting in an increase in the internal temperature of the cabinet; the heating power of the switch cabinet may cause the cabinet state assessment coefficient to decrease, because the heating power of the switch cabinet may mean that the equipment has defects or abnormal operation, such as poor contact, reduced insulation performance, etc., thereby reducing the cabinet state assessment coefficient; when the cabinet state assessment coefficient is higher, it means that the cabinet state is more qualified, which helps to reduce the impact on the monitoring of the internal temperature of the cabinet, the heating power of the switch cabinet and the cabinet loop resistance. By analyzing the comprehensive influence between the parameters, the accurate assessment of the abnormal heating situation of the high-voltage switch cabinet is achieved, and then the accuracy of the electrical state data acquisition and storage quality monitoring of the high-voltage switch cabinet is improved.

[0082] Furthermore, the specific process of defect optimization is as follows: determine whether the cabinet heating defect assessment coefficient is not higher than the preset heating threshold in the database; when the cabinet heating defect assessment coefficient is not higher than the preset heating threshold obtained from the database, no defect optimization is performed, otherwise defect optimization is performed; when the cabinet heating defect assessment coefficient is still higher than the preset heating threshold after defect optimization, an alarm is sent to the preset personnel; defect optimization includes node decoupling and overload protection; node decoupling means sending a prompt to the preset personnel to set a decoupling capacitor at the preset node; overload protection means sending a prompt to the preset personnel to set the set value of the overload protection of the high-voltage switch cabinet.

[0083] It should be supplemented that the qualified cabinet data includes qualified environmental detection impact data, qualified cabinet state interference data and qualified cabinet heating defect assessment data; the environmental detection impact data corresponding to the cabinet state assessment coefficient that is not lower than the preset cabinet state assessment threshold is obtained and stored; the cabinet state interference data corresponding to the cabinet state assessment coefficient that is not lower than the preset cabinet state assessment threshold is obtained and stored; the cabinet heating defect assessment data corresponding to the cabinet heating defect assessment coefficient that is not higher than the preset heating threshold is obtained and stored; the qualified environmental detection impact data represents the environmental detection impact data corresponding to the cabinet state assessment coefficient that is not lower than the preset cabinet state assessment threshold; the qualified cabinet state interference data represents the cabinet state interference data corresponding to the cabinet state assessment coefficient that is not lower than the preset cabinet state assessment threshold; the qualified cabinet heating defect assessment data represents the cabinet heating defect assessment data corresponding to the cabinet heating defect assessment coefficient that is not higher than the preset heating threshold.

[0084] In this embodiment, the preset heating threshold is represented by an average value of the cabinet heating defect assessment coefficient in a historical time period.

[0085] When it is monitored that the cabinet heating defect assessment coefficient is higher than the preset heating threshold, the preset personnel will set a decoupling capacitor at the preset node of the high-voltage switchgear according to the received prompt to reduce the capacitive coupling effect, reduce heating and electromagnetic interference; when the current at the preset position point of the outgoing line end of the high-voltage switchgear is higher than the set value (such as the rated current) of the high-voltage switchgear overload protection, the preset personnel will be prompted to cut off the power supply to prevent the high-voltage switchgear from heating and failure caused by overload, thereby improving the accuracy of electrical status data collection and storage quality monitoring of the high-voltage switchgear.

[0086] like Figure 3 As shown, it is a schematic diagram of a multivariate data fusion state assessment model provided in an embodiment of the present application, which is composed of Figure 3 It can be seen that by storing the acquired qualified cabinet data, further performing data analysis based on the stored qualified cabinet data, or performing state parameter preprocessing on the stored qualified cabinet data, it is possible to update the database data and use the qualified cabinet data stored in the database as a state evaluation parameter to improve the accuracy of the high-voltage switchgear operating status evaluation.

[0087] To summarize, by performing an environmental status assessment and determining whether to perform environmental interference adjustment, then performing a cabinet status interference assessment and determining whether to perform cabinet status interference adjustment, then performing a cabinet defect assessment to obtain the cabinet heating defect assessment coefficient and determine whether to perform defect optimization, and finally storing the acquired qualified cabinet data, the accuracy of storage of qualified cabinet data is improved, thereby achieving an improvement in the accuracy of electrical status data collection and storage quality monitoring of high-voltage switchgear, and effectively solving the problem of low accuracy of electrical status data collection and storage quality monitoring of high-voltage switchgear in the prior art.

[0088] It will be appreciated by those skilled in the art that embodiments of the present invention may be provided as methods, systems, or computer program products. Therefore, the present invention may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Furthermore, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0089] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0090] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0091] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1The steps for the functions specified in one or more boxes.

[0092] Although the preferred embodiments of the present invention have been described, those skilled in the art may make other changes and modifications to these embodiments once they have learned the basic creative concept. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications that fall within the scope of the present invention.

[0093] Obviously, those skilled in the art can make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include these modifications and variations.

Claims

1. A data quality monitoring storage system based on equipment electrical status evaluation, characterized in that: It includes environmental status assessment module, cabinet status interference assessment module, cabinet defect assessment module and data storage module: The environmental status assessment module is used to monitor the high-voltage switchgear to obtain live detection parameters and environmental detection parameters, and to perform environmental status assessment based on the acquired data and determine whether to perform environmental interference adjustment; The cabinet state interference assessment module is used to obtain cabinet state interference data according to the acquired cabinet state parameters and qualified environment assessment coefficients, perform cabinet state interference assessment based on the cabinet state interference data, and determine whether to perform cabinet state interference adjustment; The cabinet defect assessment module is used to obtain cabinet heating defect assessment data according to the obtained cabinet defect parameters and the qualified cabinet state assessment coefficient, perform cabinet defect assessment based on the cabinet heating defect assessment data to obtain the cabinet heating defect assessment coefficient and determine whether to perform defect optimization, the qualified cabinet state assessment coefficient represents a cabinet state assessment coefficient that is not lower than a preset cabinet state assessment threshold, and the cabinet heating defect assessment coefficient is used to assess the abnormal heating condition of the high-voltage switch cabinet during the monitoring process of the high-voltage switch cabinet; The data storage module is used to store the acquired qualified cabinet data, and the qualified cabinet data is used to perform electrical status evaluation.

2. The data quality monitoring storage system based on equipment electrical status evaluation according to claim 1, characterized in that: The live detection parameters include the switch cabinet short-circuit current and the switch cabinet magnetic field strength; The environmental detection parameters include external environmental temperature, external environmental humidity and cabinet load rate; The cabinet status parameters include cabinet leakage current, cabinet shutdown time and insulation resistance; The cabinet defect parameters include the cabinet internal temperature, switch cabinet heating power and cabinet loop resistance.

3. The data quality monitoring storage system based on equipment electrical status evaluation as claimed in claim 2, characterized in that: The specific process of performing environmental status assessment based on the acquired data is as follows: The interference influencing factor is obtained by processing the live detection parameters and the preset interference threshold; Environmental detection impact data is obtained by processing environmental detection parameters, preset environmental detection thresholds and interference impact factors; The environmental assessment coefficient is obtained by processing the environmental testing impact data and the preset environmental testing weight factors; The interference impact factor is used to reflect the degree of electromagnetic interference within a preset time period; The preset interference threshold includes a preset short-circuit current maximum value and a preset magnetic field intensity maximum value; The environmental detection impact data includes a temperature impact assessment value, a humidity impact assessment value and a load factor impact assessment value; The environmental detection impact data is used to reflect the impact of environmental detection parameters on interference factors; The preset environmental detection thresholds include a preset maximum external temperature, a preset maximum external humidity, and a preset maximum load rate; The preset environmental detection weight factors include a temperature weight factor, a humidity weight factor and a load rate weight factor; The environmental assessment coefficient is used to assess the environmental monitoring qualification level during the monitoring process of the high-voltage switchgear.

4. The data quality monitoring storage system based on equipment electrical status evaluation as claimed in claim 2, characterized in that: The switch cabinet short-circuit current represents the maximum value of the short-circuit current formed by the high-voltage switch cabinet circuit within a preset time period; The cabinet leakage current represents the maximum value of the current leaked by the insulating material of the high-voltage switch cabinet within a preset time period; The cabinet stop operation duration represents the maximum duration of the high-voltage switch cabinet stopping operation due to an abnormality within a preset time period.

5. The data quality monitoring storage system based on equipment electrical status evaluation as claimed in claim 3, characterized in that: The specific process of determining whether to perform environmental interference adjustment is as follows: Determine whether the obtained environmental assessment coefficient is not lower than the preset environmental interference threshold in the database; When the environmental assessment coefficient is not lower than the preset environmental interference threshold, the corresponding environmental assessment coefficient is marked as a qualified environmental assessment coefficient, otherwise the environmental interference adjustment is performed; When the environmental assessment coefficient after environmental interference adjustment is still lower than the preset environmental interference threshold, an alarm is sent to the preset personnel; The environmental interference adjustment includes anti-interference of charged detection values ​​and structural shielding.

6. The data quality monitoring storage system based on equipment electrical status evaluation as claimed in claim 2, characterized in that: The specific process of performing cabinet state interference evaluation based on cabinet state interference data is as follows: The cabinet state interference data is obtained by processing the environmental interference factor, the cabinet state parameter and the preset cabinet state threshold, wherein the environmental interference factor is obtained by processing the qualified environment assessment coefficient; The cabinet state evaluation coefficient is obtained by processing the cabinet state interference data and the preset cabinet state weight factor; The cabinet state interference data includes a leakage current evaluation value, a cabinet interruption evaluation value and a cabinet insulation evaluation value; The cabinet state interference data is used to reflect the influence of the cabinet state parameters on the environmental interference factors; The preset cabinet state thresholds include a preset maximum leakage current value, a preset maximum shutdown time value, and a preset maximum insulation resistance value; The preset cabinet state weight factors include a leakage current weight factor, a cabinet interruption weight factor and a cabinet insulation weight factor; The cabinet state evaluation coefficient is used to evaluate the cabinet state qualification degree of the high-voltage switch cabinet during the monitoring process of the high-voltage switch cabinet.

7. The data quality monitoring storage system based on equipment electrical status evaluation as claimed in claim 6, characterized in that: The specific process of determining whether to perform cabinet state interference adjustment is as follows: Determine whether the obtained cabinet state assessment coefficient is not lower than a preset cabinet state assessment threshold in the database; If the cabinet state evaluation coefficient is not lower than the preset cabinet state evaluation threshold, the corresponding cabinet state evaluation coefficient is marked as a qualified cabinet state evaluation coefficient, otherwise the cabinet state interference adjustment is performed; If the cabinet state evaluation coefficient is still lower than the preset cabinet state evaluation threshold after the cabinet state interference adjustment, an alarm is sent to the preset personnel; The cabinet state interference adjustment includes insulation defect marking and air gap adjustment.

8. The data quality monitoring storage system based on equipment electrical status evaluation as claimed in claim 2, characterized in that: The specific process of performing cabinet defect assessment based on cabinet heating defect assessment data is as follows: Obtaining a cabinet state influencing factor, wherein the cabinet state influencing factor is obtained by processing a qualified cabinet state evaluation coefficient; The cabinet heating defect assessment data is obtained by processing the cabinet state influencing factor, the cabinet defect parameter and the preset cabinet defect threshold, wherein the cabinet heating defect assessment data includes the cabinet internal temperature assessment value, the heating power assessment value and the cabinet loop resistance assessment value; The cabinet heating defect assessment data is used to reflect the degree to which the cabinet defect parameters are affected by the cabinet state influencing factors; The cabinet heating defect assessment coefficient is obtained by processing the cabinet heating defect assessment data and the preset heating defect weight factor; The preset heating defect weight factors include a cabinet internal temperature weight factor, a heating power weight factor and a cabinet loop resistance weight factor; The preset cabinet defect thresholds include a preset cabinet internal temperature maximum value, a preset heating power maximum value, and a preset cabinet loop resistance maximum value; The cabinet heating defect assessment coefficient is used to assess the abnormal heating condition of the high-voltage switch cabinet.

9. The data quality monitoring storage system based on equipment electrical status evaluation as claimed in claim 8, characterized in that: The specific process of defect optimization is as follows: Determine whether the obtained cabinet heating defect assessment coefficient is not higher than a preset heating threshold in the database; When the cabinet heating defect assessment coefficient is not higher than the preset heating threshold obtained from the database, defect optimization is not performed, otherwise defect optimization is performed; When the cabinet heating defect assessment coefficient is still higher than the preset heating threshold after defect optimization, an alarm is sent to the preset personnel; The defect optimization includes node decoupling and overload protection.

10. The data quality monitoring storage system based on equipment electrical status evaluation according to claim 1, characterized in that: The qualified cabinet data includes qualified environmental detection impact data, qualified cabinet state interference data and qualified cabinet heating defect assessment data; The qualified environmental detection impact data represents environmental detection impact data corresponding to a cabinet state assessment coefficient that is not lower than a preset cabinet state assessment threshold; The qualified cabinet state interference data represents cabinet state interference data corresponding to a cabinet state evaluation coefficient that is not lower than a preset cabinet state evaluation threshold; The qualified cabinet heating defect assessment data represents cabinet heating defect assessment data corresponding to a cabinet heating defect assessment coefficient that is not higher than a preset heating threshold.

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