Method and system for automatically comparing and analyzing test indexes of transformer substation

Abstract

The invention provides a transformer substation test index automatic comparison analysis method and system, and the method comprises the steps: recognizing communication paths and independent partition boundaries between air chambers through different states of communication air chambers and isolation air chambers according to the valve opening and closing conditions in a test data table, and obtaining an air chamber communication distribution diagram; aiming at the air chamber communication distribution diagram, extracting installation coordinates of each measuring point in a communicated air chamber or an independent partition, and identifying the air chamber attribution corresponding to the measuring point by combining the physical position of the measuring point and the boundary of the air chamber to obtain a measuring point grouping list; analyzing the coverage area of the communicated air chambers in the air chamber communication distribution diagram, combining the micro-water content of the corresponding measuring points in the measuring point grouping list, and evaluating the overall micro-water level of the communicated air chambers to obtain the micro-water concentration grade of the communicated air chambers; and in combination with the deviation area list and the air chamber communication distribution diagram, distinguishing different types of local defects of the independent air chamber and overall anomalies of the communicated air chamber, and positioning corresponding abnormal measuring points to obtain a transformer substation test comparison analysis result.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of information technology, and in particular to a substation test index automatic comparison and analysis method and system. BACKGROUND

[0002] In the field of power system operation and maintenance, the health state monitoring of substation equipment is of great significance, directly related to the safe and stable operation of the power grid. Especially for gas insulated switchgear, the quality state of the internal gas has a profound impact on the performance of the equipment, and any slight abnormality may cause a major failure. Therefore, accurately assessing the moisture content of the internal gas of the equipment has become an important link to ensure the safe operation of the equipment. However, there is a problem that cannot be ignored in the current assessment of the gas state of the equipment, that is, the detection method often ignores the complexity of the internal gas chamber structure. Many methods simply pursue the number of detection points, thinking that the wider the coverage, the more data can reflect the overall situation of the equipment, but in fact, this approach often backfires when faced with complex gas chamber structures. Due to the failure to accurately identify the connection and isolation relationship between the gas chambers, multiple detection points may actually measure the gas state of the same connected area, resulting in data redundancy, while the isolated area that needs to be concerned is in a monitoring blind area due to improper detection point configuration. Especially in the case of isolation valves between gas chambers, the detection results are easily disturbed, leading to a decrease in the accuracy of the assessment. As a key factor affecting the accuracy of detection, the open and closed state of the gas chamber isolation valve directly determines the flow pattern of the internal gas of the equipment. The presence of the gas chamber isolation valve may form multiple independent areas inside the equipment, and the gas state of each area may be completely different. If the open and closed state of the valve is not considered, the data of the detection points may repeatedly reflect the situation of some connected areas, while the abnormalities of the isolated areas cannot be effectively captured. Further, this influence will directly lead to the deviation of the assessment results. When multiple detection points are located in the same connected area, the data collected by these detection points have high similarity, which will produce a repeated weight effect in the evaluation calculation, making the gas state of the connected area occupy a high proportion in the overall evaluation, and thus masking the true situation of other areas, especially the isolated areas. For example, in a detection, a gas chamber forms an independent area due to the closed valve, but its internal moisture exceeds the standard and cannot be detected due to the lack of targeted detection points, while multiple detection points in other connected areas repeatedly reflect similar data, ultimately masking the abnormality of the problem area. Therefore, how to reasonably balance the distribution of detection points and the influence of gas chamber isolation state under diversified gas chamber structures, and ensure that both the overall situation of the connected area and the local abnormality of the isolated area can be accurately identified, has become a key problem to be solved. SUMMARY

[0003] The present application provides a substation test index automatic comparison and analysis method, mainly comprising: collecting SF6 micro-water content of each measuring point of the substation, opening and closing conditions of gas chamber isolation valves, and gas chamber numbers to which the measuring points belong; According to the opening and closing conditions of the gas chamber isolation valves, the communication paths between the gas chambers and the independent partition boundaries are identified through different states of the communication gas chambers and the isolation gas chambers, and a gas chamber communication distribution map is obtained. For the gas chamber communication distribution map, the installation coordinates of each measuring point in the communication gas chamber or the independent partition are extracted, the corresponding gas chamber attribution of the measuring point is identified, and a measuring point grouping list is obtained. According to the gas chamber communication distribution map and the measuring point grouping list, the micro-water concentration level of the communication gas chamber is identified. The micro-water content of the measuring point in the independent partition is extracted, the deviation degree of the micro-water content of the independent partition from the equipment qualification standard is evaluated, and the independent gas chamber defect category is obtained. According to the micro-water concentration level of the communication gas chamber and the independent gas chamber defect category, the influence proportion of each measuring point in the measuring point grouping list is adjusted, the representative strength of the micro-water content is re-evaluated, and the adjusted comparison basis group is determined. The adjusted comparison basis group is compared with the equipment qualification standard in the historical test database, different judgment thresholds of the communication area and the independent area are distinguished, the gas chamber area whose deviation exceeds the allowable error range is identified, and a deviation area list is obtained. Combined with the deviation area list and the gas chamber communication distribution map, the abnormal measuring point is located.

[0004] Further, the SF6 micro-water content of each measuring point of the substation, the opening and closing conditions of the gas chamber isolation valves, and the gas chamber numbers to which the measuring points belong are collected from the test database, including: reading the real-time monitoring records of each measuring point of the SF6 gas insulated equipment through the historical data interface of the substation monitoring system, extracting the measuring point number, the gas chamber number to which it belongs, and the gas chamber isolation valve number, obtaining the current opening and closing state signal of the gas chamber isolation valve from the equipment account, forming the corresponding relationship record of the measuring point and the gas chamber; querying the latest SF6 micro-water content detection value of each measuring point according to the measuring point number in the corresponding relationship record, reading the detection time stamp, extracting the valve opening and closing condition corresponding to the opening and closing state signal, and generating a test data table.

[0005] Further, according to the opening and closing of the gas chamber isolation valve, the communication path and the independent partition boundary between the gas chambers are identified through the different states of the communication gas chamber and the isolation gas chamber, and the gas chamber communication distribution map is obtained, including: reading the gas chamber number and the corresponding isolation valve opening and closing state, establishing the connection relationship record between the gas chambers, if there is a valve between two gas chambers and the valve is in the open state, it is marked as a direct communication relationship, if the valve is closed, it is marked as an isolation relationship, and a communication state table between the gas chambers is formed; according to the communication state table, all gas chambers directly connected with any gas chamber are found, and other gas chambers connected with these gas chambers are recursively found until there is no new connected gas chamber, a connected gas chamber set is obtained, and the process is repeated for the gas chambers not contained in any connected set, all connected gas chamber sets and independent gas chamber sets are obtained; a unique area identifier is assigned to each set, the gas chamber number and its mutual connection relationship in the set are recorded, the communication path and the isolation boundary position are marked, and the gas chamber communication distribution map containing the gas chamber area attribution, the communication path direction and the independent partition boundary is generated.

[0006] Further, for the gas chamber communication distribution map, the installation coordinates of each measuring point in the connected gas chamber or the independent partition are extracted, the gas chamber attribution corresponding to the measuring point is identified, and the measuring point grouping list is obtained, including: reading the gas chamber number set of each connected area and independent partition from the gas chamber communication distribution map, querying the three-dimensional installation coordinate data of each measuring point, extracting the physical boundary coordinate range of each gas chamber, matching the measuring point coordinates with the gas chamber boundary range, determining the gas chamber to which the measuring point belongs according to the coordinate inclusion relationship, and classifying and summarizing all measuring points according to the area number, generating the measuring point grouping list containing the measuring point number and the area number to which it belongs.

[0007] Further, the micro water concentration level of the connected gas chamber is identified, including: extracting the micro water content detection value of all measuring points in the same connected area, calculating the relative deviation between the measuring points to determine the similarity, generating a similar data group according to the similarity, reducing the weight proportion of the measuring points with similar spatial positions in the similar data group, calculating the micro water content comprehensive value of the connected area by using the weighted average method, and obtaining the micro water concentration level of the connected gas chamber.

[0008] Further, the micro water content of the measuring points in the independent partition is extracted, the deviation degree of the micro water content of the independent partition from the equipment qualification standard is evaluated, and the independent gas chamber defect category is obtained, including: identifying all independent partitions, using the value of the single measuring point in the independent partition as the representative value, selecting the maximum value of the micro water content as the representative value for the independent partition containing multiple measuring points, calculating the over-standard proportion, determining the defect category according to the over-standard proportion, establishing the independent gas chamber defect category table.

[0009] Further, according to the micro-water concentration level of the connected gas chamber and the defect category of the independent gas chamber, the influence proportion of each measuring point in the measuring point grouping list is adjusted, the representative strength of the micro-water content is re-evaluated, and the adjusted comparison basis group is determined, including: reading the micro-water concentration level of the connected gas chamber and the defect category of the independent gas chamber, distributing corresponding weight values according to the concentration level and the severity of the defect category to form an initial weight configuration table of each gas chamber; multiplying the original weight of each measuring point by the weight value of the gas chamber to which the measuring point belongs according to the initial weight configuration table and the measuring point grouping list, and recording the spatial coordinate position of the measuring point at the same time to obtain measuring point weight distribution data containing adjusted weights and spatial positions; the ratio of the number of measuring points in the connected gas chamber to the number of measuring points in the independent gas chamber is counted, the spatial distribution adjustment coefficient is determined according to the ratio, the adjusted weight of each measuring point in the measuring point weight distribution data is corrected to obtain the final weight, and the final weight and the micro-water content data of all measuring points are summarized to construct the adjusted comparison basis group containing the measuring point number, the final weight and the micro-water content.

[0010] Further, the deviation region list is obtained, including: extracting the final weight value and the micro-water content data of each measuring point, determining the comparison reference of the connected region, taking the maximum value of the micro-water content as the comparison reference of the independent region, calculating the deviation value, marking the deviation region, and generating the deviation region list.

[0011] Further, the abnormal measuring point is located, including: reading the region number in the deviation region list, marking the independent region as a local defect type and the connected region as an overall abnormal type, finding the measuring points in each deviation region from the measuring point grouping list, associating the measuring point information with the abnormal type and the deviation degree, and generating the substation test comparison analysis result.

[0012] A substation test index automatic comparison analysis system, the system comprises: A data acquisition module is configured to acquire the SF6 micro-water content of each measuring point in a substation, the opening and closing of a gas chamber isolation valve, and the gas chamber number to which the measuring point belongs. A connected analysis module is configured to identify the connected path and independent partition boundary between gas chambers according to the opening and closing of the gas chamber isolation valve through different states of the connected gas chamber and the isolated gas chamber, and obtain a gas chamber connected distribution map. A measuring point grouping module is configured to extract the installation coordinates of each measuring point in the connected gas chamber or the independent partition according to the gas chamber connected distribution map, identify the gas chamber to which the measuring point belongs, and obtain a measuring point grouping list. An identification module is configured to identify the micro-water concentration level of the connected gas chamber according to the gas chamber connected distribution map and the measuring point grouping list. A first determination module is configured to extract the micro-water content of the measuring point in the independent partition, evaluate the deviation degree of the micro-water content of the independent partition from the equipment qualification standard, and obtain the defect category of the independent gas chamber. The second determination module is configured to reevaluate the representative strength of the micro water content after adjusting the influence proportion of each measuring point in the measuring point grouping list according to the micro water concentration level of the communicating gas chamber and the defect category of the independent gas chamber, and determine an adjusted comparison basis group; The deviation analysis module is configured to compare the adjusted comparison basis group with the equipment qualification standard in the historical test database, distinguish different determination thresholds of the communicating area and the independent area, identify gas chamber areas with deviations exceeding the allowable error range, and obtain a deviation area list; The positioning module is configured to locate abnormal measuring points in combination with the deviation area list and the gas chamber communicating distribution map.

[0013] The technical scheme provided by the embodiment of the present application can include the following beneficial effects: The present application discloses a kind of substation test index automatic comparison analysis method and system, for the micro water content evaluation complexity problem caused by gas chamber communication and independent distribution characteristics in substation, by constructing gas chamber communication distribution map, identifying communicating path and independent partition boundary, fusing measuring point grouping and micro water content data, innovatively proposed double analysis mechanism of communicating gas chamber overall micro water concentration level evaluation and independent gas chamber defect category determination.The present application adjusts the influence proportion of measuring point, reevaluates the representative strength of micro water in combination with spatial distribution difference, forms comparison basis group, accurately locates deviation area after comparison with historical standard, finally realizes the classification diagnosis of independent gas chamber local defect and communicating gas chamber overall anomaly.The present application significantly improves the accuracy and pertinence of substation gas chamber micro water content analysis, provides efficient technical support for the intelligent monitoring and defect early warning of equipment operating state. BRIEF DESCRIPTION OF DRAWINGS

[0014] Fig. 1 It is a flow chart of the substation test index automatic comparison analysis method of the present application.

[0015] Fig. 2 It is a schematic diagram of the substation test index automatic comparison analysis method of the present application.

[0016] Fig. 3 It is a structural schematic diagram of the substation test index automatic comparison analysis system of the present application. DETAILED DESCRIPTION

[0017] The technical scheme of the present application will be described clearly and completely in combination with embodiments. Obviously, the described embodiments are only part of the embodiments of the present application, not all. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor are within the scope of protection of the present application.

[0018] AsFigs. 1-3 The substation test index automatic comparison and analysis method and system can specifically include the following. S101, collect SF6 micro-water content, gas chamber isolation valve opening and closing conditions, and gas chamber numbers of each measuring point of the substation from the test database to obtain a test data table containing micro-water content, valve opening and closing conditions, and gas chamber numbers.

[0019] Through the historical data interface of the substation monitoring system, real-time monitoring records of each measuring point of the SF6 gas insulated equipment are read, the measuring point number, the gas chamber number to which it belongs, and the gas chamber isolation valve number are extracted, the current opening and closing state signal of the gas chamber isolation valve is obtained from the equipment account book, and the correspondence relationship record of the measuring point and the gas chamber is formed. According to the measuring point number in the correspondence relationship record, the latest SF6 micro-water content detection value of each measuring point is queried from the test database, the detection time stamp is read, and the valve opening and closing condition corresponding to the opening and closing state signal is extracted. The measuring point number, the gas chamber number to which it belongs, the micro-water content value, and the valve opening and closing state are summarized to generate a test data table containing micro-water content, valve opening and closing conditions, and gas chamber numbers.

[0020] Specifically, in an embodiment, the substation monitoring system collects data in real time through sensor nodes deployed on each gas insulated switchgear. Each sensor node is configured with a unique measuring point number and records the gas chamber number corresponding to its installation position. The monitoring system maintains an equipment account database, which stores the physical position information of the gas chamber isolation valve, the valve number, and the connection relationship with each gas chamber. By querying this database, the current opening and closing state signal of the valve can be obtained to form a complete correspondence relationship record of the measuring point, the gas chamber, and the valve. The test database uses a relational database structure to store the SF6 micro-water content detection values of each measuring point in chronological order. When querying according to the measuring point number, the latest detection value and its corresponding time stamp are extracted, and the valve opening and closing signal is read from the real-time state register of the valve control system, where the opening state is marked as 1 and the closing state is marked as 0.

[0021] Exemplarily, the measuring point number, the gas chamber number to which it belongs, the micro-water content value, and the valve opening and closing state are integrated into the same data structure to generate a structured test data table. The data table is stored in the form of a multi-dimensional array, which facilitates quick positioning of related information of a specific gas chamber or measuring point during subsequent analysis and processing.

[0022] S102, according to the valve opening and closing conditions in the test data table, identify the communication paths and independent partition boundaries between gas chambers by the different states of the communication gas chambers and the isolation gas chambers to obtain a gas chamber communication distribution map.

[0023] Read each gas chamber number and its corresponding isolation valve open and close state in the test data table, establish the connection relationship record between the gas chambers, if there is a valve between two gas chambers and the valve is in the open state, mark the two gas chambers as direct communication relationship, if the valve is closed, mark it as isolation relationship, form the communication state table between the gas chambers. According to the communication state table, start from any gas chamber, find all the gas chambers directly connected with it, and then recursively find other gas chambers connected with these gas chambers, until no new connected gas chamber is found, obtain a connected gas chamber set, repeat this process for the gas chambers not included in any connected set, obtain all connected gas chamber sets and independent gas chamber sets. Based on the connected gas chamber set and the independent gas chamber set, assign a unique area identifier to each set, record the gas chamber numbers contained in the set and their mutual connection relationship, mark the communication path and the isolation boundary position, and generate a gas chamber communication distribution map containing the area attribution of each gas chamber, the communication path direction and the independent partition boundary.

[0024] Specifically, in an embodiment, the gas chamber connection relationship record adopts a two-dimensional relationship table structure, each record contains four fields of starting gas chamber number, target gas chamber number, intermediate valve number and valve open and close state. When the valve is in the open state, the record value is 1, indicating that there is a gas flow path between the two gas chambers; when the valve is closed, the record value is 0, indicating that the two gas chambers are isolated. By traversing all valve states, a complete gas chamber communication state table is constructed.

[0025] Specifically, the recursive search process selects an unmarked gas chamber from the communication state table as the starting point, queries all adjacent gas chambers directly connected with the gas chamber in the communication state table, i.e. the target gas chamber corresponding to the record with valve state value of 1. For each found adjacent gas chamber, continue to find other gas chambers connected therewith, and add the newly found gas chamber to the current connected set. This process continues until no new connected gas chamber is found, at which time a complete connected gas chamber set is formed. Through this depth traversal method, all groups of gas chambers connected with each other through open valves can be accurately identified. For the gas chambers isolated by closed valves, they cannot form a connected relationship with other gas chambers, and therefore are identified as independent gas chambers. The independent gas chamber set contains all single gas chambers not included in any connected set, and the SF6 gas state in these gas chambers is relatively independent and not affected by other gas chambers.

[0026] Preferably, the gas chamber communication distribution map adopts a topological structure, in which each gas chamber is represented by a node, and the connection line between the nodes represents the communication relationship between the gas chambers. The solid line connection represents the connected path formed by the open valve between the two gas chambers, and the dashed line box represents the boundary of the independent partition. Each connected set or independent gas chamber is assigned a unique area identifier, such as the connected area A containing gas chambers 1, 2 and 3, and the independent area B containing only gas chamber 4.

[0027] In a possible implementation, the gas chamber communication distribution map further records the valve number and position information on each communication path, so as to facilitate subsequent dynamic updating of the communication relationship according to the valve state change. When the state of a valve changes, only the corresponding connection relationship needs to be updated, and the communication judgment is re-executed, so that the updated gas chamber communication distribution map can be obtained.

[0028] S103, for the gas chamber communication distribution map, the installation coordinates of each measuring point in the communication gas chamber or the independent partition are extracted, the physical position of the measuring point is combined with the gas chamber boundary, the attribution of the measuring point corresponding to the gas chamber is identified, and a measuring point grouping list is obtained.

[0029] The gas chamber number set of each communication region and independent partition is read from the gas chamber communication distribution map, the three-dimensional installation coordinate data of each measuring point is inquired, which is derived from the equipment installation design drawing or the system database, and the physical boundary coordinate range of each gas chamber is extracted, which is derived from the gas chamber design parameter or the database record. The measuring point coordinates are matched with the gas chamber boundary range, and the corresponding relationship data of the measuring point position and the gas chamber boundary is obtained. According to the corresponding relationship data, the attribution of each measuring point to the gas chamber is judged through the coordinate containing relationship. If the measuring point coordinate value is in the gas chamber boundary coordinate range, it is determined that the measuring point belongs to the gas chamber, and an attribution mapping table of the measuring point and the gas chamber is formed. Based on the attribution mapping table and the region division information in the gas chamber communication distribution map, the corresponding communication region number or independent partition number of each measuring point is found, all the measuring points are classified and summarized according to the region number, and a measuring point grouping list containing the measuring point number and the region number is generated.

[0030] Specifically, in an embodiment, the corresponding relationship of the measuring point position and the gas chamber boundary is realized through a spatial coordinate matching algorithm. The physical boundary of each gas chamber is defined by the coordinate values of six faces, including the longitudinal coordinate range of the front and rear faces, the horizontal coordinate range of the left and right faces, and the height coordinate range of the upper and lower faces. The three-dimensional installation coordinates of the measuring point are represented as a space point, and whether the point satisfies the constraint conditions of the six boundary faces of the gas chamber is judged to determine whether the measuring point is located in the gas chamber.

[0031] Specifically, the judgment of the coordinate containing relationship adopts the interval judgment method. For the measuring point coordinate P(x, y, z) and the gas chamber boundary B(x min ,x max ,y min ,y max ,z min ,z max ), when x min ≤x≤x max and y min ≤y≤y max and z min ≤z≤z maxWhen the three conditions are met at the same time, it is determined that the measuring point P belongs to the gas chamber. This judgment method can accurately handle the case where the measuring point is located near the boundary of the gas chamber, and avoid misattribution. Some measuring points may be installed near the connection of the gas chamber or the valve, and at this time the measuring point may meet the boundary conditions of multiple gas chambers at the same time. For such boundary measuring points, according to the distance between the measuring point and the center point of each gas chamber, the measuring point is attributed to the nearest gas chamber. First, the coordinate inclusion relationship method is used, and the coordinates (x, y, z) of the measuring point P need to meet the gas chamber boundary conditions, that is, x min ≤x≤x max , y min ≤y≤y max , z min ≤z≤z max . If the measuring point meets the conditions of multiple gas chambers at the same time, the Euclidean distance between the measuring point and the center point of each gas chamber is further calculated, and the nearest gas chamber is attributed. The center point of the gas chamber is calculated as follows: take the average of the six boundary surfaces, that is, the center point coordinates are ((x min +x max ) / 2, (y min +y max ) / 2, (z min +z max ) / 2).

[0032] Preferably, after forming the attribution mapping table, the number of measuring points in each gas chamber is counted. If there is no measuring point in a certain gas chamber, mark the gas chamber as a monitoring point-free gas chamber, and use the data of the adjacent gas chamber for calculation in the subsequent micro-water content evaluation, and the gas chamber is included in the grouping list of the adjacent gas chamber for unified management. When evaluating the micro-water content, the nearest adjacent gas chamber with monitoring data is preferentially selected, and the data of the monitoring point-free gas chamber is calculated by the average value.

[0033] In one possible implementation, the measuring point grouping list is stored in a tree-shaped data structure, the root node is the entire substation, the first layer of child nodes is each independent partition or connected region, the second layer of child nodes is each gas chamber in the region, and the leaf node is each measuring point in the gas chamber. This hierarchical data organization method facilitates quick query of all measuring points in a specific region or gas chamber, and improves data processing efficiency.

[0034] Illustratively, for an SF6 device containing 10 gas chambers, if gas chambers 1, 2 and 3 are connected to each other through an open valve to form a connected region A, gas chambers 4 and 5 form a connected region B, and the remaining gas chambers are independent partitions, the measuring point grouping list will classify all measuring points according to A, B and each independent partition, and record all measuring point numbers and their specific location information under each classification.

[0035] S104, analyze the coverage of the communication gas chamber in the communication chamber distribution map, merge the micro water content of the corresponding measuring points in the measuring point grouping list, evaluate the overall micro water level of the communication gas chamber, and obtain the micro water concentration grade of the communication gas chamber.

[0036] According to the gas chamber communication distribution map and the measuring point grouping list, the micro water content detection values of all measuring points in the same communication region are extracted, the relative deviation between each two measuring point detection values is calculated, if the relative deviation between all measuring points is less than the preset similarity threshold, it is determined that the measuring point data in the communication region has high similarity, and is marked as a similar data group. For the similar data group, the spatial distribution of each measuring point in the communication region is counted, the weight proportion of multiple measuring points with similar spatial positions in the overall evaluation is reduced, the micro water content comprehensive value of the communication region is calculated by using the weighted average method, and the representative value of the region micro water after removing the repeated influence is obtained. The representative value of the region micro water is compared with the SF6 gas micro water content limit value specified by the industry standard, if the representative value is lower than the excellent limit value, it is marked as first level, between the excellent limit value and the qualified limit value, it is marked as second level, and more than the qualified limit value, it is marked as third level, and the micro water concentration grade of the communication gas chamber is determined.

[0037] Specifically, the calculation of the relative deviation is realized by pairwise comparison. For any two measuring points i and j in the communication region, the micro water content detection values are Wi and Wj, and the relative deviation is calculated as |Wi-Wj| / max(Wi,Wj)×100%. When the relative deviation of all measuring point pairs is less than the preset threshold of 5%, it is determined that the measuring point data in the communication region has high similarity. This judgment method can effectively identify the micro water content convergence phenomenon caused by gas flow. In an embodiment, the spatial distribution is counted by using the grid division method. The space of the communication region is divided into several cubic grids, and the number of measuring points contained in each grid is counted. For the grid with dense measuring points, the internal measuring points are given a lower weight coefficient when calculating the representative value of the region micro water. The specific weight calculation adopts an inverse proportional relationship, that is, the weight coefficient is equal to 1 divided by the number of measuring points in the grid. This weight distribution mechanism can avoid the data bias caused by the excessive concentration of local measuring points, so that the representative value of the region micro water can better reflect the true state of the entire communication region. The representative value of the region micro water calculated by the weighted average eliminates the influence of uneven distribution of measuring points. The SF6 gas micro water content limit value specified by the industry standard is determined according to the voltage level of the equipment. For equipment with voltage level of 500kV and above, the excellent limit value is 150μL / L, and the qualified limit value is 300μL / L; for equipment with voltage level of 220kV, the excellent limit value is 300μL / L, and the qualified limit value is 500μL / L.

[0038] Preferably, in determining the micro-water concentration level of the communicating gas chamber, the dispersion degree of the measured point data is also considered in addition to the comparison with the standard limit value. If the standard deviation of each measured point in the communicating area exceeds 10% of the average value, even if the average value is within the qualified range, the concentration level of the area will be upgraded by one level to reflect the unevenness of the micro-water distribution in the area. In subsequent evaluation, if the standard deviation of the measured point data in a certain area is 12% of the average value, the concentration level of the area will be directly upgraded from qualified to attention.

[0039] Illustratively, a communicating area of a certain substation contains 6 measured points, and the micro-water content detection values of the measured points are 280, 285, 290, 295, 300 and 305 μL / L, respectively. The maximum relative deviation is calculated to be 3.6%, which is less than the similarity threshold value of 5%, and it is determined to be a similar data group. According to the spatial distribution of the measured points, 4 measured points are located in the same grid, and the weight coefficient is 0.25. The other 2 measured points are located in different grids, and the weight coefficient of each is 1. The calculated micro-water representative value of the area is 289 μL / L, which corresponds to the second concentration level.

[0040] S105, analyze the independent partition range in the gas chamber communication distribution map, extract the micro-water content of the measured point grouping list in the independent partition, evaluate the deviation degree of the independent partition micro-water content from the equipment qualified standard, and obtain the independent gas chamber defect category.

[0041] The gas chamber numbers of all independent partitions are identified from the gas chamber communication distribution map. The measured point numbers and their micro-water content detection values in each independent partition are queried according to the measured point grouping list. For an independent partition with only a single measured point, the measured point value is directly used as the representative value of the area. For an independent partition containing multiple measured points, the maximum micro-water content value is selected as the representative value of the area to form a set of independent partition micro-water representative values. Each representative value in the set of independent partition micro-water representative values is compared with the equipment qualified standard limit value. When the representative value exceeds the qualified limit value, the over-standard proportion is calculated, i.e. the representative value minus the qualified limit value divided by the qualified limit value. When the representative value does not exceed the qualified limit value, the over-standard proportion is zero, and the over-standard degree data of each independent partition is obtained. Based on the over-standard degree data, when the over-standard proportion is zero, the independent partition is determined to be the no-defect category. When the over-standard proportion is greater than zero and less than 20%, the independent partition is determined to be the mild defect category. When the over-standard proportion is greater than or equal to 20%, the independent partition is determined to be the severe defect category. An independent gas chamber defect category table containing independent partition numbers and defect category identifiers is established.

[0042] Specifically, in one implementation, the identification of independent zones is based on the closed state of the valves between gas chambers. When all connecting valves of a gas chamber are closed, that chamber forms an independent zone, and the SF6 gas inside cannot exchange with other gas chambers. This isolation means that the moisture content within an independent zone depends entirely on the sealing performance and adsorbent state of that area itself, thus requiring an evaluation method different from that for connected areas. For independent zones with multiple measuring points, the maximum moisture content is chosen as the representative value for the area because the gas does not circulate within the independent zone, potentially leading to localized moisture accumulation. Using the maximum value reflects the worst moisture condition within the independent zone, avoiding the masking of severe local exceedances by average values. This conservative evaluation method helps to promptly identify potential insulation hazards. The exceedance ratio is calculated using a relative value method, that is, the difference between the measured moisture content and the acceptable standard limit is divided by the acceptable standard limit. When the moisture content in a certain independent zone is 400 μL / L, and the acceptable limit for equipment at that voltage level is 300 μL / L, the excess percentage is calculated as (400-300) / 300×100%=33.3%. This relative value calculation method can unify the evaluation standards for equipment at different voltage levels.

[0043] Preferably, the defect categories are divided into three levels. The no-defect category indicates that the moisture content is within the acceptable limit and the equipment can operate normally; the mild defect category corresponds to an excess rate of 0-20%, at which point the equipment has excess moisture but has not yet reached a serious level, and it is recommended to increase the monitoring frequency; the severe defect category corresponds to an excess rate of more than 20%, indicating that there is a serious moisture problem in this independent area, and drying measures need to be taken immediately.

[0044] In one possible implementation, the independent chamber defect category table also includes a preliminary judgment field for the cause of the defect. By analyzing the historical trend of trace moisture content changes in the independent compartments, a continuous upward trend in trace moisture content may indicate sealing failure; a sudden increase in trace moisture content may indicate saturation failure of the internal adsorbent. In subsequent evaluation processes, based on the judgment result of this field and combined with other test data, targeted maintenance strategies are prioritized to improve defect handling efficiency.

[0045] For example, a 500kV substation has three independent zones with representative values ​​of trace moisture content of 280μL / L, 360μL / L and 450μL / L, respectively. The corresponding exceedance rates are 0%, 20% and 50%, respectively. Therefore, the defect categories are determined as no defect, slight defect and severe defect, respectively.

[0046] S106, according to the micro water concentration level of the communication gas chamber and the defect category of the independent gas chamber, adjust the influence proportion of each measuring point in the measuring point grouping list, reevaluate the representative strength of the micro water content in combination with the spatial distribution difference of the communication gas chamber and the independent gas chamber, and determine the adjusted comparison basis group.

[0047] Read the micro water concentration level of the communication gas chamber and the defect category of the independent gas chamber, distribute corresponding weight values according to the severity of the concentration level and the defect category, the higher the concentration level, the greater the weight value, the more serious the defect category, the greater the weight value, and form an initial weight configuration table of each gas chamber. Obtain the initial weight configuration table and the measuring point grouping list, adjust the influence proportion of each measuring point in the overall evaluation according to the weight value of the gas chamber to which each measuring point belongs, multiply the original weight of the measuring point by the weight value of the gas chamber to which it belongs, and record the spatial coordinate position of each measuring point at the same time, obtain the measuring point weight distribution data containing the adjusted weight and the spatial position. Based on the measuring point weight distribution data, the ratio of the number of measuring points in the communication gas chamber to the number of measuring points in the independent gas chamber is calculated. When the number of measuring points in the communication gas chamber exceeds the preset multiple of the number of measuring points in the independent gas chamber, the representative coefficient of the measuring points in the independent gas chamber is increased. When the number of measuring points in the independent gas chamber exceeds the preset multiple of the number of measuring points in the communication gas chamber, the representative coefficient of the measuring points in the communication gas chamber is increased. Obtain the spatial distribution adjustment coefficient table. According to the spatial distribution adjustment coefficient table, the adjusted weight of each measuring point in the measuring point weight distribution data is corrected, the adjusted weight is multiplied by the corresponding spatial distribution adjustment coefficient to obtain the final weight value, the final weight value and the micro water content data of all measuring points are summarized, and the adjusted comparison basis group containing the measuring point number, the final weight and the micro water content is constructed.

[0048] Specifically, in one embodiment, the establishment of the initial weight configuration table is based on the severity assessment of the gas chamber state. The micro-water concentration level of the connected gas chamber reflects the degree of micro-water pollution in the entire connected area, and the higher the level, the more serious the insulation performance of the area, and therefore a higher weight value needs to be assigned. The independent gas chamber defect category reflects the degree of local sealing failure or adsorbent failure, and the more serious the defect, the greater the proportion of the gas chamber in the overall assessment. This differentiated weight allocation mechanism can ensure that the serious problem areas are fully valued in subsequent device state assessment. The allocation of weight values adopts an incremental approach to ensure that there is a clear distinction between different severity levels. For connected gas chambers, the first level concentration level indicates that the micro-water content is within the normal range, and the baseline weight is assigned; the second level indicates mild over-standard, and the weight is moderately increased; the third level indicates serious over-standard, and the weight is significantly increased. The weight allocation of independent gas chambers follows similar principles, with the defect-free category using the baseline weight, and the mild defect and severe defect increasing in turn. The initial weight configuration table records the number, type, state level and corresponding weight value of each gas chamber. The adjustment process of the measurement point influence ratio involves two key elements: the original weight of the measurement point and the weight of the gas chamber to which it belongs. The original weight of the measurement point is usually pre-set according to the measurement accuracy, historical reliability and other factors of the measurement point, while the weight of the gas chamber comes from the initial weight configuration table. The adjusted weight obtained by multiplying the two reflects the importance of the location of the measurement point and the severity of the gas state at that location. The spatial coordinate position information recorded at the same time provides basic data support for subsequent spatial distribution analysis.

[0049] Preferably, the core of the spatial distribution adjustment is to balance the representativeness of measurement points of different types of gas chambers. In actual substation equipment, connected gas chambers are often equipped with more measurement points for monitoring due to gas flow, while independent gas chambers may have fewer measurement points due to their relative independence. When the number of connected gas chamber measurement points far exceeds that of independent gas chambers, if no adjustment is made, the abnormal conditions of independent gas chambers may be masked by the large number of normal data from connected gas chambers. By comparing the ratio of the number of measurement points of the two types of gas chambers with the preset multiple, this imbalance can be identified. When the ratio exceeds the preset multiple, the representativeness coefficient of the side with fewer measurement points is increased, so that its influence in the overall assessment is strengthened. This adjustment mechanism ensures that the actual conditions of each region can be reasonably reflected in the final assessment even if the measurement points are unevenly distributed.

[0050] In a possible implementation, the construction of the spatial distribution adjustment coefficient table also considers the spatial aggregation degree of the measuring points. The spatial dispersion degree of the measuring points in each type of gas chamber is calculated. If the measuring points of a type of gas chamber are highly concentrated in a specific area, the representative coefficient is reduced; if the distribution is uniform, the representative coefficient is increased. In addition to simple quantity comparison, the spatial dispersion degree of the measuring points in each type of gas chamber is also calculated. If the measuring points of a type of gas chamber are highly concentrated in a specific area, the representative coefficient is reduced accordingly, because the concentrated measuring points may repeatedly reflect the information of the same area. On the contrary, the measuring points with uniform spatial distribution can more comprehensively reflect the overall condition of the gas chamber, and therefore obtain a higher representative coefficient.

[0051] Exemplarily, the adjusted weight is multiplied by the spatial distribution adjustment coefficient to obtain the final weight value, which comprehensively considers the influence of three dimensions of the gas chamber state severity, the original characteristics of the measuring points, and the spatial distribution factor. This multi-dimensional weight adjustment mechanism can more accurately reflect the contribution of each measuring point in the overall evaluation of the device. Further, the adjusted comparison basis group contains the measuring point number as the unique identifier, the final weight value as the influence factor of the measuring point in the evaluation, and the micro-water content as the actual detection data. The combination of these three fields provides complete basic data for subsequent comprehensive evaluation of the device state.

[0052] It can be understood that through this multi-level weight adjustment mechanism, the key area anomaly that may be ignored can be appropriately strengthened in the final comparison basis group, and the influence of the measuring point data with high repeatability is reasonably weakened, so that a more balanced and accurate device state evaluation basis is realized.

[0053] S107, comparing the adjusted comparison basis group with the device qualification standard in the historical test database, distinguishing different judgment thresholds of the connected area and the independent area, identifying the gas chamber area with deviation exceeding the allowable error range, and obtaining a deviation area list.

[0054] From the adjusted comparison basis group, the final weight and micro-water content data of each measuring point are extracted, the qualified standard limit value of the corresponding voltage level device in the historical test database is queried, the weighted average value of the micro-water content of all measuring points in the connected area is used as the comparison reference, the maximum value of the micro-water content in the independent area is used as the comparison reference, and a regional comparison data set is formed. The comparison reference of each region in the regional comparison data set is subtracted from the corresponding qualified standard limit value to obtain the deviation value of each region. If the deviation value exceeds the preset allowable error range, the gas chamber region is marked as a deviation region, and its region number, deviation value and over-standard type are recorded to form a deviation region list.

[0055] Specifically, in one embodiment, the construction of the region comparison dataset takes into account the different characteristics of connected regions and independent regions. In a connected region, the micro water content of each measuring point tends to be balanced due to the flow of gas, so using a weighted average value can reflect the overall state. In an independent region, there may be local micro water accumulation due to the lack of gas flow, so using the maximum value as the comparison benchmark can better reflect potential risks. The historical test database stores qualified standard limits for equipment at different voltage levels and different operating years. These standard limits are empirical values based on a large number of historical failure cases and test data statistics, reflecting the boundary conditions for safe operation of equipment. The allowed error range takes into account the accuracy of measuring instruments and the influence of environmental factors. It is usually set to 5% to 10% of the qualified standard limit, which can tolerate normal measurement errors and detect real abnormal conditions in time.

[0056] Preferably, the over-limit types in the deviation region list include three levels of slight over-limit, moderate over-limit and severe over-limit, which correspond to different treatment measures. Slight over-limit suggests increasing monitoring frequency, moderate over-limit requires scheduled maintenance, and severe over-limit requires immediate power-off treatment.

[0057] S108, in combination with the deviation region list and the gas chamber connectivity distribution map, differentiating between independent gas chamber local defects and connected gas chamber overall abnormalities, locating the corresponding abnormal measuring points, and obtaining the substation test comparison analysis results.

[0058] Read the region number and deviation value in the deviation region list, and combine the region type information in the gas chamber connectivity distribution map. For independent regions, mark the deviation as a local defect type, and for connected regions, mark the deviation as an overall abnormal type. Establish a classification record table containing region number, deviation value and abnormal type. Based on the classification record table, find all measuring points in each deviation region from the measuring point grouping list, extract measuring point number, micro water content value and spatial position information, associate measuring point information with corresponding abnormal type and deviation degree, and summarize to form substation test comparison analysis results containing abnormal measuring point positioning, abnormal type and deviation degree.

[0059] Specifically, the establishment of the classification record table is based on the correspondence between the area type and the abnormal form. Due to the closed characteristics of the independent area, the internal gas cannot exchange with the outside world, and the abnormality often occurs in the specific area, so it is classified as a local defect. The connected area can flow gas between multiple chambers, and the abnormality at a certain point will gradually spread to the entire connected area, showing the overall abnormal characteristics. The comparison analysis result of the substation test is recorded in table form, each record contains the unique number of the abnormal measuring point, the three-dimensional spatial coordinates of the measuring point, the gas chamber number, the area type, the measured value of the micro water content, the standard limit value, the deviation degree and the abnormal type classification. This structured recording method facilitates maintenance personnel to quickly locate the problem area and develop targeted treatment measures. For the local defect type of abnormality, only the specific independent gas chamber needs to be dried or the adsorbent needs to be replaced. For the overall abnormal type, comprehensive management of the entire connected area is needed, including finding the leakage point, replacing the sealing element or performing overall drying treatment on all connected chambers, which significantly increases the workload and complexity of the treatment.

[0060] The application provides a substation test index automatic comparison analysis system, which comprises: A data acquisition module is configured to acquire the SF6 micro water content of each measuring point in the substation, the opening and closing of the chamber isolation valve and the gas chamber number to which the measuring point belongs. A connected analysis module is configured to identify the connection path and independent partition boundary between the chambers according to the opening and closing of the chamber isolation valve, and obtain a chamber connection distribution map by means of the different states of the connected chambers and the isolated chambers. A measuring point grouping module is configured to extract the installation coordinates of each measuring point in the connected chambers or the independent partitions according to the chamber connection distribution map, identify the chamber to which the measuring point belongs, and obtain a measuring point grouping list. An identification module is configured to identify the micro water concentration grade of the connected chambers according to the chamber connection distribution map and the measuring point grouping list. A first determination module is configured to extract the micro water content of the measuring points in the independent partitions, evaluate the deviation degree of the micro water content of the independent partitions from the equipment qualification standard, and obtain the independent chamber defect category. A second determination module is configured to adjust the influence proportion of each measuring point in the measuring point grouping list according to the micro water concentration grade of the connected chambers and the independent chamber defect category, reevaluate the representative strength of the micro water content, and determine an adjusted comparison basis group. A deviation analysis module is configured to compare the adjusted comparison basis group with the equipment qualification standard in the historical test database, distinguish the different determination thresholds of the connected area and the independent area, identify the chamber area whose deviation exceeds the allowable error range, and obtain a deviation area list. A positioning module is configured to locate the abnormal measuring point in combination with the deviation area list and the chamber connection distribution map.

[0061] The above examples are only used to illustrate the technical solutions of the present application but not limit the present application. The present application is described in detail only with reference to the preferred embodiments. Those skilled in the art should understand that the technical solutions of the present application can be modified or equivalently replaced without departing from the spirit and scope of the present application, and all the modifications and equivalents should be included in the scope of the claims of the present application.

Claims

1. An automatic comparison and analysis method for substation test indicators, characterized in that, include: Collect data on SF6 moisture content, the opening and closing status of gas chamber isolation valves, and the gas chamber number to which the measuring point belongs at each measuring point in the substation. Based on the opening and closing status of the gas chamber isolation valve, the connection paths and independent partition boundaries between each gas chamber are identified by different states of the connected gas chamber and the isolation gas chamber, and a gas chamber connection distribution map is obtained. Based on the gas chamber connectivity distribution map, the installation coordinates of each measuring point in the connected gas chamber or independent partition are extracted, the gas chamber affiliation of the measuring point is identified, and a measuring point group list is obtained. Based on the gas chamber connectivity distribution diagram and the measurement point grouping list, identify the micro-water concentration levels in the connected gas chambers; Extract the trace moisture content at measurement points within an independent zone, assess the deviation of the trace moisture content in the independent zone from the equipment qualification standard, and obtain the defect category of the independent air chamber; Based on the micro-water concentration level of the connected air chamber and the defect category of the independent air chamber, after adjusting the influence ratio of each measuring point in the measuring point group list, the representativeness of the micro-water content is re-evaluated, and the adjusted comparison basis group is determined. The adjusted comparison criteria group is compared with the equipment qualification standards in the historical test database. Different judgment thresholds for connected regions and independent regions are distinguished, and air chamber regions with deviations exceeding the allowable error range are identified to obtain a list of deviation regions. By combining the list of deviation areas with the gas chamber connectivity distribution map, abnormal measurement points are located.

2. The automatic comparison and analysis method for substation test indicators according to claim 1, characterized in that, The process of collecting SF6 moisture content, gas chamber isolation valve opening and closing status, and gas chamber number of each measuring point in the substation from the test database includes: reading the real-time monitoring records of each measuring point of the SF6 gas insulation equipment through the historical data interface of the substation monitoring system, extracting the measuring point number, the gas chamber number, and the gas chamber isolation valve number, obtaining the current opening and closing status signal of the gas chamber isolation valve from the equipment ledger, and forming a correspondence record between measuring points and gas chambers; querying the most recent SF6 moisture content detection value of each measuring point according to the measuring point number in the correspondence record, reading the detection timestamp, extracting the valve opening and closing status corresponding to the opening and closing status signal, and generating a test data table.

3. The automatic comparison and analysis method for substation test indicators according to claim 1, characterized in that, The process of identifying the connection paths and independent partition boundaries between air chambers based on the opening and closing status of the air chamber isolation valves, and obtaining an air chamber connection distribution map, includes: reading the air chamber number and its corresponding isolation valve opening and closing status, establishing a record of the connection relationships between air chambers; if there is a valve between two air chambers and the valve is in the open state, it is marked as a direct connection relationship; if the valve is closed, it is marked as an isolation relationship, forming an air chamber connection status table; based on the connection status table, starting from any air chamber, searching for all air chambers directly connected to it, and then recursively searching for those connected to these air chambers... The process of searching for all directly connected air chambers, starting from any air chamber, continues until no new connected air chambers are found, resulting in a set of connected air chambers. For air chambers not included in any connected set, this process is repeated, starting from any air chamber, to find all air chambers directly connected to it, and then recursively searching for other air chambers connected to these air chambers until no new connected air chambers are found. This process yields a set of all connected air chambers and a set of independent air chambers. A unique region identifier is assigned to each set, the air chamber numbers within the set and their interconnections are recorded, and the locations of connection paths and isolation boundaries are marked. This generates a connected air chamber distribution map that includes the region affiliation of each air chamber, the direction of the connection paths, and the boundaries of independent partitions.

4. The automatic comparison and analysis method for substation test indicators according to claim 1, characterized in that, The process involves extracting the installation coordinates of each measuring point within a connected air chamber or independent partition from the air chamber connectivity distribution map, identifying the air chamber affiliation of each measuring point, and obtaining a measuring point group list. This includes: reading the air chamber number set of each connected area and independent partition from the air chamber connectivity distribution map; querying the three-dimensional installation coordinate data of each measuring point; extracting the physical boundary coordinate range of each air chamber; matching the measuring point coordinates with the air chamber boundary range; determining the air chamber to which the measuring point belongs based on the coordinate inclusion relationship; classifying and summarizing all measuring points according to the region number; and generating the measuring point group list containing the measuring point number and the region number to which it belongs.

5. The automatic comparison and analysis method for substation test indicators according to claim 1, characterized in that, The identification of the micro-water concentration level of the connected air chamber includes: extracting the micro-water content detection values ​​of all measuring points in the same connected area, calculating the relative deviation between measuring points to determine similarity, generating similar data groups based on similarity, reducing the weight ratio of measuring points with similar spatial locations in the similar data groups, and using a weighted average method to calculate the comprehensive value of micro-water content in the connected area to obtain the micro-water concentration level of the connected air chamber.

6. The automatic comparison and analysis method for substation test indicators according to claim 1, characterized in that, The process of extracting the trace moisture content at measuring points within independent zones, assessing the deviation of the trace moisture content of independent zones from the equipment qualification standards, and obtaining the defect category of independent air chambers includes: identifying all independent zones; using the value of a single measuring point as a representative value for independent zones with only one measuring point; selecting the maximum trace moisture content as a representative value for independent zones with multiple measuring points; calculating the excess ratio; determining the category of no defect, minor defect, or severe defect based on the excess ratio; and establishing the defect category table for independent air chambers.

7. The automatic comparison and analysis method for substation test indicators according to claim 1, characterized in that, The process involves adjusting the influence ratio of each measuring point in the measuring point grouping list based on the micro-moisture concentration level of the connected air chamber and the defect category of the independent air chamber, then re-evaluating the representativeness of the micro-moisture content, and determining the adjusted comparison basis group. This includes: reading the micro-moisture concentration level of the connected air chamber and the defect category of the independent air chamber, assigning corresponding weight values ​​according to the severity of the concentration level and defect category to form an initial weight configuration table for each air chamber; multiplying the original weight of each measuring point by the weight value of its respective air chamber according to the initial weight configuration table and the measuring point grouping list, while recording the spatial coordinate position of the measuring point to obtain measuring point weight distribution data containing the adjusted weight and spatial position; calculating the ratio of the number of measuring points in the connected air chamber to the number of measuring points in the independent air chamber, determining the spatial distribution adjustment coefficient based on the ratio, correcting the adjusted weight of each measuring point in the measuring point weight distribution data to obtain the final weight, summarizing the final weight and micro-moisture content data of all measuring points, and constructing the adjusted comparison basis group containing the measuring point number, final weight, and micro-moisture content.

8. The automatic comparison and analysis method for substation test indicators according to claim 1, characterized in that, The process of obtaining the list of deviation regions includes: extracting the final weight value and trace moisture content data of each measuring point, determining the comparison benchmark for connected regions, using the maximum trace moisture content as the comparison benchmark for independent regions, calculating the deviation value, marking the deviation regions, and generating the list of deviation regions.

9. The automatic comparison and analysis method for substation test indicators according to claim 1, characterized in that, The process of locating abnormal measurement points includes: reading the region number in the deviation region list, marking independent regions as local defect types and connected regions as overall abnormal types, searching for measurement points in each deviation region from the measurement point grouping list, associating the measurement point information with the abnormal type and deviation degree, and generating substation test comparison analysis results.

10. An automatic comparison and analysis system for substation test indicators, characterized in that, The system includes: The data acquisition module is used to collect the SF6 moisture content, the opening and closing status of the gas chamber isolation valves, and the gas chamber number to which the measuring point belongs at each measuring point in the substation. The connectivity analysis module is used to identify the connectivity paths and independent partition boundaries between each air chamber based on the opening and closing status of the air chamber isolation valves, and to obtain an air chamber connectivity distribution map by different states of connected air chambers and isolation air chambers. The measuring point grouping module is used to extract the installation coordinates of each measuring point in the connected air chamber or independent partition for the air chamber connectivity distribution map, identify the air chamber belonging to the measuring point, and obtain the measuring point grouping list. The identification module is used to identify the micro-water concentration level of the connected air chambers based on the air chamber connectivity distribution map and the measuring point grouping list; The first determination module is used to extract the trace moisture content of the measuring points in the independent zone, assess the degree of deviation between the trace moisture content of the independent zone and the equipment qualification standard, and obtain the defect category of the independent air chamber. The second determining module is used to re-evaluate the representativeness of the micro-water content and determine the adjusted comparison basis group after adjusting the influence ratio of each measuring point in the measuring point group list according to the micro-water concentration level of the connected air chamber and the defect category of the independent air chamber. The deviation analysis module is used to compare the adjusted comparison criteria group with the equipment qualification standards in the historical test database, distinguish different judgment thresholds for connected regions and independent regions, identify air chamber regions where the deviation exceeds the allowable error range, and obtain a list of deviation regions. The positioning module is used to locate abnormal measurement points by combining the list of deviation areas with the air chamber connectivity distribution map.

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