Method and system for testing high-low voltage gas-insulated switchgear by replacing SF6 with environment-friendly insulating gas

Abstract

The invention relates to the technical field of data acquisition control, in particular to a high-low voltage gas-insulated switchgear testing method and system for replacing SF6 with environment-friendly insulating gas, and the method comprises the following steps: extracting the change relation between pressure and conductivity, judging the trend consistency, recognizing a conductivity path, analyzing a potential difference, screening a concentrated region, judging the trend stability, and screening an evolution fragment. According to the method, the stable time period is screened by extracting the corresponding relation between the pressure and the conductivity change, the closed region is constructed in combination with the conductive trend consistent path, the space focusing precision is improved, the potential difference and the space distribution are fused to recognize the sudden change path, and the region boundary is defined. The method is advantaged in that local feature extraction capability is enhanced, continuous evolution fragments are screened in combination with time sequence conductance response, space-time labeling of a breakdown trend is realized, a space field intensity spectrum with conductivity and potential difference fusion is constructed, fault prediction precision and timeliness are improved, and equipment breakdown risk early warning capability is enhanced.

Description

Technical Field

[0001] This invention relates to the field of data acquisition and control technology, and in particular to a testing method and system for high and low voltage gas-filled switchgear that uses environmentally friendly insulating gas instead of SF6. Background Technology

[0002] The field of data acquisition and control technology involves the real-time acquisition, transmission, processing, and control of various physical quantities, electrical quantities, and environmental parameters. Its core aspects include sensor data acquisition, signal conversion, electrical quantity monitoring, automatic acquisition process control, and data recording and management. This technology field completes the parameter acquisition and system control process by establishing information acquisition channels, applying control logic instructions, and combining embedded systems, and has a high degree of automation and continuous operation capability. Among them, the traditional environmentally friendly insulating gas substitution test method for high and low voltage gas-filled switchgear using SF6 refers to manually measuring and recording parameters such as breakdown voltage, gas withstand voltage level, and breakdown distance of the equipment under different insulating gases by using standardized gas substitution devices and basic voltage and current detection instruments, under the condition of manual circuit connection. It often adopts constant voltage interval testing method or voltage increase step-by-step observation method, and is supplemented by high voltage source, leakage tester, and power frequency withstand voltage test equipment to determine the status of the equipment and record insulation performance data.

[0003] Traditional testing methods rely on manual connection to the detection circuit and constant or increased voltage to test equipment parameters item by item. This manual approach, dependent on point-by-point pressure application, observation, and recording, cannot avoid the accumulation of errors due to subjective human judgment. Manual testing lacks the ability to dynamically respond to gas diffusion processes, failing to identify whether diffusion has stabilized. This results in unremoved data fluctuations or abnormal interference during the testing phase, affecting the validity of the results. The trend of conductivity changes in the spatial path cannot be identified holistically, often focusing only on a fixed point, easily overlooking the spatial distribution of localized features. Potential difference analysis relies on point-to-point measurements, unable to accurately determine the continuity and abrupt changes in the electric field distribution, causing a lag in the determination of the breakdown critical region and affecting the foresight of equipment safety assessments. Without considering continuous changes over time, it is difficult to dynamically assess the breakdown trend; test results are mostly static parameter records, making it difficult to establish early warning models. For example, in real-world environments, starting testing before the gas has fully and uniformly diffused, or failing to identify risks in advance due to the absence of clear breakdown indicators, can lead to delays in handling abnormal equipment conditions and create safety hazards. Summary of the Invention

[0004] To address the technical problems existing in the prior art, embodiments of the present invention provide a testing method for high and low voltage gas-filled switchgear using environmentally friendly insulating gas as a substitute for SF6, comprising the following steps: To achieve the above objectives, the present invention adopts the following technical solution: a testing method for high and low voltage gas-filled switchgear using environmentally friendly insulating gas instead of SF6, comprising the following steps: S1: Acquire pressure and conductivity sensor data from the gas injection port and buffer cavity of the high and low pressure gas holder, extract the correspondence between pressure changes and conductivity responses in adjacent time periods, determine trend consistency, and generate diffusion stability period labeling information; S2: Based on the time range of the diffusion stabilization period labeling information, call the conductivity measurement point location and conductivity data within the period, identify the path with the same direction of conductivity change, and generate a preliminary closed structure diagram of the path; S3: Obtain the measurement point information in the preliminary closed structure diagram of the path, extract the potential difference and spatial distribution between paths, identify path segments with strong potential changes, filter spatially concentrated feature areas, and generate a set of region boundary coordinates; S4: Based on the spatial region formed by the boundary coordinate set of the region, call the conductivity response data sequence, determine the stability of the conductivity value change trend, filter the spatial segments of continuous evolution characteristics, and generate a breakdown trend evolution time label set; S5: Call the spatiotemporal range identified by the breakdown trend evolution time tag set, extract the conductivity and potential difference of the associated measurement points, construct a spatial field strength identification map, mark the prominent areas of trend change, and generate a spatial positioning map of the breakdown critical area.

[0005] As a further aspect of the present invention, the diffusion stabilization period annotation information includes a time range, a stable segment index, and a trend consistency index; the preliminary path closure structure diagram includes a set of measurement point paths, a spatial closed loop, and topological connection relationships; the regional boundary coordinate set includes boundary point coordinates, a boundary contour sequence, and a coordinate reference system; the breakdown trend evolution time label set includes time labels, spatial segment numbers, and evolution category identifiers; and the breakthrough critical region spatial positioning map includes critical region spatial coordinates, a field strength distribution layer, and risk level annotations.

[0006] As a further aspect of the present invention, the specific steps of S1 are as follows: S101: Acquire the sampling data of the gas pressure sensor and conductivity sensor set in the gas injection port and buffer cavity of the high and low pressure gas holder, extract the pressure sampling value sequence and conductivity sampling value sequence for continuous time periods, calculate the pressure change rate and conductivity change rate between each segment, mark the change direction, and generate a change direction marking sequence. S102: Based on the change direction marking sequence, determine whether the change direction of pressure and conductivity is consistent at each time point, filter the intervals with consistent change direction and meet the time continuity requirement, and obtain the interval segments with consistent change trend. S103: Based on the intervals with consistent trends, calculate the mean square difference between the rate of change of pressure and the rate of change of conductivity within the intervals, filter the intervals with fluctuations lower than the set benchmark, add label information, and generate diffusion stability period label information.

[0007] As a further aspect of the present invention, the specific steps of S2 are as follows: S201: Based on the time range marked in the diffusion stabilization period labeling information, call up the spatial location information and conductivity data collected by the conductivity probe in the high-pressure gas-filling cabinet within the time period, extract the conductivity change trend identifier of each measuring point within the corresponding time period, integrate them into a sequence according to the measuring point number order, and generate the measuring point conductivity trend sequence. S202: Based on the conductivity trend sequence of the measurement points, identify the combination of measurement points with the same direction of conductivity change in continuous measurement points, retain the measurement point path with the continuous and consistent direction of conductivity change, and record the spatial location information to obtain the consistent measurement point path location information; S203: Call the consistent measurement point path location information, connect adjacent measurement point locations in sequence, identify path sequences where the starting point and ending point spatial coordinates coincide or are close, construct the corresponding path loop structure, draw the structure wireframe graphic, and generate a preliminary closed structure diagram of the path.

[0008] As a further aspect of the present invention, the specific steps of S3 are as follows: S301: Obtain the path number and spatial coordinates of the measuring points marked in the preliminary closed structure diagram of the path, extract the potential value and corresponding position of the measuring points in the path segment, calculate the potential gradient of the path segment based on the potential difference and positional relationship between the measuring points, and generate the potential gradient sequence of the path segment. S302: Based on the potential gradient sequence of the path segment, the potential gradient values ​​of the path segment are filtered, and the path segments with potential gradients exceeding a set threshold are retained. The measurement point number and position of the corresponding path segment are extracted to obtain the coordinate set of high gradient path segments. S303: Call the coordinate set of the high gradient path segment, analyze the positional distribution characteristics between the measurement points, identify the combination of measurement points whose spatial distance satisfies the concentrated characteristics, extract the boundary points to form a closed contour, and generate the regional boundary coordinate set.

[0009] As a further aspect of the present invention, the specific steps of S4 are as follows: S401: Based on the spatial range defined by the region boundary coordinate set, obtain the conductivity response data sequence of the location within the region, extract the conductivity value sequence of the location changing with time, and organize and sort to generate a regional conductivity time series sequence; S402: Call the regional conductivity time series, and based on the characteristics of conductivity value change in a continuous time period, determine whether the conductivity trend is stable according to the conductivity change stability benchmark value, extract the segment numbers that meet the stability conditions, and obtain a set of stable change segment numbers; S403: Based on the time range corresponding to the stable change segment number set, extract the conductivity sequence of the location within the time period in the region, identify spatial segments with continuous evolution characteristics, and generate a breakdown trend evolution time label set.

[0010] As a further aspect of the present invention, the specific steps of S5 are as follows: S501: Call the time period and spatial range identified by the breakdown trend evolution time tag set, extract the conductivity and potential difference data of the corresponding measurement points, organize the joint parameter values ​​of the measurement point locations, and generate a joint dataset of regional conductivity and potential. S502: Based on the parameter values ​​of the measurement points in the joint dataset of regional electrical conductivity potentials, calculate the electric field strength at the corresponding spatial location, establish the correspondence between the measurement point location and the electric field strength, and obtain the spatial field strength identification map. S503: Based on the electric field intensity change value in the spatial field strength identification map, according to the change trend threshold, filter the location points that exceed the threshold, mark the spatial location, and generate a spatial positioning map of the breakdown critical region.

[0011] As a further aspect of the present invention, the conductivity sensor is a detection element used to measure the conductivity of environmentally friendly alternative gases inside the gas filling cabinet. The relationship between pressure change and conductivity response refers to the dynamic trend between the rate of change of gas pressure and the corresponding magnitude of change of conductivity within a unit time interval.

[0012] As a further aspect of the present invention, the potential difference refers to the numerical difference between voltage signals collected by spatially adjacent measuring points at the same time. The spatial distribution refers to the spatial location information of all electrical conductivity measurement points or potential acquisition points inside the high and low voltage gas-filled switchgear, which is represented in a three-dimensional coordinate format. The spatial concentration feature refers to the distribution pattern in which multiple path segments with high electric field strength or potential abrupt change properties are arranged in a clustered state in three-dimensional space. The trend stability refers to the time series characteristic that the change in conductivity over time is within a defined range of change over a continuous period of time, and that the direction of change remains consistent. The continuous evolution characteristic refers to the conductivity maintaining a unidirectional change trend across multiple time segments, without any reversal or sudden jumps in direction. The spatial field strength identification spectrum refers to a three-dimensional spatial visualization structure constructed based on the conductivity and potential difference data of the measurement points; The region of significant change refers to a spatial segment in the coupled spectrum of conductivity and potential difference that is identified as having a continuously increasing rate of change that exceeds a set judgment threshold. The region is composed of multiple conductivity measurement points in spatial coordinates, reflecting the trend of concentrated changes in electric field distribution intensity or abrupt changes in electrical parameters. The aforementioned spatial location map of the breakdown critical region refers to a data structure graph constructed based on the coupling trend of conductivity and potential difference, which identifies the spatial coordinate information of the region where the electric field intensity changes abruptly.

[0013] A testing system for high and low voltage gas-filled switchgear using environmentally friendly insulating gases as a substitute for SF6 includes: The diffusion monitoring module collects data from gas pressure sensors and conductivity sensors installed in the gas injection port and buffer chamber of the high and low pressure gas holder. It extracts pressure change sequences and conductivity response sequences in adjacent time periods, determines whether the change directions of the two sets of data are consistent, identifies continuous data intervals with consistent directions, detects the stability of conductivity changes within the identified intervals, obtains time periods that meet stability requirements, and generates diffusion stability period labeling information. The path construction module, based on the time range indicated in the diffusion stabilization period annotation information, calls the spatial location information and conductivity data of the conductivity probe inside the high-voltage gas-filled cabinet within the time period, identifies the measurement point path with the same direction of conductivity change, extracts the path set that forms a closed structure based on the spatial relationship between the start and end points of the path, and generates a preliminary closed structure diagram of the path. The region extraction module obtains the identified measurement point path information in the preliminary closed structure diagram of the path, extracts the potential difference and spatial location data between path segments, calculates the potential change intensity between path segments, filters regions with spatial concentration characteristics, extracts the coordinate information of spatial boundaries, and generates a region boundary coordinate set. The trend recognition module calls the conductivity response data of the corresponding measurement points in the region based on the coordinate range marked by the region boundary coordinate set, judges whether the change trend of conductivity value in time series is stable, filters spatial segments with continuous evolution characteristics, and generates a breakdown trend evolution time label set. The critical location module calls the time interval and spatial range identified in the breakdown trend evolution time tag set, extracts the conductivity value and potential difference data of the associated measurement points, constructs a spatial field strength identification map, locates the area with a prominent field strength change trend, and generates a spatial location map of the breakdown critical area.

[0014] Compared with the prior art, the advantages and positive effects of the present invention are as follows: In this invention, stable periods are screened by extracting the correspondence between pressure and conductivity changes, and closed regions are constructed by combining the consistent conductivity trend path to improve spatial focusing accuracy. Sudden change paths are identified by fusing potential difference and spatial distribution, clarifying regional boundaries and enhancing local feature extraction capabilities. Continuous evolution segments are screened by combining time series conductivity response to achieve spatiotemporal labeling of breakdown trends. A spatial field strength map fused with conductivity and potential difference is constructed to improve the accuracy and timeliness of fault prediction and enhance the early warning capability of equipment breakdown risk. Attached Figure Description

[0015] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0016] Figure 1 This is a schematic diagram of the steps of the present invention; Figure 2 This is a detailed schematic diagram of S1 of the present invention; Figure 3 This is a detailed schematic diagram of S2 of the present invention; Figure 4 This is a detailed schematic diagram of S3 of the present invention; Figure 5 This is a detailed schematic diagram of S4 of the present invention; Figure 6 This is a detailed schematic diagram of S5 of the present invention; Figure 7 This is a system module diagram of the present invention. Detailed Implementation

[0017] The technical solution of the present invention will now be described with reference to the accompanying drawings.

[0018] In embodiments of the present invention, words such as "exemplarily," "for example," etc., are used to indicate that something is an example, illustration, or description. Any embodiment or design described as "exemplary" in the present invention should not be construed as being more preferred or advantageous than other embodiments or designs. Specifically, the use of the word "exemplary" is intended to present the concept in a concrete manner. Furthermore, in embodiments of the present invention, the meaning expressed by "and / or" can be both, or either one.

[0019] In the embodiments of this invention, the terms "image" and "picture" may sometimes be used interchangeably. It should be noted that, without emphasizing the distinction between them, they convey the same meaning. Similarly, the terms "of," "corresponding (relevant)," and "corresponding" may sometimes be used interchangeably. It should be noted that, without emphasizing the distinction between them, they convey the same meaning.

[0020] In this embodiment of the invention, sometimes a subscript such as W1 may be written in a non-subscript form such as W1. When the difference is not emphasized, the meaning they express is the same.

[0021] To make the technical problems, technical solutions and advantages of the present invention clearer, a detailed description will be given below in conjunction with the accompanying drawings and specific embodiments.

[0022] Please see Figure 1 This invention provides a testing method for high and low voltage gas-filled switchgear using environmentally friendly insulating gas as a substitute for SF6, comprising the following steps: S1: Acquire the sampling data of gas pressure and conductivity sensors installed in the gas injection port and buffer cavity of the high and low pressure gas holder, extract the correspondence between pressure change and conductivity response in adjacent time periods, determine the consistency of the change trend and extract the stable section, and generate diffusion stable period labeling information. Gas pressure sensors are sensing devices used to collect information on pressure changes of gas inside high and low pressure gas holders under different filling or operating conditions. They adopt piezoresistive, piezoelectric, or capacitive structures and can output voltage, current, or digital signals for the control system to identify. The conductivity sensor is a detection element used to measure the conductivity of environmentally friendly alternative gases inside the gas filling cabinet. The working principle is to measure the volume conductivity of the gas medium under the target electrode structure, with the unit being Siemens per meter. It is suitable for gas medium analysis under power frequency excitation. The correspondence between pressure change and conductivity response refers to the dynamic trend between the rate of change of gas pressure and the corresponding change in conductivity within a unit time interval, which is used to analyze the gas diffusion or homogeneity state. S2: Based on the time range marked in the diffusion stabilization period labeling information, call up the spatial location information and conductivity data collected by the conductivity probe in the high-pressure gas-filling cabinet within the time period, identify the measurement point path with the same direction of conductivity change, construct the spatial closed loop region, and output the preliminary closed structure diagram of the path; A spatial closed loop region refers to a path structure formed by multiple measuring points inside a high-voltage gas-filled switchgear. In this structure, measuring points with continuous and consistent conductance changes form a closed loop, which can be used to identify potential weak insulation areas. S3: Obtain the measurement point information marked in the preliminary closed structure diagram of the path, extract the potential difference and spatial distribution data between paths, identify path segments with prominent potential change intensity, filter areas with spatial concentration characteristics, and generate a set of area boundary coordinates; Potential difference refers to the numerical difference between voltage signals collected from adjacent measuring points in space at the same moment. It is used to calculate the electric field intensity distribution at a location, and the unit is volts. Spatial distribution data refers to the spatial location information of all electrical conductivity measurement points or potential acquisition points inside the high and low voltage gas-filled switchgear, which is represented in a three-dimensional coordinate format and used to construct a spatial structure analysis model. Spatial concentration characteristics refer to the distribution pattern in which multiple path segments with high electric field strength or potential abrupt change properties are arranged in a clustered state in three-dimensional space, which is used to identify areas of concentrated breakdown risk. S4: Based on the spatial region formed by the regional boundary coordinate set, call the conductivity response data sequence within the region, determine the trend stability of conductivity value changing over time, and filter spatial segments that meet the continuous evolution characteristics to generate a breakdown trend evolution time tag set. Trend stability refers to the time series characteristic of conductivity changing over time, where the amplitude of change is within a defined range over a continuous period of time and the direction of change remains consistent. It is used to identify stable insulation states. Continuous evolution characteristics refer to the trend of conductivity maintaining a unidirectional change over multiple time segments, without any reversal or sudden jumps, which is used to identify the development process of breakdown trend. S5: Call the time period and spatial range marked in the breakdown trend evolution time tag, extract the conductivity and potential difference data of the corresponding measurement points, construct a data map of spatial field strength identification, mark the location of areas with prominent change trends, and generate a spatial positioning map of the breakdown critical area. The data map for spatial field strength identification refers to a three-dimensional spatial visualization structure constructed based on the conductivity and potential difference data of the measurement points, used to represent the distribution relationship of electric field strength in a local area; The region with a prominent trend of change refers to the spatial segment region in the coupled spectrum constructed by conductivity and potential difference that is identified as having a continuously increasing rate of change that exceeds a set judgment threshold. The region is composed of multiple conductivity measurement points on the spatial coordinates, reflecting the trend of concentrated change intensity of electric field distribution or abrupt change of electrical parameters, which is suitable for the identification of breakdown criticality. The spatial location map of the breakdown critical region refers to a data structure graph constructed based on the coupling trend of conductivity and potential difference, which identifies the spatial coordinate information of the region where the electric field strength changes abruptly, and is used to assist in the location of insulation performance tests.

[0023] The diffusion stability period annotation information includes time range, stable section index, and trend consistency index; the preliminary path closure structure diagram includes measurement point path set, spatial closed loop, and topological connection relationship; the regional boundary coordinate set includes boundary point coordinates, boundary outline sequence, and coordinate reference system; the penetration trend evolution time label set includes time label, spatial segment number, and evolution category identifier; and the penetration critical area spatial positioning map includes critical area spatial coordinates, field strength distribution layer, and risk level annotation.

[0024] Please see Figure 2 The specific steps of S1 are as follows: S101: Acquire the sampling data of the gas pressure sensor and conductivity sensor set in the gas injection port and buffer cavity of the high and low pressure gas holder, extract the pressure sampling value sequence and conductivity sampling value sequence for continuous time periods, calculate the pressure change rate and conductivity change rate between each segment, mark the change direction, and generate a change direction marking sequence. Pressure and conductivity sensors installed in the gas injection port and buffer chamber of the high and low pressure gas holder need to be set to a sampling frequency of once per second. The measurement range of the pressure sensor can be set to 0 to 10 MPa, and the measurement range of the conductivity sensor can be set to 0 to 20 mS / cm. The pressure and conductivity values ​​collected per second are acquired by the controller or data acquisition module and continuously recorded to form time series data. Assuming a 60-second analysis unit, each data segment will contain 60 sampling points. After extracting the first and last data of each segment, the rate of change of pressure and conductivity is calculated. If the pressure increases from 0.45 to 0.48 and the conductivity increases from 12.0 to 12.4 within a certain range, the pressure change per second is 0.0005 MPa and the conductivity change per second is 0.0067 mS / cm. The direction of change of pressure and conductivity in each range is determined. If the value increases, it is marked as positive; if it decreases, it is marked as negative; if it remains unchanged, it is marked as zero. After processing each range, a corresponding list of direction labels is generated. For example, if the pressure direction is positive, positive, zero, negative for several consecutive ranges, and the conductivity direction is positive, negative, zero, positive, a direction sequence is formed as the basis for subsequent analysis.

[0025] S102: Based on the sequence of change direction markers, determine whether the change direction of pressure and conductivity is consistent at each time point, filter the intervals with consistent change direction and meet the time continuity requirement, and obtain the interval segments with consistent change trend. Based on the aforementioned list of directional markers, the changing directions of pressure and conductivity are compared one by one at each time point. If they are the same, they are considered consistent; otherwise, they are considered inconsistent. A consistency sequence is constructed. For example, if the first three segments of five consecutive segments have the same changing direction, and the last two segments have different directions, it is recorded as consistent, inconsistent, inconsistent, consistent, consistent, generating a sequence such as 1, 0, 0, 1, 1. According to the set time continuity requirements, such as requiring at least three consecutive consistent time periods (at least 180 seconds), segments in the consistency sequence that meet this condition are found, and their corresponding original data segments are extracted as trend consistency intervals. Assuming that the pressure and conductivity directions in a certain segment are both continuously increasing (i.e., the directional markers are all positive), it can be considered a trend consistency. This process is applicable to gas leakage trend identification. For example, if a synchronous increase in pressure and conductivity is detected during the inflation process, it can be determined that the segment is in the stable growth period of the gas injection process.

[0026] S103: Based on the intervals with consistent trends, calculate the mean square error of the rate of change of pressure and the rate of change of conductivity within the interval, filter the intervals with fluctuations lower than the set benchmark, add label information, and generate diffusion stability period label information. From the obtained trend-consistent intervals, the fluctuation of the pressure and conductivity change rates within each segment is further assessed. The method involves calculating their root mean square deviation, taking the change rate sequence within each segment, calculating the average, then calculating the deviation between each change rate and the average, and finally taking the squared average. For example, if the pressure change rates in a segment are 0.0005, 0.0006, and 0.0004, with an average of 0.0005, the squared deviations are 0, 0.00000001, and 0.00000001, respectively, and the root mean square deviation is approximately 0.0000000067 MPa. 2 / s 2 If the preset benchmark value is 0.00000001, then the fluctuation of this segment is lower than the set benchmark and can be judged as stable. The setting of the benchmark value should be based on the statistical analysis of a large amount of actual collected data. For example, the fluctuation value is calculated from 100 sets of normal operation data, and the mean squared error at the 95% confidence level is taken as the judgment benchmark. For segments that meet the conditions, add label information, such as recording the segment number, start and end time, the mean value of the corresponding rate of change and its mean squared error value, to complete the identification and labeling of stable diffusion segments.

[0027] Please see Figure 3 The specific steps of S2 are as follows: S201: Based on the time range marked in the diffusion stabilization period labeling information, call up the spatial location information and conductivity data collected by the conductivity probe in the high-pressure gas-filling cabinet within the time period, extract the conductivity change trend identifier of each measuring point within the corresponding time period, integrate them into a sequence according to the measuring point number order, and generate the measuring point conductivity trend sequence. Based on the time range indicated in the diffusion stabilization period labeling information, for example, a time period from 12:15 to 12:18, totaling 180 seconds, it is necessary to retrieve the conductivity data and spatial coordinate information of the conductivity probes deployed inside the high-voltage gas-filled switchgear within this time range. The conductivity probes are generally arranged in several key locations within the switchgear according to rules, such as the air inlet, busbar compartment, and circuit breaker compartment. Each probe has a unique number and three-dimensional spatial coordinates; for example, the number P001 corresponds to positions X-axis 1.2, Y-axis 0.5, and Z-axis 2.0. The conductivity data sequence collected at each measuring point within this time period is extracted in chronological order, with the sampling frequency set to once per second. Each measuring point will then... During this period, 180 conductivity data points are generated. The initial and final conductivity values ​​for each measurement point within the corresponding time period are extracted. The direction of conductivity change is determined based on the increase or decrease between the initial and final values. If the final value is greater than the initial value, it is defined as an increase; if it is less than the initial value, it is a decrease; and if they are equal, it is unchanged. Alternatively, the dominant trend in the sequence can be used for judgment. For example, if the proportion of continuously increasing points exceeds 80%, it is marked as an upward trend, forming a conductivity trend identifier for the measurement points. These identifiers are then arranged and integrated according to the measurement point numbers to generate a conductivity trend sequence for the measurement points. For example, if the measurement points numbered P001 to P004 show an increase, increase, decrease, and increase respectively within a specified time period, then the sequence is increase, increase, decrease, and increase.

[0028] S202: Based on the conductivity trend sequence of measurement points, identify the combination of measurement points with the same direction of conductivity change in continuous measurement points, retain the measurement point path with the continuous and consistent direction of conductivity change, and record the spatial location information to obtain the consistent measurement point path location information; Based on the conductivity trend sequence of measurement points, a traversal analysis method is used to identify groups of measurement points with continuous and consistent conductivity change directions. Starting from the first measurement point number, the direction of change is compared with each of its adjacent measurement points. If two or more consecutive measurement points have the same direction, they are merged into the same group. If the direction changes, the current group is terminated, and a new group is started from that point. Independent trend segments are not discarded during this process. After identification, multiple groups of measurement points with consistent directions are obtained. However, further judgment is needed on whether the measurement points within the group are spatially connected. Spatial connectivity can be determined based on the relationship between adjacent measurement points. To determine whether the distance is less than a set threshold, referencing the high-voltage switchgear structure, the maximum effective connection distance between adjacent measuring points is set to 0.3m. In the combination, the distance between the three-dimensional coordinates of each pair of measuring points is calculated. For example, if the measuring points in a certain group are located at positions 1.2, 1.5, and 1.8 respectively, and the distance between their coordinates is within 0.3m, then the group is considered to be spatially connected and effective. Finally, the measuring point path group with a continuous and consistent direction of conductance change and effective spatial connectivity is selected. The number, position, and trend direction of all measuring points in the path group are recorded as consistent measuring point path position information for subsequent spatial structure construction.

[0029] S203: Call the consistent measurement point path location information, connect adjacent measurement point locations in sequence, identify path sequences where the spatial coordinates of the start and end points coincide or are close, construct the corresponding path loop structure, draw the structure wireframe graphic, and generate a preliminary closed structure diagram of the path. Based on the identified path location information of each set of consistent measuring points, all adjacent measuring points in the path are spatially connected in numerical order to form a three-dimensional path structure diagram. Further, the spatial coordinate difference between the start and end points of each path is retrieved. If the difference is very small, the path is considered to have a closed trend. For example, if the straight-line distance between the start and end points is less than 0.15m, it is considered a closed path. This spatial distance can be calculated by judging the coordinate differences in three directions. Precise overlap is not mandatory; instead, a proximity threshold is set to identify the closed trend. Once the path is confirmed to be closed, the coordinate points are connected in the order of the path nodes to form a three-dimensional graphic, which is then drawn in wireframe format to generate a preliminary closed structure diagram of the path. This diagram will indicate the path number, the coordinates of the start and end points of the closure, the number of measuring points included in the path, and the trend direction. The graphic can be completed using commonly used 3D drawing tools in engineering design and supports further export for structural identification or equipment layout analysis, ultimately forming a graphical representation of the spatial closed structure reflecting the conductivity trend of the measuring points.

[0030] Please see Figure 4 The specific steps of S3 are as follows: S301: Obtain the path number and spatial coordinates of the measuring points marked in the preliminary closed structure diagram of the path, extract the potential value and corresponding position of the measuring points within the path segment, calculate the potential gradient of the path segment based on the potential difference and positional relationship between the measuring points, and generate the potential gradient sequence of the path segment. After obtaining the path numbers and spatial coordinates of the measuring points marked in the preliminary closed structure diagram, it is necessary to sequentially read the measuring point number information in each path segment, and then obtain the spatial position and potential value data corresponding to the measuring point according to the number index. For example, for the path segment with measuring points numbered P001 to P005, their corresponding positions are arranged equidistantly in the X direction from 1.0 to 1.8, with measuring point positions of 1.0, 1.2, 1.4, 1.6, and 1.8 respectively (in meters), and potential values ​​of 4.5, 4.3, 4.0, 3.8, and 3.5 respectively (in volts). By calculating the potential difference and spatial distance between adjacent measuring points, the rate of potential change of the path segment can be determined. The potential difference passes through the potential of the next measuring point. The potential gradient is obtained by subtracting the potential of the previous measuring point. The spatial distance is determined by the difference in the coordinates of each measuring point. The two are divided to form the potential gradient value. This process is performed segment by segment. For example, if the potential difference between P001 and P002 is 0.2 and the distance is 0.2, then the potential gradient is 1.0. If the potential difference between P002 and P003 is 0.3 and the distance is 0.2, then the gradient is 1.5. And so on, to complete the potential gradient calculation between each measuring point in the entire path, forming a gradient sequence. Each gradient value needs to be labeled with the starting and ending measuring point numbers, positions, and the direction of potential change. Finally, a complete potential gradient sequence is generated under each path segment as the path electric field feature information, which is used for subsequent segment identification and extraction of abnormal change areas.

[0031] S302: Based on the potential gradient sequence of the path segment, filter the potential gradient values ​​of the path segment, retain the path segment whose potential gradient exceeds the set threshold, extract the measurement point number and position of the corresponding path segment, and obtain the coordinate set of the high gradient path segment. Based on the potential gradient sequence of the path segments, the gradient values ​​are iterated one by one and compared with the preset potential gradient threshold. When setting the threshold, the statistical law of potential change between measuring points under typical working conditions should be taken into account. For example, when the gradient value of most path segments is below 1.0, 1.2 can be used as the screening threshold to retain areas with significant abrupt changes. In the actual screening process, the gradient value of each segment is compared with the threshold. If the gradient value is equal to or greater than 1.2, the segment is retained; if it is lower than 1.2, it is discarded. This screening process is continuously executed within the path number. The screening results are then reorganized, and all isolated high gradient segments are deleted. Only the set of regional segments formed by continuous high gradient segments is retained. The criteria for determining continuous segments are that there are no low gradient segments between two or more high gradient segments under the same path number. After screening, the starting and ending measuring point numbers and their coordinate positions of each retained segment are extracted to form a new dataset, which is the high gradient path segment coordinate set. Each segment should include the starting and ending numbers, starting and ending coordinates, potential difference and distance difference, which are used for subsequent spatial clustering analysis and contour extraction operations.

[0032] S303: Call the coordinate set of high gradient path segments, analyze the positional distribution characteristics between measurement points, identify the combination of measurement points whose spatial distance satisfies the concentrated characteristics, extract boundary points to form a closed contour, and generate the coordinate set of the region boundary. Spatial distribution analysis is performed on the coordinates of all measurement points in the high-gradient path segment coordinate set. The presence of significant concentrated distribution is determined by the three-dimensional spatial relationship between the measurement points. First, the starting and ending positions of all path segments are extracted to form a point set. This point set is traversed, and the distance between each measurement point is judged one by one. If the continuous distance between multiple measurement points is less than the set concentration feature threshold, for example, 0.25 m, then the group of measurement points is identified as a spatially concentrated region. After forming the measurement point group, the boundary of the measurement point position in each group is extracted. The enclosing region is constructed by identifying the outermost distribution of points in each group. This boundary point set can be obtained by progressively filtering according to the coordinate distribution characteristics. After determining the boundary point set, all boundary points are connected in a certain order to ensure that a closed curve is formed, thus defining a closed spatial contour region. This contour line is composed of several boundary measurement points, all of which are marked with spatial coordinates and number information. Finally, all generated boundary contour point sets are output uniformly as the region boundary coordinate set for further structure recognition and graphic drawing operations.

[0033] Please see Figure 5 The specific steps of S4 are as follows: S401: Based on the spatial range defined by the regional boundary coordinate set, obtain the conductivity response data sequence of the location within the region, extract the conductivity value sequence of the location changing over time, and organize and sort to generate the regional conductivity time series sequence; Based on the spatial range defined by the region boundary coordinate set, it is necessary to first determine the coverage area of ​​this range in three-dimensional space. This involves traversing all measurement points in the conductivity data source and comparing the coordinate values ​​of each measurement point with the boundary coordinate range to determine if it falls within the target region. If the boundary range is 1 to 3 in the x-direction, 2 to 4 in the y-direction, and 0 to 1 in the z-direction, then all measurement points within this range are selected as the target analysis objects. Subsequently, the conductivity history records of each target measurement point are retrieved, and the conductivity values ​​recorded in chronological order are extracted. For example, the conductivity values ​​of measurement point P01 from t1 to t5 are 0.85, 0.90, 0.92, 0.94, and 0.95, respectively. S. Repeat this process until the conductivity value sequence of all measuring points within the same time period is obtained. After sorting, the conductivity values ​​of all measuring points are classified according to time order to form a conductivity spatial distribution data set indexed by time. Each time node corresponds to the conductivity state description within a set of measuring points. The final generated regional conductivity time series sequence constitutes a sequence that varies over time and contains multiple sets of conductivity values ​​of measuring points, which is used for subsequent trend identification and time series evolution analysis.

[0034] S402: Call the regional conductance time series, and based on the characteristics of the conductance value change over a continuous time period, determine whether the conductance trend is stable according to the benchmark value of conductance change stability, extract the segment numbers that meet the stability conditions, and obtain the set of stable change segment numbers; After retrieving the regional conductivity time series data, it is necessary to determine the conductivity change trend of each measuring point within a continuous time period. A sliding time window method is used to extract subsequences of fixed time lengths. For example, the window length can be set to 5 time nodes, sliding gradually from the first group to the last. Each time, the conductivity value sequence of the measuring point within that time period is selected, and then the fluctuation range and slope of the conductivity sequence are calculated. A stability benchmark value is set to filter segments with stable conductivity trends. The benchmark value can refer to the conductivity value change under undisturbed conditions. For example, if statistical results show that the conductivity value fluctuation in most statically stable segments is within 0.02 s, then 0.025 s is considered a stable value. S is set as the threshold. When judging any conductance sequence, if the difference between the maximum and minimum conductance values ​​of the segment does not exceed 0.025 and the overall trend of change is not significantly skewed, i.e. the slope is close to zero, then it can be judged as a stable conductance trend segment. The time segments that meet this condition are numbered and marked, such as F01, F02, etc. During the screening process, the start time, end time and corresponding measurement point set of each segment should be recorded simultaneously. By traversing all measurement points and time windows, a stable segment number set is obtained. This number set serves as the basis for identifying stable trend segments.

[0035] S403: Based on the time range corresponding to the stable change segment number set, extract the conductivity sequence of the location within the time period in the region, identify spatial segments with continuous evolution characteristics, and generate a breakdown trend evolution time label set; Based on the time range corresponding to the stable change segment number set, the conductivity data of all measuring points in the region within this time period are extracted to form a time-constrained conductivity subsequence set. The conductivity value change of each measuring point in this set in a continuous time period is analyzed to determine whether it exhibits continuous evolution characteristics in the spatial dimension. If the conductivity value of measuring point P21 from time t1 to t3 is 0.80, 0.83, and 0.88 s, it can be determined that it shows a continuous upward trend in this time period. The same analysis is performed on all measuring points in the region, and the proportion of measuring points with the same direction of change is counted. If more than 70% of the measuring points in a certain region show an increase or decrease in conductivity value in a continuous time period, and the change amplitude exceeds 0.02 s, then the region is considered to be in a continuous evolution state. The time periods with significant evolution characteristics are further recorded to form a breakdown trend evolution time tag set. Each tag contains a time range identifier and a corresponding spatial segment number. Finally, all time periods that meet the above evolution characteristics are sorted out to form a complete time tag set, which is used for the continuity judgment of the breakdown trend and the location of visible time periods.

[0036] Please see Figure 6The specific steps of S5 are as follows: S501: Call the time period and spatial range identified by the breakdown trend evolution time label, extract the conductivity and potential difference data of the corresponding measurement points, organize the joint parameter values ​​of the measurement point locations, and generate a joint dataset of regional conductivity and potential. After retrieving the time period and spatial segment numbers recorded in the breakdown trend evolution time tag set, the start and end times and corresponding spatial range indicated by each tag should be extracted first. All measurement point numbers within this range should be matched with their location coordinates to filter out all measurement points that meet the spatial segment definition. Then, within the specified time range, the conductivity and potential difference data of each measurement point should be extracted. The conductivity data is in seconds (S), and the potential difference is in seconds (V). Each measurement point forms a parameter set consisting of conductivity and potential difference at each time point. For example, if the conductivity of a measurement point is recorded as 0.88, 0.91, and 0.94 S within a certain time period, the corresponding potential differences are 1.4, 1.6, and 1.9 S. V. For each set of data, the measurement point number, spatial coordinates, time point, conductivity, and potential difference are combined into a joint parameter value sequence. After processing each measurement point in turn, a data set with dual indexes of time series and spatial measurement point coordinates is constructed. In this data set, each data item represents the conductivity potential state of the measurement point at a specific spatiotemporal node. If multiple spatial segments are contained in the same time period during the processing, they should be processed separately and the results should be merged. Finally, a joint dataset of conductivity potentials for the entire breakdown trend-related region is formed, providing a complete parameter basis for subsequent field strength calculation.

[0037] S502: Based on the parameter values ​​of the centralized measurement points in the regional electric potential joint data set, calculate the electric field intensity at the corresponding spatial location, establish the correspondence between the measurement point location and the electric field intensity, and obtain the spatial field intensity distribution map; Based on the constructed regional electrical conductivity potential joint dataset, the potential difference and reference distance values ​​of each measuring point at each time point are extracted, and the corresponding electric field strength value of the measuring point is calculated accordingly. The reference distance should be determined based on the adjacent spacing of the measuring points in the actual deployment. For example, if the distance between measuring points is set to 0.2 m, then if the potential difference is 1.6 V, the corresponding electric field strength is 8 V / m. All measuring points need to be processed individually at their respective time points to calculate the complete electric field strength value. Then, the measuring point number, three-dimensional coordinates, and corresponding electric field strength value are combined to construct the mapping relationship between the measuring point position and the electric field strength. To avoid errors caused by differences in spacing between different regions, the reference distance for each region should be dynamically set, for example, set to 0.15 m in dense regions and 0.5 m in sparse regions. m, the electric field strength values ​​calculated based on the potential difference and spacing in different regions are spatially reconstructed after being sorted out. The electric field strength values ​​of all measuring points at each time point are mapped to the three-dimensional coordinate system, marking the electric field distribution state and constructing a complete spatial field strength distribution map. Each spatial point represents the local electric field strength at a certain moment, which is used for subsequent screening and calibration of critical regions.

[0038] S503: Based on the electric field intensity variation value in the spatial field intensity distribution map, according to the change trend threshold, filter the location points that exceed the threshold, mark the spatial location, and generate a spatial positioning map of the breakdown critical region. Based on the numerical records of the spatial electric field distribution spectrum, the change in electric field intensity at each measuring point between adjacent time points should be calculated along the time axis. For example, if the electric field intensity at a measuring point is 9.5 V / m and 13.0 V / m at two consecutive time points, the change is 3.5 V / m. This process is repeated for all measuring points within the region to form a complete set of spatial electric field change data. Each change value is then filtered according to a pre-set threshold for the change trend. This threshold needs to be statistically set based on multiple pre-breakdown sample data. For example, if sampling the evolution data of multiple historical breakdown regions reveals that the average fluctuation of the electric field intensity under critical change conditions is 3.2 V / m, then the threshold can be set to 3.0 V / m. V / m is used to filter out measurement points with a change value exceeding 3.0 V / m. These points are considered critical state points with prominent electric field changes, and their three-dimensional coordinate information, change value, and time label are recorded. After marking all spatial points that meet the conditions in sequence, a spatial layer is constructed in three-dimensional space according to the coordinate points, and the critical state is marked point by point. Finally, a spatial location map of the breakdown critical region is formed, which contains information on spatial location and corresponding time, reflecting the distribution of all regions in space where the electric field change exceeds the threshold.

[0039] Please see Figure 7 A test system for high and low voltage gas-filled switchgear using environmentally friendly insulating gases as a substitute for SF6, including: The diffusion monitoring module collects data from gas pressure sensors and conductivity sensors installed in the gas injection port and buffer chamber of the high and low pressure gas holder. It extracts pressure change sequences and conductivity response sequences in adjacent time periods, determines whether the change directions of the two sets of data are consistent, identifies continuous data intervals with consistent directions, detects the stability of conductivity changes within the identified intervals, obtains time periods that meet stability requirements, and generates diffusion stability period labeling information. The path construction module, based on the time range indicated in the diffusion stabilization period annotation information, calls the spatial location information and conductivity data of the conductivity probe inside the high-voltage gas-filled cabinet within the time period, identifies the measurement point path with the same direction of conductivity change, extracts the path set that forms a closed structure based on the spatial relationship of the path start and end points, and generates a preliminary closed structure diagram of the path. The region extraction module obtains the path information of the identified measuring points in the preliminary closed structure diagram of the path, extracts the potential difference and spatial location data between path segments, calculates the potential change intensity between path segments, filters regions with spatial concentration characteristics, extracts the coordinate information of spatial boundaries, and generates a set of region boundary coordinates. The trend recognition module calls the conductivity response data of the corresponding measurement points in the region based on the coordinate range marked by the regional boundary coordinate set, judges whether the change trend of conductivity value in time series is stable, filters spatial segments with continuous evolution characteristics, and generates a breakdown trend evolution time label set. The critical location module calls the time interval and spatial range identified in the breakdown trend evolution time tag set, extracts the conductivity value and potential difference data of the associated measurement points, constructs a spatial field strength data map, locates the area with a prominent field strength change trend, and generates a spatial location map of the breakdown critical area.

[0040] The above description is merely a specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed in the present invention should be included within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope of the claims.

Claims

1. A test method for high and low voltage gas-filled switchgear using environmentally friendly insulating gas as a substitute for SF6, characterized in that, Includes the following steps: S1: Acquire pressure and conductivity sensor data from the gas injection port and buffer cavity of the high and low pressure gas holder, extract the correspondence between pressure changes and conductivity responses in adjacent time periods, determine trend consistency, and generate diffusion stability period labeling information; S2: Based on the time range of the diffusion stabilization period labeling information, call the conductivity measurement point location and conductivity data within the period, identify the path with the same direction of conductivity change, and generate a preliminary closed structure diagram of the path; S3: Obtain the measurement point information in the preliminary closed structure diagram of the path, extract the potential difference and spatial distribution between paths, identify path segments with strong potential changes, filter spatially concentrated feature areas, and generate a set of region boundary coordinates; S4: Based on the spatial region formed by the boundary coordinate set of the region, call the conductivity response data sequence, determine the stability of the conductivity value change trend, filter the spatial segments of continuous evolution characteristics, and generate a breakdown trend evolution time label set; S5: Call the spatiotemporal range identified by the breakdown trend evolution time tag set, extract the conductivity and potential difference of the associated measurement points, construct a spatial field strength identification map, mark the prominent areas of trend change, and generate a spatial positioning map of the breakdown critical area.

2. The testing method for high and low voltage gas-filled switchgear using environmentally friendly insulating gas as a substitute for SF6 according to claim 1, characterized in that, The diffusion stabilization period annotation information includes time range, stable segment index, and trend consistency index; the preliminary path closure structure diagram includes measurement point path set, spatial closed loop, and topological connection relationship; the regional boundary coordinate set includes boundary point coordinates, boundary contour line sequence, and coordinate reference system; the breakdown trend evolution time label set includes time label, spatial segment number, and evolution category identifier; and the breakthrough critical region spatial positioning map includes critical region spatial coordinates, field strength distribution layer, and risk level annotation.

3. The testing method for high and low voltage gas-filled switchgear using environmentally friendly insulating gas as a substitute for SF6 according to claim 1, characterized in that, The specific steps of S1 are as follows: S101: Acquire the sampling data of the gas pressure sensor and conductivity sensor set in the gas injection port and buffer cavity of the high and low pressure gas holder, extract the pressure sampling value sequence and conductivity sampling value sequence for continuous time periods, calculate the pressure change rate and conductivity change rate between each segment, mark the change direction, and generate a change direction marking sequence. S102: Based on the change direction marking sequence, determine whether the change direction of pressure and conductivity is consistent at each time point, filter the intervals with consistent change direction and meet the time continuity requirement, and obtain the interval segments with consistent change trend. S103: Based on the intervals with consistent trends, calculate the mean square difference between the rate of change of pressure and the rate of change of conductivity within the intervals, filter the intervals with fluctuations lower than the set benchmark, add label information, and generate diffusion stability period label information.

4. The testing method for high and low voltage gas-filled switchgear using environmentally friendly insulating gas as a substitute for SF6 according to claim 3, characterized in that, The specific steps of S2 are as follows: S201: Based on the time range marked in the diffusion stabilization period labeling information, call up the spatial location information and conductivity data collected by the conductivity probe in the high-pressure gas-filling cabinet within the time period, extract the conductivity change trend identifier of each measuring point within the corresponding time period, integrate them into a sequence according to the measuring point number order, and generate the measuring point conductivity trend sequence. S202: Based on the conductivity trend sequence of the measurement points, identify the combination of measurement points with the same direction of conductivity change in continuous measurement points, retain the measurement point path with the continuous and consistent direction of conductivity change, and record the spatial location information to obtain the consistent measurement point path location information; S203: Call the consistent measurement point path location information, connect adjacent measurement point locations in sequence, identify path sequences where the starting point and ending point spatial coordinates coincide or are close, construct the corresponding path loop structure, draw the structure wireframe graphic, and generate a preliminary closed structure diagram of the path.

5. The testing method for high and low voltage gas-filled switchgear using environmentally friendly insulating gas as a substitute for SF6 according to claim 4, characterized in that, The specific steps for S3 are as follows: S301: Obtain the path number and spatial coordinates of the measuring points marked in the preliminary closed structure diagram of the path, extract the potential value and corresponding position of the measuring points in the path segment, calculate the potential gradient of the path segment based on the potential difference and positional relationship between the measuring points, and generate the potential gradient sequence of the path segment. S302: Based on the potential gradient sequence of the path segment, the potential gradient values ​​of the path segment are filtered, and the path segments with potential gradients exceeding a set threshold are retained. The measurement point number and position of the corresponding path segment are extracted to obtain the coordinate set of high gradient path segments. S303: Call the coordinate set of the high gradient path segment, analyze the positional distribution characteristics between the measurement points, identify the combination of measurement points whose spatial distance satisfies the concentrated characteristics, extract the boundary points to form a closed contour, and generate the regional boundary coordinate set.

6. The testing method for high and low voltage gas-filled switchgear using environmentally friendly insulating gas as a substitute for SF6 according to claim 5, characterized in that, The specific steps of S4 are as follows: S401: Based on the spatial range defined by the region boundary coordinate set, obtain the conductivity response data sequence of the location within the region, extract the conductivity value sequence of the location changing with time, and organize and sort to generate a regional conductivity time series sequence; S402: Call the regional conductivity time series, and based on the characteristics of conductivity value change in a continuous time period, determine whether the conductivity trend is stable according to the conductivity change stability benchmark value, extract the segment numbers that meet the stability conditions, and obtain a set of stable change segment numbers; S403: Based on the time range corresponding to the stable change segment number set, extract the conductivity sequence of the location within the time period in the region, identify spatial segments with continuous evolution characteristics, and generate a breakdown trend evolution time label set.

7. The testing method for high and low voltage gas-filled switchgear using environmentally friendly insulating gas as a substitute for SF6 according to claim 6, characterized in that, The specific steps of S5 are as follows: S501: Call the time period and spatial range identified by the breakdown trend evolution time tag set, extract the conductivity and potential difference data of the corresponding measurement points, organize the joint parameter values ​​of the measurement point locations, and generate a joint dataset of regional conductivity and potential. S502: Based on the parameter values ​​of the measurement points in the joint dataset of regional electrical conductivity potentials, calculate the electric field strength at the corresponding spatial location, establish the correspondence between the measurement point location and the electric field strength, and obtain the spatial field strength identification map. S503: Based on the electric field intensity change value in the spatial field strength identification map, according to the change trend threshold, filter the location points that exceed the threshold, mark the spatial location, and generate a spatial positioning map of the breakdown critical region.

8. The testing method for high and low voltage gas-filled switchgear using environmentally friendly insulating gas as a substitute for SF6 according to claim 1, characterized in that, The conductivity sensor is a detection element used to measure the conductivity of environmentally friendly alternative gases inside the gas filling cabinet. The relationship between pressure change and conductivity response refers to the dynamic trend between the rate of change of gas pressure and the corresponding magnitude of change of conductivity within a unit time interval.

9. The testing method for high and low voltage gas-filled switchgear using environmentally friendly insulating gas as a substitute for SF6 according to claim 1, characterized in that, The potential difference refers to the numerical difference between voltage signals collected from adjacent measuring points in space at the same moment; The spatial distribution refers to the spatial location information of all electrical conductivity measurement points or potential acquisition points inside the high and low voltage gas-filled switchgear, which is represented in a three-dimensional coordinate format. The spatial concentration feature refers to the distribution pattern in which multiple path segments with high electric field strength or potential abrupt change properties are arranged in a clustered state in three-dimensional space. The trend stability refers to the time series characteristic that the change in conductivity over time is within a defined range of change over a continuous time period and maintains a consistent direction of change. The continuous evolution characteristic refers to the conductivity maintaining a unidirectional change trend across multiple time segments, without any reversal or sudden jumps in direction. The spatial field strength identification spectrum refers to a three-dimensional spatial visualization structure constructed based on the conductivity and potential difference data of the measurement points; The region of significant change refers to a spatial segment in the coupled spectrum of conductivity and potential difference that is identified as having a continuously increasing rate of change that exceeds a set judgment threshold. The region is composed of multiple conductivity measurement points in spatial coordinates, reflecting the trend of concentrated changes in electric field distribution intensity or abrupt changes in electrical parameters. The aforementioned spatial location map of the breakdown critical region refers to a data structure graph constructed based on the coupling trend of conductivity and potential difference, which identifies the spatial coordinate information of the region where the electric field intensity changes abruptly.

10. A testing system for high and low voltage gas-filled switchgear using environmentally friendly insulating gas as a substitute for SF6, characterized in that: The system is used to implement the testing method for high and low voltage gas-filled switchgear using environmentally friendly insulating gas as a substitute for SF6 according to any one of claims 1-9. The system includes: The diffusion monitoring module collects data from gas pressure sensors and conductivity sensors installed in the gas injection port and buffer chamber of the high and low pressure gas holder. It extracts pressure change sequences and conductivity response sequences in adjacent time periods, determines whether the change directions of the two sets of data are consistent, identifies continuous data intervals with consistent directions, detects the stability of conductivity changes within the identified intervals, obtains time periods that meet stability requirements, and generates diffusion stability period labeling information. The path construction module, based on the time range indicated in the diffusion stabilization period annotation information, calls the spatial location information and conductivity data of the conductivity probe inside the high-voltage gas-filled cabinet within the time period, identifies the measurement point path with the same direction of conductivity change, extracts the path set that forms a closed structure based on the spatial relationship between the start and end points of the path, and generates a preliminary closed structure diagram of the path. The region extraction module obtains the identified measurement point path information in the preliminary closed structure diagram of the path, extracts the potential difference and spatial location data between path segments, calculates the potential change intensity between path segments, filters regions with spatial concentration characteristics, extracts the coordinate information of spatial boundaries, and generates a region boundary coordinate set. The trend recognition module calls the conductivity response data of the corresponding measurement points in the region based on the coordinate range marked by the region boundary coordinate set, judges whether the change trend of conductivity value in time series is stable, filters spatial segments with continuous evolution characteristics, and generates a breakdown trend evolution time label set. The critical location module calls the time interval and spatial range identified in the breakdown trend evolution time tag set, extracts the conductivity value and potential difference data of the associated measurement points, constructs a spatial field strength identification map, locates the area with a prominent field strength change trend, and generates a spatial location map of the breakdown critical area.

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