Partial discharge detection method, system and equipment based on imaging

Abstract

The present invention provides a partial discharge detection method, system and equipment based on imaging, which relate to the field of power detection technology. The detection method includes step S1: acquiring imaging data of power equipment, and determining a number of abnormal areas based on the imaging data; step S2: determining the abnormal coefficient of each abnormal area; step S3: calculating the abnormal emergency value of the equipment based on the determined abnormal coefficient, and determining the fault emergency signal of the power equipment accordingly. The present invention can obtain the abnormal area, that is, the location where partial discharge exists, and can further obtain the fault emergency signal to effectively judge the urgency of partial discharge at different locations. Based on this, the problem that a single infrared detection method is used in the prior art to perform partial discharge detection, the detection principle is relatively one-sided and the information obtained is relatively shallow, which will lead to the problem that the accuracy of the detection result is not ideal and is not conducive to the subsequent processing of partial discharge is solved.

Description

Technical Field

[0001] The present invention relates to the technical field of power detection, and in particular to a partial discharge detection method, system and equipment based on imaging. Background Art

[0002] Partial discharge refers to the discharge in a local area caused by internal defects in the insulation of high-voltage power equipment under the action of an electric field. It has an adverse effect on the insulating medium, causing the insulation strength of the insulating medium to gradually decrease, and eventually causing a short circuit failure in the high-voltage power equipment, resulting in economic losses or even casualties. Therefore, power equipment maintenance personnel need to conduct partial discharge detection on operating high-voltage electrical equipment to promptly discover and deal with internal insulation defects.

[0003] Traditional partial discharge detection relies on visual inspection combined with existing experience to make judgments. This method has problems with accuracy and low efficiency, and cannot meet the growing detection needs with the development of power technology. At present, most of the partial discharge detections carried out use a single infrared detection method, specifically: using an infrared thermal imager based on infrared thermal imaging technology to obtain infrared radiation images. Since the partial discharge area has a large thermal contrast, the corresponding partial discharge situation can be obtained by observing and analyzing the temperature situation in the infrared radiation image. For example, the Chinese patent with publication number CN115616356A provides a method and device for partial discharge detection of power poles based on infrared images. The image with temperature data taken by the infrared camera can be used to determine whether there is a partial discharge phenomenon on the photographed power pole.

[0004] However, this simple infrared detection method has the following defects: first, it only relies on temperature as an indicator for judgment, lacks comprehensiveness, and is prone to misjudgment; second, the amount of information contained in the infrared radiation image is relatively small, and it is difficult for technicians to further analyze the partial discharge. Therefore, the simple infrared detection method usually takes the determination of the location of the partial discharge as the ultimate goal, but cannot obtain deeper information, which is not conducive to the subsequent processing of the partial discharge. Summary of the invention

[0005] The object of the present invention is to provide a partial discharge detection method, system and equipment based on imaging, so as to solve the problem mentioned in the above background technology that the prior art adopts a single infrared detection method to perform partial discharge detection, the detection principle is relatively one-sided and the information obtained is relatively shallow, which leads to the detection result accuracy is not ideal and is not conducive to the subsequent processing of partial discharge.

[0006] The present invention is achieved by adopting the following technical solutions:

[0007] A partial discharge detection method based on imaging comprises the following steps:

[0008] Step S1: acquiring imaging data of the power equipment, and determining a number of abnormal areas based on the imaging data;

[0009] Step S2: determining the abnormal coefficient of each abnormal area;

[0010] Step S3: Based on the determined abnormal coefficient, the equipment abnormal emergency value is calculated, and the fault emergency signal of the power equipment is determined accordingly;

[0011] The fault emergency signal includes a high emergency signal of equipment fault and a low emergency signal of equipment fault.

[0012] Furthermore, in step S1, the specific steps of determining the abnormal area are:

[0013] Step S1-1: The acquired imaging data includes a sound imaging view and a temperature imaging view,

[0014] If the sound source frequency value in the sound imaging view is greater than or equal to the set sound source frequency threshold, a sound source abnormality signal is generated; if the temperature value in the temperature imaging view is greater than or equal to the set temperature threshold, a temperature abnormality signal is generated;

[0015] Step S1-2: Mark the positions corresponding to the abnormal sound source signal and the abnormal temperature signal in the power equipment respectively to obtain the abnormal sound source area and the abnormal temperature area.

[0016] Furthermore, in step S2, the specific steps of determining the abnormal coefficient are:

[0017] Step S2-1: for a number of abnormal areas in the power equipment, respectively collect the coincidence characteristic value of each abnormal area; wherein the coincidence characteristic value includes the number of coincidences of the abnormal areas;

[0018] Step S2-2: sorting based on the overlapping feature value of each abnormal area to obtain a single abnormal area and a coincident abnormal area; wherein the single abnormal area includes a sound source abnormal area or a temperature abnormal area, and the coincident abnormal area includes both a sound source abnormal area and a temperature abnormal area;

[0019] Step S2-3: For the single abnormal region and the overlapping abnormal region, obtain the single region abnormal value and the overlapping region abnormal value respectively.

[0020] Furthermore, in step S2-2, the specific method of sorting is:

[0021] If the number of overlapping abnormal regions collected in a certain abnormal region is 1, the abnormal region is marked as a single abnormal region;

[0022] If the number of overlapped abnormal regions collected in a certain abnormal region is 2, the abnormal region is marked as an overlapped region anomaly.

[0023] Furthermore, in step S2-3, the specific steps of obtaining the outlier value of a single region are:

[0024] Step S2-3-d1: Obtain the area value of a single abnormal region;

[0025] Step S2-3-d2: Divide the single abnormal region area value by the set single abnormal region area standard value to obtain the single region abnormal value Zd.

[0026] Furthermore, in step S2-3, the specific steps of obtaining the abnormal value of the overlapped area are:

[0027] Step S2-3-c1: Obtain the abnormal area value of the overlapped area;

[0028] Step S2-3-c2: Obtain the abnormal time value of the overlap area;

[0029] Step S2-3-c3: Calculate the difference between the abnormal area value of the overlapping area and the abnormal time value of the overlapping area to obtain the abnormal value Zc of the overlapping area.

[0030] Furthermore, in step S3, the specific steps of determining the fault emergency signal are:

[0031] Step S3-1: add up all the single-area abnormal values ​​in the power equipment to obtain the single-area abnormal total value ZZd; add up all the overlapping-area abnormal values ​​in the power equipment to obtain the overlapping-area abnormal total value ZZc;

[0032] Step S3-2: Substitute the obtained single area abnormal total value ZZd and the overlap area abnormal total value ZZc into the equipment abnormal emergency value calculation formula to obtain the equipment abnormal emergency value ZJS;

[0033] The calculation formula of the equipment abnormal emergency value is as follows:

[0034] ZJS=a1*ZZd+a2*ZZc,

[0035] In the formula, a1 and a2 are weight ratio coefficients;

[0036] Step S3-3: If the equipment abnormality emergency value ZJS is greater than or equal to the set equipment abnormality emergency threshold, a high emergency signal of equipment failure is generated; if the equipment abnormality emergency value ZJS is less than the set equipment abnormality emergency threshold, a low emergency signal of equipment failure is generated.

[0037] Furthermore, the method further comprises the following steps:

[0038] Step S4: determining an inspection route based on the determined fault emergency signal;

[0039] Among them, when a fault emergency signal is obtained, a single abnormal area and a overlapping abnormal area are extracted respectively; according to the inspection route, regional inspection is performed on the overlapping abnormal area first, and then regional inspection is performed on the single abnormal area.

[0040] A partial discharge detection system based on imaging is used to execute the partial discharge detection method based on imaging described above, comprising a detection module, an analysis module and a judgment module, wherein: the detection module is used to obtain imaging data of power equipment and determine abnormal areas, the analysis module is used to determine the abnormal coefficient of each abnormal area, and the judgment module is used to determine the fault emergency signal of the power equipment.

[0041] A partial discharge detection device based on imaging includes the above-mentioned partial discharge detection system based on imaging.

[0042] The beneficial effects achieved by the present invention are:

[0043] Provided is a partial discharge detection method, system and device based on imaging mode, by collecting data from power equipment, displaying it in the form of images and analyzing the image data, the abnormal area, i.e. the location where partial discharge exists, can be obtained, and the fault emergency signal can be further obtained to effectively judge the urgency of partial discharge at different locations. Compared with the existing technology using a single infrared detection method, the present invention makes a more accurate judgment on partial discharge and can obtain deeper emergency information, so as to facilitate reasonable and efficient subsequent treatment of partial discharge. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] Figure 1 is a schematic flow chart of the partial discharge detection method described in Example 1 of the present invention;

[0045] Figure 2 is a schematic flow chart of the partial discharge detection method described in Embodiment 2 of the present invention;

[0046] Figure 3 It is a schematic block diagram of the structure of the partial discharge detection system described in Example 3 of the present invention. DETAILED DESCRIPTION

[0047] To clearly illustrate the solution in the present invention, further description is given below in conjunction with the accompanying drawings:

[0048] Example 1

[0049] Please refer to Figure 1This embodiment provides a partial discharge detection method based on imaging, comprising the following steps:

[0050] Step S1: acquiring imaging data of the electric power equipment, and determining a number of abnormal areas based on the imaging data.

[0051] Specifically:

[0052] In this embodiment, a microphone matrix board and an infrared temperature sensor are installed in the power equipment; the microphone matrix board is used to receive and locate the sound source signal of the power equipment and generate a sound imaging view; the infrared temperature sensor is used to convert the power signal radiated by the heating part of the power equipment into an electrical signal, and then form an infrared thermal image as a temperature imaging view to display the temperature distribution of the power equipment.

[0053] The specific steps to determine the abnormal area are as follows:

[0054] Step S1-1: The acquired imaging data includes a sound imaging view and a temperature imaging view. If the sound source frequency value in the sound imaging view is greater than or equal to the set sound source frequency threshold, a sound source abnormality signal is generated; if the temperature value in the temperature imaging view is greater than or equal to the set temperature threshold, a temperature abnormality signal is generated;

[0055] If the sound source frequency value in the sound imaging view is less than the set sound source frequency threshold, a sound source normal signal is generated; if the temperature value in the temperature imaging view is less than the set temperature threshold, a temperature normal signal is generated.

[0056] Step S1-2: Mark the positions corresponding to the abnormal sound source signal and the abnormal temperature signal in the power equipment respectively to obtain the abnormal sound source area and the abnormal temperature area.

[0057] Step S2: Determine the abnormal coefficient of each abnormal area.

[0058] Specifically:

[0059] The specific steps to determine the anomaly coefficient include:

[0060] Step S2-1: for a plurality of abnormal areas within the power equipment, respectively collect the coincident characteristic values ​​of each abnormal area;

[0061] Among them, the overlapping characteristic value includes the number of overlapping abnormal areas; specifically, the number of overlapping abnormal areas includes 1 or 2; if only one of the abnormal sound source area or the abnormal temperature area appears, and the abnormal sound source area and the abnormal temperature area do not overlap with each other, then the number of overlaps in the area is 1; if the abnormal sound source area and the abnormal temperature area appear at the same time, and the abnormal sound source area and the abnormal temperature area overlap with each other, then the number of overlaps in the area is 2.

[0062] Step S2-2: sorting based on the overlapping feature value of each abnormal area to obtain a single abnormal area and a coincident abnormal area; wherein the single abnormal area includes a sound source abnormal area or a temperature abnormal area, and the coincident abnormal area includes both a sound source abnormal area and a temperature abnormal area;

[0063] The specific method of sorting is: if the number of overlapping abnormal regions collected in a certain abnormal region is 1, the abnormal region is marked as a single abnormal region; if the number of overlapping abnormal regions collected in a certain abnormal region is 2, the abnormal region is marked as an overlapping region abnormality;

[0064] Among them, the purpose of sorting is to classify the abnormal performance of power equipment. Specifically: when power equipment fails during operation, it may show local temperature abnormality, local noise abnormality, or local temperature abnormality and noise abnormality. The different number of abnormalities in the area will also reflect the different fault levels in the area, that is, the fault degree of overlapping abnormal areas is greater than the fault degree of a single abnormal area; therefore, according to the results after sorting, the abnormal evaluation and judgment of power equipment can be carried out more accurately.

[0065] Step S2-3: for the single abnormal area and the overlapping abnormal area, obtaining the single area abnormal value and the overlapping area abnormal value respectively;

[0066] in,

[0067] The specific steps to obtain the outliers of a single region are:

[0068] Step S2-3-d1: Obtain the area value of a single abnormal region;

[0069] Step S2-3-d2: Divide the single abnormal region area value by the single abnormal region area standard value set (in advance by a person skilled in the art) to obtain a single region abnormal value Zd;

[0070] It should be noted that for a single abnormal region, the single regional abnormal value is characterized by the size of the region. The larger the area, the greater the abnormality of the region, and vice versa.

[0071] The specific steps to obtain the outliers in the overlapping area are:

[0072] Step S2-3-c1: Obtain the abnormal area value of the overlapped area;

[0073] This step specifically includes:

[0074] Step S2-3-c1-1: respectively obtain the area value of the abnormal sound source region and the area value of the abnormal temperature region, add the area value of the abnormal sound source region and the area value of the abnormal temperature region, and obtain the total area value of the overlapping abnormal region;

[0075] Step S2-3-c1-2: Obtain the overlapping area value of the overlapping abnormal area (the overlapping area value of the sound source abnormal area and the temperature abnormal area);

[0076] Step S2-3-c1-3: Calculate the ratio of the overlap area value of the overlap abnormal area to the total area value of the overlap abnormal area to obtain the abnormal area value of the overlap area;

[0077] Step S2-3-c2: Obtain the abnormal time value of the overlap area;

[0078] This step specifically includes:

[0079] Step S2-3-c2-1: respectively obtain the start time of the generation of the abnormal sound source area and the start time of the generation of the abnormal temperature area, make a difference between the two start times and take the absolute value to obtain the overlap time difference;

[0080] Step S2-3-c2-2: Divide the overlap time difference value by the overlap time difference standard value set in advance (by a person skilled in the art) to obtain the overlap area abnormal time value;

[0081] Step S2-3-c3: Calculate the difference between the abnormal area value of the overlapped area and the abnormal time value of the overlapped area to obtain the abnormal value Zc of the overlapped area;

[0082] It should be noted that for the overlapping abnormal area, the abnormal value of the overlapping area is characterized by the size of the overlapping area and the time difference between the sound source and the stable abnormality generation time. The larger the overlapping area and the smaller the overlapping time, the greater the degree of abnormality in the area, and vice versa.

[0083] Step S3: Based on the determined abnormal coefficient, the equipment abnormal emergency value is calculated, and the fault emergency signal of the power equipment is determined accordingly.

[0084] Specifically:

[0085] The specific steps to determine the emergency signal of a fault include:

[0086] Step S3-1: add up all the single-area abnormal values ​​in the power equipment to obtain a single-area abnormal total value ZZd; add up all the overlapping-area abnormal values ​​in the power equipment to obtain a overlapping-area abnormal total value ZZc.

[0087] Step S3-2: Substitute the obtained single area abnormal total value ZZd and the overlap area abnormal total value ZZc into the equipment abnormal emergency value calculation formula to obtain the equipment abnormal emergency value ZJS;

[0088] The calculation formula of the equipment abnormal emergency value is as follows:

[0089] ZJS=a1*ZZd+a2*ZZc,

[0090] In the formula, a1 and a2 are weight proportion coefficients, a1+a2=1. For example, if a1 is 0.17, a2 is 0.83. The values ​​of a1 and a2 represent the influence of the single area abnormal total value ZZd and the overlapping area abnormal total value ZZc on the equipment abnormal emergency value ZJS.

[0091] Step S3-3: Compare the equipment abnormality emergency value ZJS with the equipment abnormality emergency threshold value. If the equipment abnormality emergency value ZJS is greater than or equal to the set equipment abnormality emergency threshold value, a high emergency signal of equipment failure is generated; if the equipment abnormality emergency value ZJS is less than the set equipment abnormality emergency threshold value, a low emergency signal of equipment failure is generated;

[0092] It should be noted that the equipment abnormality emergency value ZJS is used to reflect the degree of fault in the power equipment. The larger the equipment abnormality emergency value ZJS is, the higher the fault level in the power equipment, that is, the higher the fault urgency of the power equipment, and the operating personnel need to quickly repair the power equipment with high fault urgency.

[0093] In summary, the imaging-based partial discharge detection method provided in this embodiment can comprehensively and accurately obtain the abnormal area, that is, the location where partial discharge exists, by collecting data from the power equipment, displaying it in the form of images, and analyzing the image data from two dimensions: sound source and temperature; and, further, a fault emergency signal can be obtained to effectively judge the urgency of partial discharge at different locations, thereby facilitating reasonable and efficient subsequent disposal of partial discharge.

[0094] Example 2

[0095] Please refer to Figure 2 This embodiment provides a partial discharge detection method based on imaging, which, based on Embodiment 1, further includes:

[0096] Step S4: Determine an inspection route based on the determined fault emergency signal.

[0097] Specifically:

[0098] When a fault emergency signal is received, the single abnormal area and the overlapping abnormal area are extracted respectively; according to the inspection route, the overlapping abnormal area is inspected first, and then the single abnormal area is inspected.

[0099] For the overlapped abnormal area, the specific steps to determine the inspection route include:

[0100] Step S4-c1: obtaining the distance between any two overlapping abnormal areas, and if the distance is less than a preset distance threshold, generating a continued judgment signal; otherwise, generating a regional non-conformity signal, indicating that the two overlapping abnormal areas need to be inspected separately;

[0101] Step S4-c2: When a continue judgment signal is obtained, the abnormal values ​​of any two overlapping areas, the start time of the abnormal sound source area, and the start time of the abnormal temperature area are obtained, and the difference between the two overlapping areas is calculated to obtain the abnormal difference of the overlapping area, the start time difference of the abnormal sound source area, and the start time difference of the abnormal temperature area;

[0102] When performing difference calculation on two overlapping areas, the difference between the abnormal values ​​of the overlapping areas is made, the difference between the start time of the generation of the abnormal sound source area is made, and the difference between the start time of the generation of the abnormal temperature area is made.

[0103] Step S4-c3: comparing the overlap area abnormal difference, the sound source abnormal area start time difference, and the temperature abnormal area start time difference with corresponding preset thresholds respectively;

[0104] If the abnormal difference of the overlapping area, the start time difference of the sound source abnormal area, and the start time difference of the temperature abnormal area are all less than the corresponding preset thresholds, a regional integration signal is generated, indicating that the two overlapping abnormal areas can be inspected together, that is, one of the overlapping abnormal areas can be inspected and the largest abnormal value of the overlapping area can be extracted; otherwise, a regional non-integration signal is generated, indicating that the two overlapping abnormal areas need to be inspected separately;

[0105] Step S4-c4: Obtain the overlap area abnormal value Zc of the integrated overlap abnormal area; arrange them in order from large to small, construct the inspection set {Zc1, Zc2, ..., Zci}, and obtain the integration coefficient, i represents the number of the overlap abnormal area after integration;

[0106] Step S4-c5: Determine the inspection route, requiring that during the inspection, the regional inspection work of the overlapping abnormal areas shall be completed according to the inspection set sequence.

[0107] For a single abnormal area, the specific steps to determine the inspection route include:

[0108] Step S4-d1: Obtain the distance between any two single abnormal areas. If the distance is less than a preset distance threshold, a continue judgment signal is generated; otherwise, a regional non-conformity signal is generated, indicating that the two single abnormal areas need to be inspected separately;

[0109] Step S4-d2: When a continue judgment signal is obtained, obtain any two single area abnormal values ​​and the start time of the sound source abnormal area generation (or the start time of the temperature abnormal area generation), and perform difference calculation on the two single abnormal areas to obtain the single area abnormal difference and the sound source abnormal area start time difference (or the temperature abnormal area start time difference);

[0110] Step S4-d3: comparing the single area abnormal difference, the sound source abnormal area start time difference (or the temperature abnormal area start time difference) with the corresponding preset thresholds respectively;

[0111] If the single-area abnormal difference and the start time difference of the sound source abnormal area (or the start time difference of the temperature abnormal area) are both less than the corresponding preset thresholds, a regional integration signal is generated, indicating that the two single abnormal areas can be inspected together, that is, one of the single abnormal areas can be inspected and the largest single area abnormal value can be extracted; otherwise, a regional non-integration signal is generated, indicating that the two single abnormal areas need to be inspected separately;

[0112] Step S4-d4: Obtain the abnormal value Zd of the overlapping area of ​​the integrated single abnormal area; arrange them in order from large to small, construct the inspection set {Zd1, Zd2, ..., Zdn}, and obtain the integration coefficient, where n represents the number of overlapping abnormal areas after integration;

[0113] Step S4-d5: Determine the inspection route, requiring that during the inspection, the regional inspection of the single abnormal area shall be completed in accordance with the inspection set sequence; wherein, when inspecting a single abnormal area, the inspection paths of the sound source abnormal area and the temperature abnormal area can be carried out simultaneously or separately.

[0114] In summary, the imaging-based partial discharge detection method provided in this embodiment can further determine the inspection route based on the fault emergency signal on the basis of obtaining the partial discharge position and the fault emergency signal. Specifically: the inspection route is planned according to the fault urgency of each abnormal area. Through integrated processing, not only the number of inspections can be reduced, but also reasonable priority inspections can be performed according to the fault urgency of each abnormal area, thereby greatly improving the inspection efficiency.

[0115] Example 3

[0116] Please refer to Figure 3This embodiment provides a partial discharge detection system based on imaging, which is used to execute the detection method described in Example 2. The system includes:

[0117] A detection module, used to obtain imaging data of power equipment and determine abnormal areas;

[0118] Analysis module to determine the anomaly coefficient for each anomaly area:

[0119] A judgment module, used to determine the fault emergency signal of the power equipment;

[0120] The inspection module is used to determine the inspection route according to the fault emergency signal.

[0121] Example 4

[0122] This embodiment provides a partial discharge detection device based on imaging, which includes a memory, a processor, and a computer program stored in the memory and executable on the processor. The processor includes the detection system described in Embodiment 3. When the processor executes the computer program, a partial discharge detection method based on imaging can be implemented.

[0123] It should be noted that the above formulas are all dimensionless and numerical calculations, and the formula is a formula of the most recent real situation obtained by collecting a large amount of data for software simulation, and the preset parameters in the formula are set by technicians in this field according to actual conditions. The parts that are not described in detail or expanded in the above scheme are all prior art, which do not belong to the improvement made by the present invention over the prior art, nor do they belong to the protection scope of the technical solution of the present invention, so they will not be repeated in this article.

[0124] Of course, the above contents are only preferred embodiments of the present invention and cannot be considered to limit the scope of the embodiments of the present invention. The present invention is not limited to the above examples, and equal changes and improvements made by ordinary technicians in the technical field within the essential scope of the present invention should all fall within the scope of the patent coverage of the present invention.

Claims

1. A partial discharge detection method based on imaging, characterized in that: The steps include: Step S1: acquiring imaging data of the power equipment, and determining a number of abnormal areas based on the imaging data; Step S2: determining the abnormal coefficient of each abnormal area; Step S3: Based on the determined abnormal coefficient, the equipment abnormal emergency value is calculated, and the fault emergency signal of the power equipment is determined accordingly; Wherein, the fault emergency signal includes a high emergency signal of equipment fault and a low emergency signal of equipment fault; In step S1, the specific steps of determining the abnormal area are: Step S1-1: The acquired imaging data includes a sound imaging view and a temperature imaging view, If the sound source frequency value in the sound imaging view is greater than or equal to the set sound source frequency threshold, a sound source abnormality signal is generated; if the temperature value in the temperature imaging view is greater than or equal to the set temperature threshold, a temperature abnormality signal is generated; Step S1-2: Mark the positions corresponding to the abnormal sound source signal and the abnormal temperature signal in the power equipment respectively to obtain the abnormal sound source area and the abnormal temperature area; In step S2, the specific steps of determining the abnormal coefficient are: Step S2-1: for a number of abnormal areas in the power equipment, respectively collect the coincidence characteristic value of each abnormal area; wherein the coincidence characteristic value includes the number of coincidences of the abnormal areas; Step S2-2: sorting based on the overlapping feature value of each abnormal area to obtain a single abnormal area and a coincident abnormal area; wherein the single abnormal area includes a sound source abnormal area or a temperature abnormal area, and the coincident abnormal area includes both a sound source abnormal area and a temperature abnormal area; Step S2-3: for the single abnormal area and the overlapping abnormal area, obtaining the single area abnormal value and the overlapping area abnormal value respectively; In step S2-3, the specific steps of obtaining the outlier value of a single region are: Step S2-3-d1: Obtain the area value of a single abnormal region; Step S2-3-d2: Divide the single abnormal region area value by the set single abnormal region area standard value to obtain the single region abnormal value Zd; In step S2-3, the specific steps of obtaining the abnormal value of the overlapped area are: Step S2-3-c1: Obtain the abnormal area value of the overlapped area; This step specifically includes: Step S2-3-c1-1: respectively obtain the area value of the abnormal sound source region and the area value of the abnormal temperature region, add the area value of the abnormal sound source region and the area value of the abnormal temperature region, and obtain the total area value of the overlapping abnormal region; Step S2-3-c1-2: Obtain the overlap area value of the overlap abnormal area; Step S2-3-c1-3: Calculate the ratio of the overlap area value of the overlap abnormal area to the total area value of the overlap abnormal area to obtain the overlap abnormal area value; Step S2-3-c2: Obtain the abnormal time value of the overlap area; This step specifically includes: Step S2-3-c2-1: respectively obtain the start time of the abnormal sound source area and the start time of the abnormal temperature area, subtract the two start times and take the absolute value to obtain the overlap time difference; Step S2-3-c2-2: Divide the overlap time difference value by the set overlap time difference standard value to obtain the overlap area abnormal time value; Step S2-3-c3: Calculate the difference between the abnormal area value of the overlapping area and the abnormal time value of the overlapping area to obtain the abnormal value Zc of the overlapping area.

2. The imaging-based partial discharge detection method according to claim 1, characterized in that: In step S2-2, the specific method of sorting is: If the number of overlapping abnormal regions collected in a certain abnormal region is 1, the abnormal region is marked as a single abnormal region; If the number of overlapped abnormal regions collected in a certain abnormal region is 2, the abnormal region is marked as an overlapped region anomaly.

3. The imaging-based partial discharge detection method according to claim 1, characterized in that: In step S3, the specific steps of determining the fault emergency signal are: Step S3-1: add up all the single-area abnormal values ​​in the power equipment to obtain the single-area abnormal total value ZZd; add up all the overlapping-area abnormal values ​​in the power equipment to obtain the overlapping-area abnormal total value ZZc; Step S3-2: Substitute the obtained single area abnormal total value ZZd and the overlap area abnormal total value ZZc into the equipment abnormal emergency value calculation formula to obtain the equipment abnormal emergency value ZJS; The calculation formula of the equipment abnormal emergency value is as follows: ZJS=a1*ZZd+a2*ZZc, In the formula, a1 and a2 are weight ratio coefficients; Step S3-3: If the equipment abnormality emergency value ZJS is greater than or equal to the set equipment abnormality emergency threshold, a high emergency signal of equipment failure is generated; if the equipment abnormality emergency value ZJS is less than the set equipment abnormality emergency threshold, a low emergency signal of equipment failure is generated.

4. The imaging-based partial discharge detection method according to claim 1, characterized in that: The method further comprises the following steps: Step S4: determining an inspection route based on the determined fault emergency signal; Among them, when a fault emergency signal is obtained, a single abnormal area and a overlapping abnormal area are extracted respectively; according to the inspection route, regional inspection is performed on the overlapping abnormal area first, and then regional inspection is performed on the single abnormal area.

5. A partial discharge detection system based on imaging, used to execute the partial discharge detection method based on imaging as claimed in any one of claims 1 to 4, characterized in that: It includes a detection module, an analysis module and a judgment module, wherein: the detection module is used to obtain imaging data of the power equipment and determine the abnormal area, the analysis module is used to determine the abnormal coefficient of each abnormal area, and the judgment module is used to determine the fault emergency signal of the power equipment.

6. A partial discharge detection device based on imaging, characterized in that: The device comprises the imaging-based partial discharge detection system according to claim 5.

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