GIS equipment insulation defect partial discharge signal-based detection positioning method and system

Abstract

The invention provides a GIS equipment insulation defect partial discharge signal-based detection positioning method and system, and relates to the technical field of data processing, and the method comprises the steps: activating an eight-dimensional signal capture array to execute the subnanosecond partial discharge signal synchronous collection of GIS equipment according to the partial discharge signal intensity span of the GIS equipment, and obtaining a real-time eight-dimensional signal array; performing signal confidence evaluation on the single-dimensional signal capture sub-array, and screening and outputting eight-dimensional credible signal features; and positioning the partial discharge space of the latent defect based on the timestamp information of the eight-dimensional credible signal characteristics. The technical problems that in the prior art, GIS equipment insulation defect partial discharge signal collection is incomplete in coverage and insufficient in instantaneity, so that insulation defect partial discharge signal source positioning precision is insufficient, and a reliable decision basis is difficult to provide for operation and maintenance are solved. The technical effects that the insulation defect partial discharge signals of the GIS equipment are comprehensively covered and collected, the signal source is accurately positioned, and a reliable decision basis is provided for real-time operation and maintenance of the GIS equipment are achieved.

Description

Technical Field

[0001] This invention relates to the field of data processing technology, and specifically to a method and system for detecting and locating partial discharge signals of insulation defects in GIS equipment. Background Technology

[0002] Existing technologies for collecting partial discharge signals from insulation defects in GIS equipment often employ a single mode or a limited arrangement of a few sensors. This approach cannot fully cover partial discharge signals of different locations, types, and intensities within the equipment, leading to the missed detection of weak signals from some latent defects or signals from specific areas.

[0003] Meanwhile, the low time synchronization accuracy of signal acquisition makes it difficult to accurately obtain the time difference of partial discharge signals arriving at different sensors, which in turn affects the accuracy of positioning methods such as triangulation. This results in insufficient positioning accuracy of the partial discharge signal source, only providing a general area of ​​the defect.

[0004] These problems prevent maintenance personnel from obtaining comprehensive partial discharge signal characteristics and accurate defect location information, making it difficult to determine the type, severity, and development trend of defects, and thus failing to provide reliable decision-making basis for equipment maintenance.

[0005] In summary, existing technologies suffer from incomplete coverage and insufficient real-time performance in collecting partial discharge signals from insulation defects in GIS equipment. This results in insufficient accuracy in locating partial discharge signal sources and makes it difficult to provide reliable decision-making support for operation and maintenance. Summary of the Invention

[0006] This invention provides a method and system for detecting and locating partial discharge signals of insulation defects in GIS equipment. It addresses the technical problem that existing technologies do not provide complete coverage and real-time data acquisition for partial discharge signals of insulation defects in GIS equipment, resulting in insufficient accuracy in locating the source of the partial discharge signal and making it difficult to provide reliable decision-making basis for operation and maintenance.

[0007] In view of the above problems, the present invention provides a method and system for detecting and locating partial discharge signals of insulation defects in GIS equipment.

[0008] The first aspect of this invention provides a method for detecting and locating partial discharge signals based on insulation defects in GIS equipment. The method includes: constructing an eight-dimensional signal acquisition array by performing partial discharge signal capture analysis on the GIS equipment, wherein each signal acquisition subarray includes a multi-scale gain PGA, a UHF ultra-high frequency sensor, and an ultrasonic sensor; when the GIS equipment exhibits a suspected partial discharge signal due to an insulation defect, the eight-dimensional signal acquisition array is temporarily deployed non-damagingly by using a magnetic base to migrate and attach the array to the metal casing of the GIS equipment; based on the intensity range of the partial discharge signal of the GIS equipment, the eight-dimensional signal acquisition array is initialized with multi-gain classification, and then activated to perform sub-nanosecond-level synchronous acquisition of partial discharge signals from the GIS equipment, resulting in a real-time eight-dimensional signal array; after performing signal redundancy verification on the real-time eight-dimensional signal array, the signal confidence of the single-dimensional signal acquisition subarray is evaluated, and eight-dimensional reliable signal features are selected and output; based on the timestamp information of the eight-dimensional reliable signal features, multiple rounds of triangulation measurement verification are performed to locate the latent defect partial discharge space.

[0009] A second aspect of the present invention provides a detection and location system based on partial discharge signals of insulation defects in GIS equipment. The system includes: a capture array construction module for constructing an eight-dimensional signal capture array by performing partial discharge signal capture analysis on the GIS equipment, wherein each signal capture subarray includes a multi-scale gain PGA, a UHF ultra-high frequency sensor, and an ultrasonic sensor; a temporary deployment execution module for migrating and adsorbing the eight-dimensional signal capture array onto the metal casing of the GIS equipment using a magnetic base when a suspected partial discharge signal of insulation defect is detected, performing a non-destructive temporary deployment; and a signal acquisition execution module. The module is used to initialize the eight-dimensional signal acquisition array with multi-gain classification based on the partial discharge signal strength span of the GIS device, and then activate the eight-dimensional signal acquisition array to perform sub-nanosecond level partial discharge signal synchronous acquisition of the GIS device to obtain a real-time eight-dimensional signal array; the signal quality assessment module is used to perform signal redundancy verification on the real-time eight-dimensional signal array, and then perform signal confidence assessment on the single-dimensional signal acquisition subarray to filter and output eight-dimensional reliable signal features; the defect space location module is used to perform multi-round triangulation verification based on the timestamp information of the eight-dimensional reliable signal features to locate the latent defect partial discharge space.

[0010] One or more technical solutions provided in this invention have at least the following technical effects or advantages: The method provided in this invention constructs an eight-dimensional signal acquisition array by capturing and analyzing partial discharge signals from GIS equipment. Each signal acquisition subarray includes a multi-scale gain PGA, a UHF ultra-high frequency sensor, and an ultrasonic sensor. When the GIS equipment exhibits a suspected partial discharge signal due to insulation defects, the eight-dimensional signal acquisition array is temporarily deployed non-damagingly by migrating and adhering it to the metal casing of the GIS equipment using a magnetic base. Based on the intensity range of the partial discharge signal from the GIS equipment, the eight-dimensional signal acquisition array is initialized with multi-gain levels and then activated to synchronously acquire the sub-nanosecond level partial discharge signal from the GIS equipment, resulting in a real-time eight-dimensional signal array. After performing signal redundancy verification on the real-time eight-dimensional signal array, the signal confidence of the single-dimensional signal acquisition subarrays is evaluated, and eight-dimensional reliable signal features are selected and output. Based on the timestamp information of the eight-dimensional reliable signal features, multiple rounds of triangulation measurement verification are performed to locate the latent defect partial discharge space. This achieves the technical effect of comprehensive coverage acquisition and precise signal source location of partial discharge signals from insulation defects in GIS equipment, providing a reliable decision-making basis for the real-time operation and maintenance of GIS equipment. Attached Figure Description

[0011] Figure 1 This is a schematic flowchart of the detection and location method for partial discharge signals of insulation defects in GIS equipment provided by the present invention.

[0012] Figure 2 This is a schematic diagram of the structure of the detection and location system based on partial discharge signal of insulation defects in GIS equipment provided by the present invention.

[0013] Figure labeling: 11 Capture array construction module, 12 Temporary deployment execution module, 13 Signal acquisition execution module, 14 Signal quality assessment module, 15 Defect spatial location module. Detailed Implementation

[0014] This invention provides a method and system for detecting and locating partial discharge signals from insulation defects in GIS equipment. It addresses the technical problem of incomplete coverage and insufficient real-time data acquisition of partial discharge signals from insulation defects in GIS equipment in existing technologies, resulting in insufficient accuracy in locating the signal source and hindering reliable decision-making for maintenance. The invention achieves comprehensive coverage acquisition and precise signal source location of partial discharge signals from insulation defects in GIS equipment, providing a reliable basis for real-time maintenance decisions.

[0015] The technical solutions of the present invention will now be clearly and completely described with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of the present invention, and not all of them. It should be understood that the present invention is not limited to the exemplary embodiments described herein. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without creative effort are within the scope of protection of the present invention. It should also be noted that, for ease of description, only the parts related to the present invention are shown in the accompanying drawings, not all of them.

[0016] Example 1, as Figure 1 As shown, this invention provides a method for detecting and locating partial discharge signals of insulation defects in GIS equipment, the method comprising: A100: By performing partial discharge signal capture analysis on GIS equipment, an eight-dimensional signal capture array is constructed. Each signal capture subarray includes a multi-scale gain PGA, a UHF ultra-high frequency sensor, and an ultrasonic sensor.

[0017] Furthermore, by performing partial discharge signal capture analysis on the GIS equipment and constructing an eight-dimensional signal capture array, step A100 of the method further includes: A110: Locate the internal high-incidence area of ​​local emission using the equipment drawings of the GIS equipment.

[0018] A120: Starting from the location of the high-incidence area of ​​internal partial discharge, identify the effective signal capture area of ​​the metal casing of the GIS equipment.

[0019] A130: Using the effective signal capture area as a spatial constraint, perform non-uniform positioning of the eight-dimensional monitoring space according to the shape of the metal casing of the GIS device.

[0020] A140: By simulating a partial discharge source, a signal acquisition coverage test is performed in the eight-dimensional monitoring space to locate the eight-dimensional signal acquisition array.

[0021] Furthermore, by locating the internal high-incidence areas of localized emissions using the equipment drawings of the GIS device, step A110 of the method also includes: A111: Local access to the equipment maintenance records of the same model of GIS equipment.

[0022] A112: Based on the equipment drawings and equipment operation and maintenance records, locate the high-incidence area of ​​partial discharge and output the location of the internal high-incidence area of ​​partial discharge.

[0023] Furthermore, taking the location of the high-incidence area of ​​internal partial discharge as the starting point, the method step A120 further includes identifying the effective signal capture area of ​​the metal casing of the GIS equipment. A121: Interactively obtain the minimum detectable signal threshold of the UHF ultra-high frequency sensor.

[0024] A122: Local call Gas attenuation coefficient and attenuation law of partial discharge UHF signal spherical propagation.

[0025] A123: Taking the location of the aforementioned high-incidence area of ​​internal partial discharge as the starting point, based on Using the gas attenuation coefficient, the spherical propagation attenuation law of partial discharge UHF signals, and the minimum detectable signal threshold, the maximum permissible propagation distance of UHF signals is calculated, and the effective area of ​​UHF signals is marked.

[0026] A124: Interactively obtain the minimum detectable vibration threshold of the ultrasonic sensor.

[0027] A125: Locally retrieves the attenuation coefficient of the casing material and the mechanical transmission characteristics of the partial discharge ultrasonic signal.

[0028] A126: Starting from the location of the high-incidence area of ​​internal partial discharge, the maximum allowable transmission distance of the ultrasonic signal is calculated based on the attenuation coefficient of the shell material, the mechanical transmission characteristics of the partial discharge ultrasonic signal, and the minimum detectable vibration threshold, and the effective area of ​​the ultrasonic signal is marked.

[0029] A127: The intersection area of ​​the effective UHF signal area and the effective ultrasonic signal area is taken as the effective signal capture area.

[0030] Specifically, this embodiment performs partial discharge signal capture and analysis on GIS equipment by arranging eight signal capture subarrays around its metal casing. Each subarray integrates a multi-scale gain PGA, a UHF ultra-high frequency sensor, and an ultrasonic sensor. The multi-scale gain PGA can dynamically adjust its gain according to the partial discharge signal strength to avoid loss of weak signals or saturation of strong signals. The UHF ultra-high frequency sensor is used to capture the 300MHz to 3GHz ultra-high frequency electromagnetic signals generated by partial discharge events, and the ultrasonic sensor is used to capture the 20kHz to 200kHz mechanical vibration signals of the metal casing caused by partial discharge. The combination of the two achieves multi-modal signal acquisition, comprehensively covering partial discharge signals of different types and intensities.

[0031] The specific construction process of the eight-dimensional signal acquisition array is as follows: First, the equipment operation and maintenance records of the same model of GIS equipment are retrieved, such as historical partial discharge detection reports and fault repair records. These records can reflect the common high-incidence locations of partial discharge in the same model of equipment. Then, combined with the physical structure of the GIS equipment's equipment drawings, the high-incidence locations in the equipment operation and maintenance records are matched with the components in the drawings. Finally, the accurate location of the high-incidence area of ​​partial discharge inside the GIS equipment is determined, such as the connection between the busbar and the insulator, thus obtaining the location of the high-incidence area of ​​partial discharge inside the equipment.

[0032] Starting from the location of the high-incidence area of ​​internal partial discharge, the effective signal capture area of ​​the metal casing of the GIS equipment is identified. This is because when the partial discharge signal travels from the high-incidence area to the casing, it passes through… The attenuation of gas (UHF signal) or metal parts (ultrasonic signal) means that only specific areas on the casing (i.e., the effective signal capture area) can receive a signal of sufficient strength. Identifying these areas is to deploy the array in a location where the signal can be effectively received, thus avoiding missed detections.

[0033] By reading the built-in parameters of the UHF sensor, its minimum detectable signal threshold can be obtained. This threshold is the weakest signal strength that the UHF sensor can recognize. It is a key indicator for determining whether a partial discharge signal can be effectively detected when it travels from the internal high-frequency area to the metal casing. If the signal strength is lower than this value when it reaches a certain area of ​​the casing, the sensor cannot recognize it, and that area cannot be used as a signal capture point.

[0034] Retrieve from local database or pre-stored knowledge base Gas attenuation coefficient and attenuation law of partial discharge UHF signal spherical propagation. Gas serves as the insulating medium for GIS equipment and attenuates UHF signals to a certain extent. Its attenuation coefficient reflects the degree of signal strength reduction per unit distance. Partial discharge UHF signals propagate from the high-incidence area outwards in the form of spherical waves. The spherical propagation attenuation law refers to the signal strength decreasing according to the spherical diffusion law as the propagation distance increases. These two parameters together determine the UHF signal's attenuation. Propagation characteristics in gases.

[0035] Starting from the aforementioned high-incidence area of ​​internal partial discharge, combined with The gas attenuation coefficient, the spherical propagation attenuation law of partial discharge UHF signals, and the minimum detectable signal threshold of the sensor are used to calculate the maximum distance at which a UHF signal can travel from a high-intensity area to a metal casing while still reaching the sensor's detection threshold. For example, if the UHF signal strength in the high-intensity area is a certain value, after passing through... After the gas attenuates, the intensity of the signal reaches a certain point on the casing and is exactly equal to the sensor's minimum detectable threshold. The distance from this point to the high-incidence area is the maximum permissible propagation distance. All areas of the casing less than or equal to this distance can receive a UHF signal with sufficient intensity and are marked as the effective area for the UHF signal.

[0036] By reading the built-in parameters of the ultrasonic sensor, its minimum detectable vibration threshold is obtained. This threshold is the weakest mechanical vibration intensity that the ultrasonic sensor can identify. Partial discharge events will cause the GIS metal shell to vibrate. The vibration signal is transmitted to the sensor through the shell. If the vibration intensity transmitted to a certain point on the shell is lower than this threshold, the sensor cannot identify it, and that area cannot be used as a signal capture point.

[0037] Starting from the high-incidence area of ​​internal partial discharge, and combining the attenuation coefficient of the casing material, the mechanical transmission characteristics of the partial discharge ultrasonic signal, and the minimum detectable vibration threshold of the sensor, the maximum distance at which the ultrasonic signal can still reach the sensor's detection threshold after being transmitted from the high-incidence area through the metal casing to the casing surface is calculated. For example, if the ultrasonic vibration intensity in the high-incidence area is a certain value, after attenuation by the casing material, the intensity at a certain point on the casing is exactly equal to the sensor's minimum detectable threshold. The distance from this point to the high-incidence area is the maximum allowable transmission distance. All casing areas with a distance less than or equal to this distance can receive ultrasonic signals of sufficient intensity and are marked as the effective ultrasonic signal area.

[0038] Because GIS partial discharge detection requires the simultaneous acquisition of UHF electromagnetic signals and ultrasonic vibration signals, only the shell area that belongs to both effective areas can ensure that both signals can be effectively detected by the sensor, avoiding missed detection due to excessive attenuation of a single signal, and ensuring the effectiveness of subsequent array deployment. Therefore, in this embodiment, the intersection area of ​​the effective UHF signal area and the effective ultrasonic signal area is taken as the effective signal capture area.

[0039] Using the effective signal capture area as a spatial constraint, non-uniform positioning of the eight-dimensional monitoring space is performed based on the shape of the metal casing of the GIS equipment. Non-uniform positioning means that instead of arranging the eight sub-arrays in a uniform distribution, the position of each sub-array is adjusted according to the shape of the casing to ensure that all sub-arrays are within the effective signal capture area and cover the entire monitoring space. For example, the eight sub-arrays of a cylindrical casing are arranged in eight directions such as east, south, west, and north, but the distance between the sub-arrays in each direction and the high-incidence area is different.

[0040] The simulated partial discharge source is placed inside or on the casing of the GIS equipment, and tests are conducted at different locations in the eight-dimensional monitoring space to check whether all eight subarrays can capture the signal of the simulated partial discharge source and whether the strength meets the standard. If the signal at a certain location can only be captured by a few subarrays, it indicates that there is a blind zone in the array, and the positions of the subarrays need to be adjusted until the simulated partial discharge source signal in all monitoring spaces can be captured by at least three subarrays. Finally, the accurate position of the eight-dimensional signal capture array is determined, and the eight-dimensional signal capture array is obtained.

[0041] This embodiment achieves comprehensive coverage of partial discharge signals from GIS equipment by constructing an eight-dimensional multi-gain multi-modal signal acquisition array, thereby improving detection accuracy and reliability and providing reliable analytical data for subsequent detection and location of partial discharge signals of insulation defects.

[0042] A200: When the GIS equipment shows a suspected partial discharge signal due to insulation defects, a magnetic base is used to migrate and attach the eight-dimensional signal capture array to the metal casing of the GIS equipment for non-destructive temporary deployment.

[0043] A300: Based on the partial discharge signal strength span of the GIS device, after initializing the eight-dimensional signal acquisition array with multi-gain banding, activate the eight-dimensional signal acquisition array to perform sub-nanosecond level partial discharge signal synchronous acquisition of the GIS device, and obtain a real-time eight-dimensional signal array.

[0044] Furthermore, based on the partial discharge signal strength span of the GIS device, after initializing the eight-dimensional signal acquisition array with multi-gain banding, the eight-dimensional signal acquisition array is activated to perform sub-nanosecond level partial discharge signal synchronous acquisition of the GIS device, thereby obtaining a real-time eight-dimensional signal array. Method step A300 further includes: A310: Locally retrieve the partial discharge detection records of the GIS device, calculate and output the partial discharge signal strength distribution and the partial discharge signal strength span.

[0045] A320: The output gain level allocation strategy is based on the partial discharge signal intensity distribution and the partial discharge signal intensity span.

[0046] A330: According to the gain level allocation strategy, the gain level of each single-dimensional signal acquisition subarray in the eight-dimensional signal acquisition array is allocated, and the multi-gain level initialization of the eight-dimensional signal acquisition array is completed.

[0047] A340: Activate the eight-dimensional signal acquisition array to perform sub-nanosecond level partial discharge signal synchronous acquisition of the GIS device to obtain the real-time eight-dimensional signal array, wherein the real-time single-dimensional signal subarray includes a multi-gain-level time-series UHF signal subarray and a multi-gain-level time-series ultrasonic signal subarray.

[0048] Specifically, in this embodiment, the partial discharge signal strength span is the historical partial discharge signal strength range of the GIS device. Previous partial discharge detection records are retrieved from the GIS device's local monitoring system or historical database, and the partial discharge signal strength data in the records is analyzed to calculate the partial discharge signal strength distribution representing common signal strength ranges and the partial discharge signal strength span representing historical partial discharge signal strength ranges.

[0049] Based on the distribution and range of partial discharge signal strength, a multi-gain level allocation strategy is formulated for each single-dimensional signal capture subarray. For example, based on a 60dB range, the gain is divided into three levels: high (corresponding to weak signals from -60dBm to -40dBm), medium (corresponding to medium signals from -40dBm to -20dBm), and low (corresponding to strong signals from -20dBm to 0dBm), to ensure that the gain level of each subarray can cover all possible partial discharge signal strengths of the device.

[0050] Based on the gain level allocation strategy, each single-dimensional signal acquisition subarray in the eight-dimensional signal acquisition array is assigned a corresponding multi-scale gain level, such as setting three gain levels (high, medium, and low) for each subarray, thus completing the multi-gain level initialization of the eight-dimensional signal acquisition array.

[0051] This allows each subarray in the eight-dimensional signal acquisition array to process partial discharge signals of different intensities through different gain levels, avoiding the loss of weak signals or saturation of strong signals caused by a single gain level.

[0052] Activating the eight-dimensional signal acquisition array essentially means enabling all single-dimensional signal acquisition subarrays to synchronously acquire partial discharge signals from the GIS equipment with sub-nanosecond time precision, resulting in the real-time eight-dimensional signal array. Each real-time single-dimensional signal subarray contains a multi-gain-level time-series UHF signal subarray (e.g., high-gain UHF, medium-gain UHF, and low-gain UHF signals arranged in chronological order) and a multi-gain-level time-series ultrasonic signal subarray (e.g., high-gain, medium-gain, and low-gain ultrasonic signals arranged in chronological order). This ensures that the multi-gain-level signals from each subarray can be acquired synchronously, providing comprehensive raw data for subsequent signal processing.

[0053] A400: After performing signal redundancy verification on the real-time eight-dimensional signal array, the signal confidence of the single-dimensional signal capture subarray is evaluated, and the eight-dimensional reliable signal features are screened and output.

[0054] Furthermore, after performing signal redundancy verification on the real-time eight-dimensional signal array, the signal confidence of the single-dimensional signal acquisition subarray is evaluated, and eight-dimensional reliable signal features are screened and output. Method step A400 further includes: A410: Based on the spherical propagation characteristics of partial discharge signals, a signal identification time window is set to identify signal clusters in the first single-dimensional signal acquisition subarray, so as to remove noise signals with an acquisition dimension < 3 and obtain the first single-dimensional signal filtering subarray.

[0055] A420: Perform multi-gain level position confidence evaluation on the first single-dimensional signal filtering subarray and output the first multi-gain level position signal confidence.

[0056] A430: Based on the real-time eight-dimensional signal array, the signal confidence level is calculated to obtain the eight-dimensional multi-gain level signal confidence level.

[0057] A440: Based on the confidence level of the eight-dimensional multi-gain level signal, perform multi-gain level position information fusion evaluation of the gain level allocation strategy to locate the target reliable gain level.

[0058] A450: Based on the target reliable gain level, gain signal features are extracted from the real-time eight-dimensional signal array mapping to obtain the eight-dimensional reliable signal features.

[0059] Furthermore, the single-dimensional reliable signal features in the eight-dimensional reliable signal features include UHF timestamp, UHF peak amplitude, UHF frequency spectrum peak value, UHF phase correlation coefficient, ultrasonic timestamp, ultrasonic peak amplitude, ultrasonic frequency spectrum peak value, and ultrasonic phase correlation coefficient.

[0060] Furthermore, multi-gain level positional confidence evaluation is performed on the first single-dimensional signal filtering subarray, and the confidence level of the first multi-gain level positional signal is output. Method step A420 further includes: A421: Extract the first multi-gain scale signal-to-noise ratio, the first multi-gain scale pulse width, and the first multi-gain scale phase correlation coefficient from the multi-gain scale time-series UHF signal subarray of the first single-dimensional signal filtering subarray.

[0061] A422: Extract the second multi-gain scale signal-to-noise ratio, the second multi-gain scale pulse width, and the second multi-gain scale phase correlation coefficient from the multi-gain scale temporal ultrasonic signal subarray of the first single-dimensional signal acquisition subarray.

[0062] A423: Based on predefined weighting rules, map and weight the first multi-gain scale signal-to-noise ratio, the first multi-gain scale pulse width, the first multi-gain scale phase correlation coefficient, the second multi-gain scale signal-to-noise ratio, the second multi-gain scale pulse width, and the second multi-gain scale phase correlation coefficient, and output the confidence level of the first multi-gain scale signal.

[0063] Specifically, the spherical propagation characteristic of partial discharge (PD) signals refers to the fact that the signal generated by the PD source diffuses into the surrounding space in the form of a spherical wave. The time difference between the arrival of signals from the same PD source at different single-dimensional signal acquisition subarrays is determined by the difference in propagation distance and is within a reasonable range. Based on the spherical propagation characteristic of PD signals, a signal identification time window (e.g., 10 nanoseconds) is set, and the signals received in the first single-dimensional subarray within this time window are grouped into a signal cluster, with each signal cluster originating from the same PD source.

[0064] It should be understood that a real partial discharge signal should be received by multiple subarrays. Therefore, if a signal cluster is captured by fewer than 3 single-dimensional subarrays, i.e., the capture dimension is <3, it indicates that the signal may be noise. Thus, these noise signals are removed to obtain the first single-dimensional signal filtering subarray that retains signal clusters with a capture dimension ≥3.

[0065] For the first single-dimensional signal filtering subarray that has had noise removed, evaluate the signal quality of each of its multiple gain levels (such as high, medium, and low gain), and output the signal confidence level of each level. The higher the confidence level value, the more reliable the signal at that level.

[0066] Specifically, the confidence level of the gain signal is calculated as follows: The data structure of the multi-gain-level time-series UHF signal subarray in the first single-dimensional signal filtering subarray includes a set of high-gain UHF signals, medium-gain UHF signals, and low-gain UHF signals arranged in chronological order.

[0067] Three parameters reflecting signal quality are extracted from the multi-gain-level timing UHF signal subarray: the first multi-gain-scale signal-to-noise ratio (SNR) representing the ratio of signal strength to noise strength (the higher the ratio, the clearer the signal); the first multi-gain-scale pulse width representing the duration of the partial discharge signal; and the first multi-gain-scale phase correlation coefficient representing the correlation between the partial discharge signal and the phase of the grid voltage.

[0068] The data structure of the multi-gain temporal ultrasonic signal subarray of the first single-dimensional signal acquisition subarray includes a set of high-gain ultrasonic signals, medium-gain ultrasonic signals, and low-gain ultrasonic signals arranged in chronological order.

[0069] Three parameters corresponding to the UHF signal are extracted from the multi-gain time-series ultrasonic signal subarray: the first is the signal-to-noise ratio of the second multi-gain scale, which characterizes the ratio of ultrasonic signal to noise; the second is the pulse width of the second multi-gain scale, which characterizes the duration of ultrasonic signal; and the third is the phase correlation coefficient of the second multi-gain scale, which characterizes the phase correlation between ultrasonic signal and grid voltage.

[0070] Using predefined weighting rules, such as defining the signal-to-noise ratio (SNR) weight as 0.4, the pulse width (PWM) weight as 0.3, and the phase correlation coefficient (PCC) weight as 0.3, the three parameters of the UHF signal (SNR of the first multi-gain scale, PWM, and PCC) and the three parameters of the ultrasonic signal (SNR of the second multi-gain scale, PWM, and PCC) are weighted and summed to obtain the confidence level of the first multi-gain scale signal.

[0071] The other seven single-dimensional subarrays are also calculated using the same method to obtain the confidence level of the first multi-gain level signal, and finally the confidence levels of the eight multi-gain level signals of the eight subarrays are obtained, and the confidence levels of the eight-dimensional multi-gain level signals are output.

[0072] It should be understood that each level of each subarray has a confidence level. Based on this, this embodiment performs a fusion evaluation of the gain level allocation strategy based on the confidence level of the eight-dimensional multi-gain level signal. For example, it looks at which level has a high confidence level in multiple subarrays and finds the gain level with the highest confidence level in each subarray as the target reliable gain level. The target reliable gain level is then used as a reference for signal feature extraction.

[0073] Based on the target reliable gain level, features are extracted from the signal at the corresponding level in the real-time eight-dimensional signal array to obtain the eight-dimensional reliable signal features. The single-dimensional reliable signal features in the eight-dimensional reliable signal features include UHF timestamp, UHF peak amplitude, UHF frequency spectrum peak value, UHF phase correlation coefficient, ultrasonic timestamp, ultrasonic peak amplitude, ultrasonic frequency spectrum peak value, and ultrasonic phase correlation coefficient.

[0074] Among them, the UHF timestamp refers to the time when the UHF signal arrives at the subarray, which is used for triangulation positioning; the UHF peak amplitude refers to the strongest intensity of the UHF signal, reflecting the intensity of the partial discharge source; the UHF frequency spectrum peak refers to the main frequency of the UHF signal, reflecting the type of partial discharge source, such as the frequency characteristics of metal impurity discharge; and the UHF phase correlation coefficient characterizes the correlation between the UHF signal and the phase of the grid voltage, which is used to determine whether it is a real partial discharge signal.

[0075] Among them, the ultrasonic timestamp refers to the time when the ultrasonic signal arrives at the subarray, which is used to assist in positioning; the ultrasonic peak amplitude refers to the strongest intensity of the ultrasonic signal, which is used to assist in judging the intensity of the partial discharge source; the peak value of the ultrasonic frequency spectrum is the main frequency of the ultrasonic signal, which is used to assist in judging the type of partial discharge source; and the ultrasonic phase correlation coefficient characterizes the correlation between the ultrasonic signal and the phase of the power grid voltage, which is used to assist in verifying the authenticity of the signal.

[0076] The single-dimensional reliable signal features mentioned above together constitute the basic data for subsequent partial discharge localization and defect identification.

[0077] A500: Based on the timestamp information of the eight-dimensional reliable signal characteristics, perform multiple rounds of triangulation measurement verification to locate the latent defect partial discharge space.

[0078] Furthermore, based on the timestamp information of the eight-dimensional reliable signal features, multiple rounds of triangulation measurement verification are performed to locate the latent defect partial discharge space. The method step A500 also includes: A510: Retrieve the eight-dimensional signal space coordinates based on the target confidence gain level.

[0079] A520: Extract eight UHF timestamps from the eight-dimensional trusted signal features of the eight-dimensional signal capture subarrays.

[0080] A530: Taking the horizontal direction of the first single-dimensional signal acquisition subarray as the first reference direction, calculate the seven relative time differences of the remaining seven single-dimensional signal acquisition subarrays based on the eight UHF timestamps.

[0081] A540: Based on the eight-dimensional signal spatial coordinates and seven relative time differences, establish a set of trigonometric measurement equations, solve and output the first set of three-dimensional coordinates of the partial discharge source.

[0082] A550: Traverse the horizontal direction of the eight single-dimensional signal acquisition subarrays, update the reference direction by analogy, perform triangulation calculation, and obtain the three-dimensional coordinates of the eight partial discharge sources.

[0083] A560: Integrate the three-dimensional coordinates of the eight sets of partial discharge sources to output the latent defect partial discharge space.

[0084] Specifically, based on the target confidence gain level previously located by A440, the three-dimensional coordinates of the installation position of each single-dimensional signal acquisition subarray on the metal casing of the GIS equipment are obtained to form the eight-dimensional signal space coordinates. It should be noted that these coordinates are pre-stored when constructing the eight-dimensional array and are used for the sensor position input for triangulation.

[0085] Because UHF signals are Since the propagation speed in the signal is stable, this embodiment extracts the UHF timestamps of each of the eight single-dimensional subarrays from the eight-dimensional reliable signal features. It should be understood that the UHF timestamp refers to the time when the UHF signal arrives at the subarray, which is a key parameter for time difference positioning.

[0086] Using the horizontal direction of the first one-dimensional subarray, such as due north, as the first reference direction, the time difference of the remaining seven subarrays relative to this reference direction is calculated using eight UHF timestamps. For example, the timestamp of the reference direction is... The timestamps of the other subarrays are arrive The relative time difference is , This reflects the time difference in arrival of the partial discharge signal at different subarrays.

[0087] Using the eight-dimensional signal space coordinates representing the installation position of each subarray and seven relative time differences, based on the time difference positioning principle (that is, the distance difference between the partial discharge source and different sensors is equal to the propagation speed multiplied by the time difference), a system of equations is established to calculate the first set of three-dimensional coordinates of the partial discharge source representing the initial position of the partial discharge source.

[0088] The horizontal direction of each subarray is used as the reference direction in sequence, and the steps of calculating the relative time difference and triangulation are repeated to obtain eight sets of three-dimensional coordinates of partial discharge sources. It should be understood that each reference direction in the eight sets of three-dimensional coordinates of partial discharge sources corresponds to a set of coordinates. This embodiment uses multiple rounds of calculation to reduce the error of a single reference direction.

[0089] The average value is obtained by taking the least squares method or by weighting the average value according to the confidence level of each set of coordinates. The three-dimensional coordinates of the eight sets of partial discharge sources are then fused to obtain the final three-dimensional coordinates of the partial discharge sources. The output is the latent defect partial discharge space that characterizes the specific location range of the partial discharge source, which is used to guide maintenance personnel to accurately locate the defect.

[0090] The UHF peak amplitude, UHF frequency spectrum peak value, UHF phase correlation coefficient, ultrasonic timestamp, ultrasonic peak amplitude, ultrasonic frequency spectrum peak value, and ultrasonic phase correlation coefficient, which are included in the eight single-dimensional reliable signal features excluding the UHF timestamp, are subjected to multi-subarray multi-mode feature fusion processing to obtain a multi-dimensional feature description of the partial discharge source.

[0091] The multi-dimensional feature description of the partial discharge source is bound to the latent defect partial discharge space and sent to provide users with a more comprehensive basis for decision-making.

[0092] This embodiment achieves the technical effect of comprehensively collecting partial discharge signals from insulation defects in GIS equipment and accurately locating the signal source, providing a reliable decision-making basis for the real-time operation and maintenance of GIS equipment.

[0093] Example 2 is based on the same inventive concept as the detection and location method based on partial discharge signals of insulation defects in GIS equipment in the previous examples, such as... Figure 2 As shown, the present invention provides a detection and location system for partial discharge signals of insulation defects in GIS equipment, wherein the system includes: The capture array construction module 11 is used to construct an eight-dimensional signal capture array by performing partial discharge signal capture analysis on GIS equipment. Each signal capture subarray includes a multi-scale gain PGA, a UHF ultra-high frequency sensor, and an ultrasonic sensor.

[0094] The temporary deployment execution module 12 is used to temporarily deploy the eight-dimensional signal capture array onto the metal casing of the GIS device without damage when the GIS device shows a suspected partial discharge signal due to insulation defects.

[0095] The signal acquisition and execution module 13 is used to initialize the eight-dimensional signal acquisition array with multi-gain based on the partial discharge signal strength span of the GIS device, and then activate the eight-dimensional signal acquisition array to perform sub-nanosecond level partial discharge signal synchronous acquisition of the GIS device to obtain a real-time eight-dimensional signal array.

[0096] The signal quality assessment module 14 is used to perform signal redundancy verification on the real-time eight-dimensional signal array, evaluate the signal confidence of the single-dimensional signal capture subarray, and filter and output eight-dimensional reliable signal features.

[0097] The defect space localization module 15 is used to perform multiple rounds of triangulation measurement and verification based on the timestamp information of the eight-dimensional reliable signal features to locate the latent defect partial discharge space.

[0098] Furthermore, the capture array construction module 11 is also used for: The location of the high-incidence area of ​​internal partial discharge is located using the equipment drawings of the GIS device; the effective signal capture area of ​​the metal casing of the GIS device is identified starting from the location of the high-incidence area of ​​internal partial discharge; the effective signal capture area is used as a spatial constraint, and non-uniform positioning of the eight-dimensional monitoring space is performed according to the shape of the metal casing of the GIS device; by simulating a partial discharge source, a signal capture coverage test is performed in the eight-dimensional monitoring space to locate the eight-dimensional signal capture array.

[0099] Furthermore, the capture array construction module 11 is also used for: Interactively obtain the minimum detectable signal threshold of the UHF sensor; local call. Gas attenuation coefficient and spherical propagation attenuation law of partial discharge UHF signal; taking the location of the internal partial discharge high-incidence area as the starting point, according to The maximum permissible propagation distance of the UHF signal is calculated based on the gas attenuation coefficient, the spherical propagation attenuation law of the partial discharge UHF signal, and the minimum detectable signal threshold, and the effective area of ​​the UHF signal is marked. The minimum detectable vibration threshold of the ultrasonic sensor is obtained interactively. The attenuation coefficient of the shell material and the mechanical conduction characteristics of the partial discharge ultrasonic signal are locally retrieved. Starting from the location of the internal high-incidence area of ​​partial discharge, the maximum permissible propagation distance of the ultrasonic signal is calculated based on the attenuation coefficient of the shell material, the mechanical conduction characteristics of the partial discharge ultrasonic signal, and the minimum detectable vibration threshold, and the effective area of ​​the ultrasonic signal is marked. The intersection area of ​​the effective area of ​​the UHF signal and the effective area of ​​the ultrasonic signal is taken as the effective signal capture area.

[0100] Furthermore, the signal acquisition and execution module 13 is also used for: The system locally retrieves the partial discharge (PD) detection records of the GIS device, calculates and outputs the PD signal strength distribution and the PD signal strength span; uses the PD signal strength distribution and the PD signal strength span as the basis for gain level allocation, and outputs a gain level allocation strategy; according to the gain level allocation strategy, it allocates the gain level of each single-dimensional signal acquisition subarray in the eight-dimensional signal acquisition array, completing the multi-gain level initialization of the eight-dimensional signal acquisition array; it activates the eight-dimensional signal acquisition array to perform sub-nanosecond level PD signal synchronous acquisition of the GIS device, obtaining the real-time eight-dimensional signal array, wherein the real-time single-dimensional signal subarray includes a multi-gain level time-series UHF signal subarray and a multi-gain level time-series ultrasonic signal subarray.

[0101] Furthermore, the signal quality assessment module 14 is also used for: Based on the spherical propagation characteristics of partial discharge signals, a signal identification time window is set, and signal cluster identification is performed on the first single-dimensional signal acquisition subarray to remove noise signals with an acquisition dimension < 3, thus obtaining the first single-dimensional signal filtering subarray. Multi-gain level positional signal evaluation is performed on the first single-dimensional signal filtering subarray to output the first multi-gain level signal confidence score. Signal confidence scores are calculated analogously to the real-time eight-dimensional signal array to obtain the eight-dimensional multi-gain level signal confidence score. Based on the eight-dimensional multi-gain level signal confidence score, multi-gain level positional signal fusion evaluation of the gain level allocation strategy is performed to locate the target reliable gain level. Based on the target reliable gain level, gain signal features are extracted on the real-time eight-dimensional signal array mapping to obtain the eight-dimensional reliable signal features.

[0102] Furthermore, the defect spatial positioning module 15 is also used for: The eight-dimensional signal spatial coordinates are retrieved based on the target reliable gain level; eight UHF timestamps of eight single-dimensional signal acquisition subarrays are extracted from the eight-dimensional reliable signal features; taking the horizontal direction of the first single-dimensional signal acquisition subarray as the first reference direction, the seven relative time differences of the remaining seven single-dimensional signal acquisition subarrays are calculated based on the eight UHF timestamps; a set of triangulation equations is established based on the eight-dimensional signal spatial coordinates and the seven relative time differences, and the first set of partial discharge source three-dimensional coordinates is output; the horizontal direction of the eight single-dimensional signal acquisition subarrays is traversed, the reference direction is updated by analogy, and triangulation is performed to obtain eight sets of partial discharge source three-dimensional coordinates; the eight sets of partial discharge source three-dimensional coordinates are fused to output the latent defect partial discharge space.

[0103] Furthermore, the signal quality assessment module 14 is also used for: The first multi-gain scale signal-to-noise ratio, the first multi-gain scale pulse width, and the first multi-gain scale phase correlation coefficient are extracted from the multi-gain scale time-series UHF signal subarray of the first single-dimensional signal filtering subarray; the second multi-gain scale signal-to-noise ratio, the second multi-gain scale pulse width, and the second multi-gain scale phase correlation coefficient are extracted from the multi-gain scale time-series ultrasonic signal subarray of the first single-dimensional signal acquisition subarray; based on a predefined weighting rule, the first multi-gain scale signal-to-noise ratio, the first multi-gain scale pulse width, the first multi-gain scale phase correlation coefficient, the second multi-gain scale signal-to-noise ratio, the second multi-gain scale pulse width, and the second multi-gain scale phase correlation coefficient are mapped and weighted, and the confidence level of the first multi-gain scale signal is output.

[0104] Furthermore, the single-dimensional reliable signal features in the eight-dimensional reliable signal features include UHF timestamp, UHF peak amplitude, UHF frequency spectrum peak value, UHF phase correlation coefficient, ultrasonic timestamp, ultrasonic peak amplitude, ultrasonic frequency spectrum peak value, and ultrasonic phase correlation coefficient.

[0105] Furthermore, the capture array construction module 11 is also used for: The system retrieves the equipment operation and maintenance records of the same model of GIS equipment locally; it locates the high-incidence area of ​​partial discharge based on the equipment drawings and equipment operation and maintenance records, and outputs the location of the internal high-incidence area of ​​partial discharge.

[0106] In summary, any of the methods or steps described above can be stored as computer instructions or programs in various types of computer memory, and the computer instructions or programs can be recognized by various types of computer processors to implement any of the above methods or steps.

[0107] Based on the above specific embodiments of the present invention, any improvements and modifications made to the present invention by those skilled in the art without departing from the principle of the present invention shall fall within the patent protection scope of the present invention.

Claims

1. A method for detecting and locating partial discharge signals of insulation defects in GIS equipment, characterized in that, The method includes: By performing partial discharge signal capture analysis on GIS equipment, an eight-dimensional signal capture array was constructed. Each signal capture subarray includes a multi-scale gain PGA, a UHF ultra-high frequency sensor, and an ultrasonic sensor. When the GIS equipment shows a suspected partial discharge signal due to insulation defects, a magnetic base is used to migrate and attach the eight-dimensional signal capture array to the metal casing of the GIS equipment for a non-damaging temporary deployment. Based on the partial discharge signal strength span of the GIS device, after initializing the eight-dimensional signal acquisition array with multi-gain banding, the eight-dimensional signal acquisition array is activated to perform sub-nanosecond level partial discharge signal synchronous acquisition of the GIS device, thereby obtaining a real-time eight-dimensional signal array. After performing signal redundancy verification on the real-time eight-dimensional signal array, the signal confidence of the single-dimensional signal acquisition subarray is evaluated, and the eight-dimensional reliable signal features are screened and output. Based on the timestamp information of the eight-dimensional reliable signal characteristics, multiple rounds of triangulation measurement and verification are performed to locate the latent defect partial discharge space.

2. The detection and location method based on partial discharge signal of insulation defects in GIS equipment as described in claim 1, characterized in that, An eight-dimensional signal acquisition array is constructed by performing partial discharge signal capture analysis on GIS equipment. The method includes: The location of high-incidence areas of localized emission can be determined using the equipment drawings of the GIS device; Starting from the location of the high-incidence area of ​​internal partial discharge, the effective signal capture area of ​​the metal casing of the GIS equipment is identified; Using the effective signal capture area as a spatial constraint, and based on the shape of the metal casing of the GIS device, perform non-uniform positioning of the eight-dimensional monitoring space; By simulating a partial discharge source, a signal acquisition coverage test is performed in the eight-dimensional monitoring space to locate the eight-dimensional signal acquisition array.

3. The detection and location method based on partial discharge signal of insulation defects in GIS equipment as described in claim 2, characterized in that, Starting from the location of the high-incidence area of ​​internal partial discharge, the method for identifying the effective signal capture area of ​​the metal casing of the GIS equipment includes: The minimum detectable signal threshold of the UHF ultra-high frequency sensor is obtained interactively; Local call Gas attenuation coefficient and attenuation law of partial discharge UHF signal spherical propagation; Starting from the location of the aforementioned high-incidence area of ​​internal partial discharge, based on Based on the gas attenuation coefficient, the spherical propagation attenuation law of partial discharge UHF signal, and the minimum detectable signal threshold, calculate the maximum allowable propagation distance of UHF signal and mark the effective area of ​​UHF signal; The minimum detectable vibration threshold of the ultrasonic sensor is obtained interactively. Locally invokes the attenuation coefficient of the shell material and the mechanical transmission characteristics of the partial discharge ultrasonic signal; Starting from the location of the high-incidence area of ​​internal partial discharge, the maximum allowable transmission distance of the ultrasonic signal is calculated based on the attenuation coefficient of the shell material, the mechanical transmission characteristics of the partial discharge ultrasonic signal, and the minimum detectable vibration threshold, and the effective area of ​​the ultrasonic signal is marked. The intersection of the effective UHF signal region and the effective ultrasonic signal region is taken as the effective signal capture region.

4. The detection and location method based on partial discharge signal of insulation defects in GIS equipment as described in claim 1, characterized in that, Based on the partial discharge signal strength span of the GIS device, after initializing the eight-dimensional signal acquisition array with multi-gain banding, the eight-dimensional signal acquisition array is activated to perform sub-nanosecond level partial discharge signal synchronous acquisition of the GIS device, thereby obtaining a real-time eight-dimensional signal array. The method includes: The partial discharge detection records of the GIS device are retrieved locally, and the partial discharge signal strength distribution and the partial discharge signal strength span are calculated and output. The output gain level allocation strategy is based on the partial discharge signal intensity distribution and the partial discharge signal intensity span. According to the gain level allocation strategy, the gain level of each single-dimensional signal acquisition subarray in the eight-dimensional signal acquisition array is allocated, and the multi-gain level initialization of the eight-dimensional signal acquisition array is completed. The eight-dimensional signal acquisition array is activated to perform sub-nanosecond level partial discharge signal synchronous acquisition of the GIS device, thereby obtaining the real-time eight-dimensional signal array, wherein the real-time single-dimensional signal subarray includes a multi-gain-level time-series UHF signal subarray and a multi-gain-level time-series ultrasonic signal subarray.

5. The detection and location method based on partial discharge signal of insulation defects in GIS equipment as described in claim 4, characterized in that, After performing signal redundancy verification on the real-time eight-dimensional signal array, the signal confidence of the single-dimensional signal acquisition subarray is evaluated, and eight-dimensional reliable signal features are screened and output. The method includes: Based on the spherical propagation characteristics of partial discharge signals, a signal identification time window is set to identify signal clusters in the first single-dimensional signal acquisition subarray, so as to remove noise signals with an acquisition dimension < 3 and obtain the first single-dimensional signal filtering subarray. Perform multi-gain level position signal evaluation on the first single-dimensional signal filtering subarray and output the first multi-gain level position signal confidence score; Based on the real-time eight-dimensional signal array, the signal confidence level is calculated to obtain the eight-dimensional multi-gain level signal confidence level. Based on the confidence level of the eight-dimensional multi-gain level signal, perform the multi-gain level position information fusion evaluation of the gain level allocation strategy to locate the target reliable gain level; Based on the target reliable gain level, gain signal features are extracted from the real-time eight-dimensional signal array mapping to obtain the eight-dimensional reliable signal features.

6. The detection and location method based on partial discharge signal of insulation defects in GIS equipment as described in claim 5, characterized in that, Based on the timestamp information of the eight-dimensional reliable signal features, multiple rounds of triangulation measurement verification are performed to locate the latent defect partial discharge space. The method includes: The eight-dimensional signal space coordinates are retrieved based on the target reliable gain level; Eight UHF timestamps of eight single-dimensional signal capture subarrays are extracted from the eight-dimensional trusted signal features; Using the horizontal direction of the first single-dimensional signal acquisition subarray as the first reference direction, and based on the eight UHF timestamps, calculate the seven relative time differences of the remaining seven single-dimensional signal acquisition subarrays; Based on the eight-dimensional signal spatial coordinates and seven relative time differences, a set of trigonometric measurement equations is established, and the first set of three-dimensional coordinates of the partial discharge source is calculated and output. By traversing the horizontal direction of the eight single-dimensional signal acquisition subarrays, updating the reference direction by analogy, and performing triangulation calculations, the three-dimensional coordinates of the eight partial discharge sources are obtained. By fusing the three-dimensional coordinates of the eight sets of partial discharge sources, the latent defect partial discharge space is output.

7. The detection and location method based on partial discharge signal of insulation defects in GIS equipment as described in claim 5, characterized in that, Perform multi-gain level position signal evaluation on the first single-dimensional signal filtering subarray and output the first multi-gain level position signal confidence score. The method includes: The first multi-gain scale signal-to-noise ratio, the first multi-gain scale pulse width, and the first multi-gain scale phase correlation coefficient are extracted from the multi-gain scale time-series UHF signal subarray of the first single-dimensional signal filtering subarray. The signal-to-noise ratio, pulse width, and phase correlation coefficient of the second multi-gain scale are extracted from the multi-gain scale temporal ultrasonic signal subarray of the first single-dimensional signal acquisition subarray. Based on predefined weighting rules, the first multi-gain scale signal-to-noise ratio, the first multi-gain scale pulse width, the first multi-gain scale phase correlation coefficient, the second multi-gain scale signal-to-noise ratio, the second multi-gain scale pulse width, and the second multi-gain scale phase correlation coefficient are mapped and weighted to output the confidence level of the first multi-gain scale signal.

8. The detection and location method based on partial discharge signal of insulation defects in GIS equipment as described in claim 5, characterized in that, The single-dimensional reliable signal features in the eight-dimensional reliable signal features include UHF timestamp, UHF peak amplitude, UHF frequency spectrum peak value, UHF phase correlation coefficient, ultrasonic timestamp, ultrasonic peak amplitude, ultrasonic frequency spectrum peak value, and ultrasonic phase correlation coefficient.

9. The detection and location method based on partial discharge signal of insulation defects in GIS equipment as described in claim 2, characterized in that, The method for locating high-incidence areas of localized emissions within the GIS equipment using its equipment drawings includes: Locally access the equipment maintenance records of the same model of GIS equipment; Based on the equipment drawings and equipment operation and maintenance records, the high-incidence area of ​​partial discharge is located, and the location of the internal high-incidence area of ​​partial discharge is output.

10. A detection and location system based on partial discharge signals of insulation defects in GIS equipment, characterized in that, The steps for implementing the method according to any one of claims 1 to 9 include: The capture array construction module is used to construct an eight-dimensional signal capture array by performing partial discharge signal capture analysis on GIS equipment. Each signal capture subarray includes a multi-scale gain PGA, a UHF ultra-high frequency sensor, and an ultrasonic sensor. The temporary deployment execution module is used to temporarily deploy the eight-dimensional signal capture array onto the metal casing of the GIS device without damage when the GIS device shows a suspected partial discharge signal due to an insulation defect. The signal acquisition and execution module is used to initialize the eight-dimensional signal acquisition array with multi-gain classification based on the partial discharge signal strength span of the GIS device, and then activate the eight-dimensional signal acquisition array to perform sub-nanosecond level partial discharge signal synchronous acquisition of the GIS device to obtain a real-time eight-dimensional signal array. The signal quality assessment module is used to perform signal redundancy verification on the real-time eight-dimensional signal array, evaluate the signal confidence of the single-dimensional signal capture subarray, and filter and output eight-dimensional reliable signal features. The defect space localization module is used to perform multiple rounds of triangulation measurement and verification based on the timestamp information of the eight-dimensional reliable signal features to locate the latent defect partial discharge space.

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