Acoustic partial discharge signal data processing method and system

Abstract

The invention provides an acoustic partial discharge signal data processing method and system, and belongs to the technical field of data processing, and the method specifically comprises the steps: a power equipment obtaining module is responsible for determining the distribution data of power equipment in a target detection region, the partial discharge signal analysis module is responsible for determining fault characteristic data of partial discharge signals of the power equipment in different frequency ranges, and the frequency range positioning module is responsible for positioning the distribution data of the power equipment in the target detection area and the fault characteristic data of the partial discharge signals of different power equipment in different frequency ranges. A target frequency range of acoustic partial discharge signals of the target detection area is determined, and the acoustic signal processing module is responsible for determining analysis and processing strategies of the acoustic partial discharge signals of different power devices based on analysis and processing results of the acoustic partial discharge signals of the power devices within the target frequency range; and the data processing efficiency of the acoustic partial discharge signal is improved.

Description

Technical Field

[0001] The present invention belongs to the technical field of data processing, and in particular relates to a method and system for processing acoustic partial discharge signal data. Background Art

[0002] In order to realize the recognition and processing of acoustic partial discharge signals and utilize acoustic signals to realize the recognition and processing of power equipment with abnormal partial discharge, in the invention patent application CN202311609378.7 "Acoustic power partial discharge drone integrated monitoring instrument and equipment based on artificial intelligence", the sound collected by the acoustic receiving unit is filtered and processed, and then the feedback signal of the acoustic signal in the machine learning unit is output to the user end, thereby realizing the recognition and processing of partial discharge acoustic signals.

[0003] The differences in the types of power equipment lead to differences in the significance of fault characteristics in different frequency ranges when partial discharge faults occur in power equipment. Therefore, how to generate differentiated fault feature analysis and processing methods based on the distribution data of power equipment in the inspection target area, and improve the efficiency of fault feature identification and processing on the basis of improving the accuracy of fault feature identification and processing, has become a technical problem that needs to be solved urgently.

[0004] In order to solve the above technical problems, the present application provides a method and system for processing acoustic partial discharge signal data. Summary of the Invention

[0005] To achieve the purpose of the present invention, the present invention adopts the following technical solutions: In a first aspect, the present invention provides an acoustic partial discharge signal data processing system, specifically comprising: Power equipment acquisition module, partial discharge signal analysis module, frequency range positioning module, acoustic signal processing module; The power equipment acquisition module is responsible for determining the distribution data of the power equipment in the target detection area; The partial discharge signal analysis module is responsible for determining the fault characteristic data of the partial discharge signal of the power equipment in different frequency ranges; The frequency range positioning module is responsible for determining the target frequency range of the acoustic partial discharge signal in the target detection area based on the distribution data of the power equipment in the target detection area and the fault characteristic data of the partial discharge signals of different power equipment in different frequency ranges; The acoustic signal processing module is responsible for determining analysis and processing strategies for acoustic partial discharge signals of different power equipment based on analysis and processing results of acoustic partial discharge signals of power equipment within a target frequency range.

[0006] A further technical solution is that the distribution data of the power equipment includes the number of the power equipment and the equipment type of the power equipment.

[0007] A further technical solution is that the fault characteristic data of the partial discharge signal of the electric power equipment in different frequency ranges include amplitude ratios of the partial discharge signal of the electric power equipment in different frequency ranges.

[0008] A further technical solution is that the method for determining the target frequency range of the acoustic partial discharge signal in the target detection area is: Determine the amplitude proportions of the partial discharge signals of different power equipment in different frequency ranges based on the fault characteristic data of the partial discharge signals of different power equipment in the target detection area in different frequency ranges; Determining matching frequency ranges for different power equipment based on the amplitude ratios; Based on the overlap data of matching frequency ranges of different electrical equipment, a target frequency range of the acoustic partial discharge signal in the target detection area is determined.

[0009] A further technical solution is that the matching frequency range is a frequency range whose amplitude ratio is greater than a preset amplitude ratio threshold.

[0010] A further technical solution is that the target frequency range is a frequency range in which different power equipment all fall within a matching frequency range.

[0011] In a second aspect, the present application provides an acoustic partial discharge signal data processing method, which is applied to the above-mentioned acoustic partial discharge signal data processing method, specifically comprising: S1 determines a target frequency range of acoustic partial discharge signals in the target detection area based on distribution data of power equipment in the target detection area and fault characteristic data of partial discharge signals of different power equipment in different frequency ranges; S2: Classify the power equipment in the target detection area into installation equipment and other equipment based on whether the power equipment is installed with a partial discharge monitoring device, and determine the risky installation equipment among the installation equipment based on the analysis data of the partial discharge monitoring device of the installation equipment; S3 uses the fault characteristic signals of different risky installation equipment under the current operating data in different target frequency ranges, and combines the interval between the risky installation equipment and other equipment and the fault characteristic data of other equipment in different target frequency ranges to determine whether there is a target frequency range that meets the monitoring accuracy requirements, and then proceeds to the next step; S4 determines a data processing strategy for acoustic partial discharge signals of different other devices in the target monitoring area based on the analysis results of the acoustic partial discharge signals in the target frequency range whose monitoring accuracy meets the requirements.

[0012] The beneficial effects of the present invention are: Based on the distribution data of the power equipment in the target detection area and the fault characteristic data of the partial discharge signals of different power equipment in different frequency ranges, the target frequency range of the acoustic partial discharge signal in the target detection area is determined. This not only takes into account the differences in the data processing requirements of the acoustic partial discharge signal in the target detection area caused by the differences in the number of power equipment in the target detection area, but also further combines the fault characteristic data of the partial discharge signals of different power equipment in different frequency ranges, thereby realizing the determination of the target frequency range with more obvious fault characteristics, and also laying the foundation for further improving the efficiency of the analysis and processing of partial discharge acoustic signals.

[0013] Based on the analysis results of the acoustic partial discharge signals in the target frequency range where the monitoring accuracy meets the requirements, the data processing strategies for the acoustic partial discharge signals of different other equipment in the target monitoring area are determined, thereby avoiding the influence of installed power equipment with partial discharge signals in certain target frequency ranges. The data processing results of the acoustic partial discharge signals of other equipment in a single certain target frequency range are realized, and the data processing strategies for the acoustic partial discharge signals of different other equipment are determined. This not only improves the efficiency of the data processing of the acoustic partial discharge signals, but also ensures the reliability of the data analysis and processing of other equipment with partial discharge risks.

[0014] A further technical solution is that the method for determining the target frequency range of the acoustic partial discharge signal in the target detection area is: Determine the fault characteristic signals of the partial discharge signals of different power equipment in different frequency ranges based on the fault characteristic data of the partial discharge signals of different power equipment in the target detection area in different frequency ranges; The frequency range in which the similarity coefficients of the fault characteristic signal and the fault characteristic signals of other power equipment are both less than a similarity coefficient threshold is used as the matching frequency range of the power equipment; Based on the overlap data of matching frequency ranges of different electrical equipment, a target frequency range of the acoustic partial discharge signal in the target detection area is determined.

[0015] A further technical solution is to extract and process the acoustic partial discharge signals in the target detection area in all frequency ranges when there is no target frequency range, thereby realizing detection and processing of the power equipment in the target detection area.

[0016] A further technical solution is that the data processing strategy includes performing comparison processing on partial discharge characteristic signals of other devices within different frequency ranges.

[0017] A further technical solution is that the method for determining the data processing strategy of the acoustic partial discharge signals of different other devices in the target monitoring area is: The target frequency range that meets the monitoring accuracy requirement is used as the monitoring frequency range. The similarity coefficients between the acoustic partial discharge signals within different monitoring frequency ranges and the fault characteristic signals of other equipment are determined based on the analytical results of the acoustic partial discharge signals within different monitoring frequency ranges. Determining failure risk coefficients of different other devices based on an average value of the product of a similarity coefficient and a monitoring accuracy rate of the failure characteristic signal of the other devices within different monitoring frequency ranges; Based on the failure risk coefficients of different other devices, a data processing strategy for acoustic partial discharge signals of different other devices in the target monitoring area is determined.

[0018] A further technical solution is to determine a data processing strategy for acoustic partial discharge signals of different other devices in the target monitoring area based on the failure risk coefficients of different other devices, specifically including: When there is no other device with a fault risk coefficient greater than the preset fault risk coefficient threshold, there is no need to process the data of the acoustic partial discharge signals of other devices; When there are other devices with a fault risk coefficient greater than a preset fault risk coefficient threshold, the other devices with a fault risk coefficient greater than the preset fault risk coefficient threshold are regarded as risky power devices. When the number of risky power devices is greater than the preset risky power device number threshold, data processing of acoustic partial discharge signals of the other devices is performed in all frequency ranges. When the number of risky power equipment is not greater than a preset risky power equipment number threshold, the data processing strategy for acoustic partial discharge signals of other equipment is determined based on the sum of the number of risky power equipment and risky installation equipment and the proportion of the number of power equipment in the target detection area.

[0019] Other features and advantages will be described in the following description, and in part will become apparent from the description, or understood by practicing the invention. The purpose and other advantages of the invention are realized and obtained by the structures particularly pointed out in the description and the drawings.

[0020] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, preferred embodiments are given below and described in detail with reference to the accompanying drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] The above and other features and advantages of the present invention will become more apparent by describing in detail exemplary embodiments thereof with reference to the accompanying drawings.

[0022] Figure 1 It is a framework diagram of an acoustic partial discharge signal data processing system; Figure 2is a flow chart of a method for determining a target frequency range of an acoustic partial discharge signal in a target detection area; Figure 3 It is a flow chart of a method for processing acoustic partial discharge signal data; Figure 4 It is a flow chart of a method for determining monitoring accuracy of a target frequency range. DETAILED DESCRIPTION

[0023] Example embodiments will now be described more fully with reference to the accompanying drawings. However, example embodiments can be embodied in many forms and should not be construed as limited to the embodiments set forth herein; rather, these embodiments are provided so that this disclosure will be thorough and complete and will fully convey the concepts of the example embodiments to those skilled in the art. Like reference numerals in the figures represent like or similar structures, and thus their detailed description will be omitted.

[0024] The terms "a", "an", "the", and "said" are used to indicate the presence of one or more elements / components / etc.; the terms "including" and "having" are used to express an open-ended inclusive meaning and mean that additional elements / components / etc. may be present in addition to the listed elements / components / etc.

[0025] Example 1 To solve the above problems, according to one aspect of the present invention, Figure 1 As shown, an acoustic partial discharge signal data processing system is provided, specifically comprising: Power equipment acquisition module, partial discharge signal analysis module, frequency range positioning module, acoustic signal processing module; The power equipment acquisition module is responsible for determining the distribution data of the power equipment in the target detection area; The partial discharge signal analysis module is responsible for determining the fault characteristic data of the partial discharge signal of the power equipment in different frequency ranges; The frequency range positioning module is responsible for determining the target frequency range of the acoustic partial discharge signal in the target detection area based on the distribution data of the power equipment in the target detection area and the fault characteristic data of the partial discharge signals of different power equipment in different frequency ranges; The acoustic signal processing module is responsible for determining analysis and processing strategies for acoustic partial discharge signals of different power equipment based on analysis and processing results of acoustic partial discharge signals of power equipment within a target frequency range.

[0026] Furthermore, the distribution data of the power equipment includes the number of the power equipment and the device type of the power equipment.

[0027] It can be understood that the fault characteristic data of the partial discharge signal of the electric power equipment in different frequency ranges include the amplitude ratios of the partial discharge signal of the electric power equipment in different frequency ranges.

[0028] Specifically, such as Figure 2 As shown, the method for determining the target frequency range of the acoustic partial discharge signal in the target detection area is: Determine the amplitude proportions of the partial discharge signals of different power equipment in different frequency ranges based on the fault characteristic data of the partial discharge signals of different power equipment in the target detection area in different frequency ranges; Determining matching frequency ranges for different power equipment based on the amplitude ratios; Based on the overlap data of matching frequency ranges of different electrical equipment, a target frequency range of the acoustic partial discharge signal in the target detection area is determined.

[0029] Furthermore, the matching frequency range is a frequency range in which the amplitude ratio is greater than a preset amplitude ratio threshold, and in a possible embodiment, is a frequent range in which the amplitude ratio is greater than 0.9.

[0030] It should be noted that the target frequency range is a frequency range within which different power equipment all fall within a matching frequency range.

[0031] Example 2 Second, as Figure 3 As shown, the present application provides an acoustic partial discharge signal data processing method, which is applied to the above-mentioned acoustic partial discharge signal data processing method, specifically comprising: S1 determines a target frequency range of acoustic partial discharge signals in the target detection area based on distribution data of power equipment in the target detection area and fault characteristic data of partial discharge signals of different power equipment in different frequency ranges; S2: Classify the power equipment in the target detection area into installation equipment and other equipment based on whether the power equipment is installed with a partial discharge monitoring device, and determine the risky installation equipment among the installation equipment based on the analysis data of the partial discharge monitoring device of the installation equipment; S3 uses the fault characteristic signals of different risky installation equipment under the current operating data in different target frequency ranges, and combines the interval between the risky installation equipment and other equipment and the fault characteristic data of other equipment in different target frequency ranges to determine whether there is a target frequency range that meets the monitoring accuracy requirements, and then proceeds to the next step; S4 determines a data processing strategy for acoustic partial discharge signals of different other devices in the target monitoring area based on the analysis results of the acoustic partial discharge signals in the target frequency range whose monitoring accuracy meets the requirements.

[0032] Furthermore, the method for determining the target frequency range of the acoustic partial discharge signal in the target detection area is: Determine the fault characteristic signals of the partial discharge signals of different power equipment in different frequency ranges based on the fault characteristic data of the partial discharge signals of different power equipment in the target detection area in different frequency ranges; The frequency range in which the similarity coefficients of the fault characteristic signal and the fault characteristic signals of other power equipment are both less than a similarity coefficient threshold is used as the matching frequency range of the power equipment; Based on the overlap data of matching frequency ranges of different electrical equipment, a target frequency range of the acoustic partial discharge signal in the target detection area is determined.

[0033] Specifically, when there is no target frequency range, the acoustic partial discharge signal in the target detection area is subjected to partial discharge signal extraction processing in all frequency ranges to achieve detection processing of the power equipment in the target detection area.

[0034] Furthermore, when the superposition identification reliability coefficient of the screening target frequency range is within a preset superposition identification reliability coefficient interval, the screening target frequency range is determined to be the target frequency range of the acoustic partial discharge signal in the target detection area.

[0035] Specifically, the risky installation equipment among the installation equipment is an installation equipment having a partial discharge fault according to a monitoring result of a partial discharge monitoring device.

[0036] Specifically, such as Figure 4 As shown, the method for determining the monitoring accuracy of the target frequency range is: Determine the similarity coefficient of the fault characteristic signals between the risky installation equipment and other equipment using the fault characteristic signals of the different risky installation equipment within the target frequency range under the current operating data; Determining a signal interference coefficient of the other device based on a spacing distance between the other device and the risky installation device and a similarity coefficient of the fault characteristic signal; The monitoring accuracy of the target frequency range is determined according to the maximum value of the signal interference coefficient of the other devices at different risk installation devices.

[0037] Furthermore, the monitoring accuracy of the target frequency range is determined based on the difference between a preset value and a maximum value of a signal interference coefficient of other devices installed at different risks.

[0038] It should be noted that the preset value is 1.

[0039] It can be understood that the similarity coefficient of the fault characteristic signal between the risky installation equipment and other equipment is determined based on the deviation of the fault characteristic signal in different dimensions, specifically based on the difference between the preset value and the average value of the deviation of the fault characteristic signal in different dimensions.

[0040] Furthermore, the method for determining the signal interference coefficient is: Determine the interference influence coefficient by multiplying the distance between the other equipment and the risky installation equipment by a preset proportional factor; Based on the ratio of the similarity coefficient to the interference influence coefficient, a signal interference coefficient of the other device is determined.

[0041] Specifically, the fault characteristic signals of the risky installation equipment in different target frequency ranges under current operation data are determined according to historical monitoring results of the fault characteristic signals of the risky installation equipment in the target frequency range under a partial discharge fault state.

[0042] It can be understood that the fault characteristic signal includes a waveform index, a pulse index, a kurtosis index, a margin index, a peak-to-peak value, and a slope.

[0043] Specifically, the monitoring accuracy of the target frequency range ranges from 0 to 1. When the monitoring accuracy of the target frequency range is less than a preset monitoring accuracy threshold, that is, less than 0.85, it is determined that the monitoring accuracy of the target frequency range does not meet the requirements.

[0044] It should be noted that when there is no target frequency range in which the monitoring accuracy meets the requirements, the acoustic partial discharge signal in the target detection area is extracted and processed in all frequency ranges to achieve detection and processing of the power equipment in the target detection area.

[0045] Furthermore, the data processing strategy includes performing comparison processing on partial discharge characteristic signals of other devices within different frequency ranges.

[0046] Specifically, the method for determining the data processing strategy for acoustic partial discharge signals of different other devices in the target monitoring area is: The target frequency range that meets the monitoring accuracy requirement is used as the monitoring frequency range. The similarity coefficients between the acoustic partial discharge signals within different monitoring frequency ranges and the fault characteristic signals of other equipment are determined based on the analytical results of the acoustic partial discharge signals within different monitoring frequency ranges. It can be understood that the similarity coefficient is determined based on the fault characteristic signal using the Euclidean distance function.

[0047] Constructing weight coefficients based on similarity coefficients of the fault characteristic signals of the other devices within different monitoring frequency ranges, and determining fault risk coefficients of different other devices based on the average value of the product of the weight coefficients and the monitoring accuracy; Based on the failure risk coefficients of different other devices, a data processing strategy for acoustic partial discharge signals of different other devices in the target monitoring area is determined.

[0048] Furthermore, based on the failure risk coefficients of different other devices, a data processing strategy for acoustic partial discharge signals of different other devices in the target monitoring area is determined, specifically including: When there is no other device whose failure risk coefficient is greater than a preset failure risk coefficient threshold, in one possible embodiment, greater than 0.6, then there is no need to process the data of the acoustic partial discharge signals of the other devices; When there are other devices with a fault risk coefficient greater than a preset fault risk coefficient threshold, the other devices with a fault risk coefficient greater than the preset fault risk coefficient threshold are regarded as risky power devices. When the number of risky power devices is greater than the preset risky power device number threshold, that is, greater than 2, data processing of acoustic partial discharge signals of the other devices is performed in all frequency ranges; When the number of risky power equipment is not greater than a preset risky power equipment number threshold, the data processing strategy for acoustic partial discharge signals of other equipment is determined based on the sum of the number of risky power equipment and risky installation equipment and the proportion of the number of power equipment in the target detection area.

[0049] It is understandable that the data processing strategy for acoustic partial discharge signals of other devices is determined based on the sum of the number of risky power equipment and risky installation equipment and the proportion of the number of power equipment in the target detection area, specifically including: When the sum of the number of risky power equipment and risky installation equipment accounts for more than a preset device number ratio threshold in the target detection area, that is, greater than 0.7, data processing of acoustic partial discharge signals of other equipment is performed within all frequency ranges; When the sum of the number of risky power equipment and risky installation equipment accounts for no more than a preset equipment number ratio threshold in the target detection area, data processing of acoustic partial discharge signals of risky power equipment is performed only within all frequency ranges, and data processing of acoustic partial discharge signals of other equipment excluding the risky power equipment is determined based on the number of risky power equipment and risky installation equipment of other equipment within the preset range.

[0050] Furthermore, when the sum of the number of risky power equipment and risky installation equipment of other equipment within a preset range is greater than a preset threshold value of the number of interfering equipment, that is, greater than 2, data processing of the acoustic partial discharge signals of other equipment is performed in all frequency ranges; otherwise, data processing of the acoustic partial discharge signals of the other equipment is not required.

[0051] Specifically, data processing of acoustic partial discharge signals of risky power equipment is carried out, including: The similarity between the acoustic partial discharge signal and the fault characteristic signal of the risky power equipment is evaluated in all frequency ranges, and the evaluation results of the similarity between the acoustic partial discharge signal and the fault characteristic signal of the risky power equipment in all frequency ranges are used to determine whether the risky power equipment has partial discharge.

[0052] Furthermore, when the evaluation result of the similarity of the fault characteristic signal of the risky power equipment is that the number of similar frequency ranges is greater than a preset frequency range number threshold, it is determined that partial discharge exists in the risky power equipment.

[0053] It should be noted that, when the similarity coefficient is greater than a preset similarity coefficient threshold, it is determined that the evaluation result of the similarity of the fault characteristic signals of the risky power equipment is similar.

[0054] The various embodiments in this specification are described in a progressive manner. Similar portions between the various embodiments can be referenced to each other, and each embodiment focuses on the differences from the other embodiments. In particular, the device, apparatus, and non-volatile computer storage medium embodiments are generally similar to the method embodiments, so their descriptions are relatively simplified. For relevant details, refer to the descriptions of the method embodiments.

[0055] The foregoing description of this specification describes specific embodiments. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps recited in the claims can be performed in an order different from that described in the embodiments and still achieve the desired results. Furthermore, the processes depicted in the accompanying drawings do not necessarily require the specific order shown or the sequential order to achieve the desired results. In certain embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0056] The foregoing description is merely one or more embodiments of this specification and is not intended to limit this specification. It will be apparent to those skilled in the art that various modifications and variations may be made to one or more embodiments of this specification. Any modifications, equivalent substitutions, or improvements made within the spirit and principles of one or more embodiments of this specification are intended to be within the scope of the claims of this specification.

Claims

1. An acoustic partial discharge signal data processing system, characterized in that: Specifically include: Power equipment acquisition module, partial discharge signal analysis module, frequency range positioning module, acoustic signal processing module; The power equipment acquisition module is responsible for determining the distribution data of the power equipment in the target detection area; The partial discharge signal analysis module is responsible for determining the fault characteristic data of the partial discharge signal of the power equipment in different frequency ranges; The frequency range positioning module is responsible for determining the target frequency range of the acoustic partial discharge signal in the target detection area based on the distribution data of the power equipment in the target detection area and the fault characteristic data of the partial discharge signals of different power equipment in different frequency ranges; The acoustic signal processing module is responsible for determining analysis and processing strategies for acoustic partial discharge signals of different power equipment based on analysis and processing results of acoustic partial discharge signals of power equipment within a target frequency range.

2. The acoustic partial discharge signal data processing system according to claim 1, characterized in that: The distribution data of the electrical devices includes the number of the electrical devices and the device types of the electrical devices.

3. The acoustic partial discharge signal data processing system according to claim 1, characterized in that: The fault characteristic data of the partial discharge signal of the electric power equipment in different frequency ranges include amplitude ratios of the partial discharge signal of the electric power equipment in different frequency ranges.

4. The acoustic partial discharge signal data processing system according to claim 1, characterized in that: The method for determining the target frequency range of the acoustic partial discharge signal in the target detection area is: Determine the amplitude proportions of the partial discharge signals of different power equipment in different frequency ranges based on the fault characteristic data of the partial discharge signals of different power equipment in the target detection area in different frequency ranges; Determining matching frequency ranges for different power equipment based on the amplitude ratios; Based on the overlap data of matching frequency ranges of different electrical equipment, a target frequency range of the acoustic partial discharge signal in the target detection area is determined.

5. The acoustic partial discharge signal data processing system according to claim 4, characterized in that: The target frequency range is a frequency range in which different power equipment all fall within a matching frequency range.

6. A method for processing acoustic partial discharge signal data, applied to the method for processing acoustic partial discharge signal data according to any one of claims 1 to 5, characterized in that: Specifically include: Determining a target frequency range of acoustic partial discharge signals in the target detection area based on distribution data of power equipment in the target detection area and fault characteristic data of partial discharge signals of different power equipment in different frequency ranges; Based on whether the power equipment in the target detection area is equipped with a partial discharge monitoring device, the power equipment is divided into installation equipment and other equipment, and the risky installation equipment among the installation equipment is determined based on the analysis data of the partial discharge monitoring device of the installation equipment; Based on the fault characteristic signals of different risky installation equipment under the current operating data in different target frequency ranges, combined with the interval between the risky installation equipment and other equipment and the fault characteristic data of other equipment in different target frequency ranges, it is determined that there is a target frequency range that meets the monitoring accuracy requirements, and then the next step is entered; Based on the analysis results of the acoustic partial discharge signals in the target frequency range whose monitoring accuracy meets the requirements, a data processing strategy for the acoustic partial discharge signals of different other devices in the target monitoring area is determined.

7. The method for processing acoustic partial discharge signal data according to claim 6, wherein: The risky installation equipment in the installation equipment is an installation equipment in which a monitoring result of a partial discharge monitoring device indicates a partial discharge fault.

8. The method for processing acoustic partial discharge signal data according to claim 6, wherein: The method for determining the monitoring accuracy of the target frequency range is: Determine the similarity coefficient of the fault characteristic signals between the risky installation equipment and other equipment using the fault characteristic signals of the different risky installation equipment within the target frequency range under the current operating data; Determining a signal interference coefficient of the other device based on a spacing distance between the other device and the risky installation device and a similarity coefficient of the fault characteristic signal; The monitoring accuracy of the target frequency range is determined according to the maximum value of the signal interference coefficient of the other devices at different risk installation devices.

9. The method for processing acoustic partial discharge signal data according to claim 6, wherein: The method for determining the data processing strategy for acoustic partial discharge signals of different other devices in the target monitoring area is as follows: The target frequency range that meets the monitoring accuracy requirement is used as the monitoring frequency range. The similarity coefficients between the acoustic partial discharge signals within different monitoring frequency ranges and the fault characteristic signals of other equipment are determined based on the analytical results of the acoustic partial discharge signals within different monitoring frequency ranges. Determining failure risk coefficients of different other devices based on an average value of the product of a similarity coefficient and a monitoring accuracy rate of the failure characteristic signal of the other devices within different monitoring frequency ranges; Based on the failure risk coefficients of different other devices, a data processing strategy for acoustic partial discharge signals of different other devices in the target monitoring area is determined.

10. The method for processing acoustic partial discharge signal data according to claim 9, wherein: Determining a data processing strategy for acoustic partial discharge signals of different other devices in the target monitoring area based on the failure risk coefficients of different other devices, specifically including: When there is no other device with a fault risk coefficient greater than the preset fault risk coefficient threshold, there is no need to process the data of the acoustic partial discharge signals of other devices; When there are other devices with a fault risk coefficient greater than a preset fault risk coefficient threshold, the other devices with a fault risk coefficient greater than the preset fault risk coefficient threshold are regarded as risky power devices. When the number of risky power devices is greater than the preset risky power device number threshold, data processing of acoustic partial discharge signals of the other devices is performed in all frequency ranges. When the number of risky power equipment is not greater than a preset risky power equipment number threshold, the data processing strategy for acoustic partial discharge signals of other equipment is determined based on the sum of the number of risky power equipment and risky installation equipment and the proportion of the number of power equipment in the target detection area.

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