A method and apparatus for partial discharge signal separation

Abstract

The application discloses a partial discharge signal separation method and device. The method determines a signal waveform fitting degree characteristic value according to minimum Euclidean distances of a to-be-processed waveform sequence and a sample waveform sequence; determines a signal frequency spectrum fitting degree characteristic value according to minimum Euclidean distances of a to-be-processed frequency spectrum sequence and a sample frequency spectrum sequence; and based on the signal waveform fitting degree characteristic value and the signal frequency spectrum fitting degree characteristic value, multiple signals in partial discharge detection can be effectively separated, and the problem that it is difficult to accurately extract a real discharge signal when multiple similar signals exist is solved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of high-voltage power, in particular to a partial discharge signal separation method and device. BACKGROUND

[0002] The partial discharge of insulation equipment in high-voltage power equipment is a precursor and manifestation of the degradation of insulation equipment. Long-term partial discharge can cause insulation aging, trigger abnormal operation of power insulation equipment, and further cause power system failure. Therefore, during the operation of the insulation equipment, it is necessary to monitor the partial discharge in real time to prevent potential power equipment operation accidents.

[0003] When carrying out partial discharge detection on high-voltage equipment, various kinds of interference and noise signals will be encountered, such as periodic interference, pulse interference, and white noise interference, which will have a great impact on the detection of partial discharge. In some cases, the real partial discharge signal will be submerged in the noise on the scene. Therefore, in order to identify the real discharge signal, various signal separation methods such as equivalent time-frequency method, time-frequency entropy method, and pulse amplitude parameter method are successfully applied to partial discharge measurement.

[0004] However, these signal separation methods are somewhat "extensive" in actual use in some cases, and the actual separation effect is limited for multiple signals that are relatively similar. SUMMARY

[0005] The purpose of the present application is to provide a partial discharge signal separation method and device which can improve the above problems.

[0006] Embodiments of the present application are implemented as follows:

[0007] In a first aspect, the present application provides a partial discharge signal separation method, which comprises:

[0008] S1: obtaining the synchronization signal and the partial discharge signal simultaneously collected by the partial discharge detector in a target time period, and calculating a sample waveform sequence of a target abscissa length according to the synchronization signal and the partial discharge signal and a sample spectrum sequence

[0009] S2: obtaining at least two to-be-processed signals collected by the partial discharge detector after the target time period, taking the target abscissa length with different abscissa starting points as a target abscissa range, and extracting at least two to-be-processed waveform sequences of the to-be-processed signals from the target abscissa range;

[0010] S3: calculating signal waveform fitting degree characteristic values and spectrum fitting degree characteristic values according to the at least two to-be-processed waveform sequences;

[0011] S4: generating a two-dimensional signal separation spectrum map with the signal waveform fitting degree characteristic value and the spectrum fitting degree characteristic value as coordinates, circling a signal concentration area from the two-dimensional signal separation spectrum map, and generating a corresponding target Q-φ two-dimensional spectrum map.

[0012] Wherein, S1, S2, etc. are only step identifiers, and the execution order of the method does not necessarily follow the order from small to large, such as executing step S2 first and then executing step S1. The present application does not make any limitation.

[0013] The present application discloses a partial discharge signal separation method, which determines a signal waveform fitting degree characteristic value according to the minimum Euclidean distance of a to-be-processed waveform sequence and a sample waveform sequence; determines a signal spectrum fitting degree characteristic value according to the minimum Euclidean distance of a to-be-processed spectrum sequence and a sample spectrum sequence; and based on the signal waveform fitting degree characteristic value and the signal spectrum fitting degree characteristic value, can effectively separate multiple signals in partial discharge detection, and especially solves the problem of difficult accurate extraction of the real discharge signal in the presence of multiple similar signals.

[0014] The present application proposes a new signal separation method based on waveform and spectrum fitting degree, which will have a more "fine" actual application effect, especially for multiple similar signals, the separation effect will be better, which will help to separate and identify the real discharge signal from numerous interference and noise signals in a complex test environment. This will help the detection personnel to find the real discharge signal from the complex on-site test environment, thereby increasing the accuracy of partial discharge signal identification, reducing the risk of missed detection and misjudgment of partial discharge signals, and further timely and accurately finding and solving the safety hazards existing in high-voltage equipment, and further improving the safe operation of high-voltage equipment in the power system.

[0015] The present application separates the signals by the method based on the signal waveform and spectrum fitting degree,

[0016] In an optional embodiment of the present application, the step S1 comprises:

[0017] S11: acquiring a synchronization signal and a partial discharge signal simultaneously collected by a partial discharge detector in a target time period, and generating a Q-φ real-time two-dimensional spectrum map;

[0018] S12: selecting a signal with the largest discharge quantity absolute value from the synchronization signal and the partial discharge signal as a sample signal;

[0019] S13: and extracting a target waveform sequence S0(t) of the sample signal according to a preset abscissa range;

[0020] S14: performing change processing on the target waveform sequence S0(t) to obtain a sample waveform sequence and a sample spectrum sequence

[0021] It can be understood that, for the selected sample signal, the waveform peak position p is found, the target waveform sequence S0(t) of the preset abscissa range [p-p1, p+p2] is intercepted, and the sequence length is p1+p2+1.

[0022] In an optional embodiment of the present application, the step S14 comprises:

[0023] S141: performing Fourier transform on the target waveform sequence S0(t) to obtain a target spectrum sequence S0(w);

[0024] S142: performing normalization processing on the target waveform sequence S0(t) and the target spectrum sequence S0(w) to obtain a sample waveform sequence and a sample spectrum sequence

[0025] In an optional embodiment of the present application, the step S142 comprises: performing normalization processing on the target waveform sequence S0(t) and the target spectrum sequence S0(w) according to the following formula:

[0026]

[0027] Wherein, t0 is the maximum discharge amount absolute value in the target waveform sequence S0(t), and w0 is the maximum discharge amount absolute value in the target waveform sequence S0(w).

[0028] In an optional embodiment of the present application, the target abscissa length is consistent with the abscissa length of the preset abscissa range, and the abscissa starting point of at least one target abscissa range is consistent with the abscissa starting point of the preset abscissa range.

[0029] In an optional embodiment of the present application, in the step S2, the target abscissa length with different abscissa starting points as the target abscissa range comprises: taking the abscissa starting point of the preset abscissa range as a standard starting point; and taking the target abscissa length of each abscissa point after the standard starting point as each target abscissa range.

[0030] It can be understood that, for the signal S x (t) obtained from the partial discharge detector, the starting point is from p-p1-L to p+p1+L, the step is 1, the waveform sequence with the length of p1+p2+1 is intercepted, and there are 2L+1 waveform sequences, which are taken as the waveform sequence of the signal

[0031] The step S3 comprises:

[0032] S31: performing weighted scaling processing on the to-be-processed waveform sequence to obtain a minimum Euclidean distance between the to-be-processed waveform sequence and the sample waveform sequence

[0033] S32: selecting, as a signal waveform fitting degree characteristic value, the minimum Euclidean distance between the to-be-processed waveform sequence corresponding to the signal waveform fitting degree characteristic value and the sample waveform sequence

[0034] S33: performing Fourier transform on the to-be-processed waveform sequence corresponding to the signal waveform fitting degree characteristic value to obtain a to-be-processed frequency spectrum sequence

[0035] S34: performing weighted scaling processing on the to-be-processed frequency spectrum sequence to obtain a minimum Euclidean distance between the to-be-processed frequency spectrum sequence and the sample frequency spectrum sequence as a signal frequency spectrum fitting degree characteristic value

[0036] In an optional embodiment of the present application, the step S31 comprises:

[0037] The Euclidean distance between the to-be-processed waveform sequence after the weighted scaling processing and the sample waveform sequence is calculated by the following formula:

[0038]

[0039] wherein, is the sample waveform sequence, is the to-be-processed waveform sequence, and k is a weighting value;

[0040] When p1+p2+1 is the length of the to-be-processed waveform sequence, the minimum Euclidean distance is obtained;

[0041]

[0042] In a second aspect, the present application provides a method for separating partial discharge signals, which comprises a processor and a memory connected to each other, wherein the memory is used for storing a computer program, the computer program comprises program instructions, and the processor is configured to invoke the program instructions to execute the method according to any one of the first aspect.

[0043] In a third aspect, the present application further provides a computer readable storage medium, which stores a computer program, the computer program comprises program instructions, and the program instructions, when executed by a processor, cause the processor to execute the method according to any one of the first aspect.

[0044] Advantages:

[0045] ​​​​​The application discloses a partial discharge signal separation method, determines a signal waveform fitting degree characteristic value according to minimum Euclidean distances of a to-be-processed waveform sequence and a sample waveform sequence, determines a signal spectrum fitting degree characteristic value according to minimum Euclidean distances of a to-be-processed frequency spectrum sequence and a sample frequency spectrum sequence, and can effectively separate multiple signals in partial discharge detection based on the signal waveform fitting degree characteristic value and the signal spectrum fitting degree characteristic value, especially solves the problem that it is difficult to accurately extract a real discharge signal in the case that multiple similar signals exist.

[0046] The application provides a new signal separation method based on waveform and spectrum fitting degree, the actual application effect of the separation method will be more "fine", especially for multiple similar signals, the separation effect is better, which will help to separate and identify the real discharge signal from numerous interference and noise signals in a complex test environment. This will help the detection personnel to find the real discharge signal from the complex on-site test environment, thereby increasing the accuracy of partial discharge signal identification, reducing the risk of missed detection and misjudgment of partial discharge signals, and further finding and solving the safety hazards existing in high-voltage equipment in time, and further improving the safe operation of high-voltage equipment in the power system.

[0047] In order to make the above-mentioned purposes, features and advantages of the application more obvious and easy to understand, the following optional embodiments are described in detail below, and the accompanying drawings are described as follows. BRIEF DESCRIPTION OF DRAWINGS

[0048] In order to more clearly illustrate the technical solutions of the embodiments of the application, the following will briefly introduce the drawings needed to be used in the embodiments, and it should be understood that the following drawings only show some embodiments of the application, and therefore should not be regarded as a limitation to the scope, and for those skilled in the art, other related drawings can also be obtained without creative labor on the basis of these drawings.

[0049] Figure 1 is a flowchart of a partial discharge signal separation method provided by the application;

[0050] Figure 2 is a Q-φ real-time two-dimensional spectrum diagram generated according to signals collected by a partial discharge detector in a target time period;

[0051] Figure 3 is a waveform diagram of a sample signal;

[0052] Figure 4 is a schematic diagram of a target waveform sequence of a sample signal;

[0053] Figure 5 is a target Q-φ two-dimensional spectrum diagram obtained by processing the partial discharge signal separation method. Detailed Implementation

[0054] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of this application.

[0055] Firstly, such as Figure 1 As shown, this application provides a method for separating partial discharge signals, which includes:

[0056] S1: Acquire the synchronization signal and partial discharge signal simultaneously collected by the partial discharge detector within the target time period, and calculate the sample waveform sequence with the target horizontal coordinate length based on the synchronization signal and partial discharge signal. and sample spectrum sequence

[0057] In an optional embodiment of this application, step S1 includes:

[0058] S11: Acquire the synchronization signal and partial discharge signal simultaneously collected by the partial discharge detector within the target time period, and generate a real-time two-dimensional Q-φ spectrum, such as... Figure 2 As shown.

[0059] S12: Select the signal with the largest absolute value of discharge from the synchronization signal and the partial discharge signal as the sample signal, such as... Figure 3 As shown.

[0060] S13: Extract the target waveform sequence S0(t) of the sample signal according to the preset horizontal coordinate range, such as Figure 4 As shown.

[0061] It can be understood that, for the selected sample signal, the peak position p of the waveform is found, and the target waveform sequence S0(t) within the preset horizontal coordinate range of [p-p1, p+p2] is extracted, with a sequence length of p1+p2+1.

[0062] S14: The target waveform sequence S0(t) is transformed to obtain the sample waveform sequence. and sample spectrum sequence

[0063] S2: Acquire at least two signals to be processed by the partial discharge detector after the target time period, and use the target horizontal coordinate length with different horizontal coordinate starting points as the target horizontal coordinate range, and extract at least two waveform sequences of the signals to be processed from the target horizontal coordinate range.

[0064] In an optional embodiment of the present application, the target abscissa length is consistent with the abscissa length of the preset abscissa range, and the abscissa starting point of the at least one target abscissa range is consistent with the abscissa starting point of the preset abscissa range.

[0065] In an optional embodiment of the present application, in step S2, the target abscissa length with different abscissa starting points is taken as the target abscissa range, which comprises: taking the abscissa starting point of the preset abscissa range as a standard starting point; and taking the target abscissa length of each abscissa point after the standard starting point as each target abscissa range.

[0066] It can be understood that, for the to-be-processed signal S x (t) obtained from the partial discharge detector, the starting point is from p-p1-L to p+p1+L, the step is 1, the waveform sequence with the length of p1+p2+1 is intercepted, and a total of 2L+1 waveform sequences are taken as the waveform sequence of the signal

[0067] S3: calculating a signal waveform fitting degree characteristic value and a frequency spectrum fitting degree characteristic value according to the at least two to-be-processed waveform sequences.

[0068] Step S3 comprises:

[0069] S31: performing weighted scaling processing on the to-be-processed waveform sequence to obtain the minimum Euclidean distance between the to-be-processed waveform sequence and the sample waveform sequence .

[0070] S32: screening out the minimum Euclidean distance as the signal waveform fitting degree characteristic value.

[0071] S33: performing Fourier transform on the to-be-processed waveform sequence corresponding to the signal waveform fitting degree characteristic value to obtain a to-be-processed frequency spectrum sequence.

[0072] S34: performing weighted scaling processing on the to-be-processed frequency spectrum sequence to obtain the minimum Euclidean distance between the to-be-processed frequency spectrum sequence and the sample frequency spectrum sequence as the signal frequency spectrum fitting degree characteristic value.

[0073] S4: generating a two-dimensional signal separation spectrum diagram with the signal waveform fitting degree characteristic value and the frequency spectrum fitting degree characteristic value as coordinates, circling a signal concentrated area from the two-dimensional signal separation spectrum diagram, and generating a corresponding target Q-φ two-dimensional spectrum diagram, as shown in Figure 5 .

[0074] In the present application, the execution order of the method is not necessarily in the order from small to large according to the numbers, for example, step S2 can be executed first and then step S1, which is not limited in the present application.

[0075] The application discloses a partial discharge signal separation method, determines a signal waveform fitting degree characteristic value according to minimum Euclidean distances of a to-be-processed waveform sequence and a sample waveform sequence, determines a signal spectrum fitting degree characteristic value according to minimum Euclidean distances of a to-be-processed frequency spectrum sequence and a sample frequency spectrum sequence, and can effectively separate multiple signals in partial discharge detection based on the signal waveform fitting degree characteristic value and the signal spectrum fitting degree characteristic value, thereby solving the problem that it is difficult to accurately extract a real discharge signal in the case that multiple similar signals exist.

[0076] The application provides a new signal separation method based on waveform and spectrum fitting degree, the actual application effect of the separation method will be more "fine", especially for multiple similar signals, the separation effect is better, which will help to separate and identify the real discharge signal from numerous interference and noise signals in a complex test environment. This will help the detection personnel to find the real discharge signal from the complex on-site test environment, thereby increasing the accuracy of partial discharge signal identification, reducing the risk of missed detection and misjudgment of partial discharge signals, and further timely and accurately finding and solving the safety hazards existing in high-voltage equipment, and further improving the safe operation of high-voltage equipment in the power system.

[0077] The application separates the signals by the method based on the signal waveform and spectrum fitting degree,

[0078] In the optional embodiment of the application, step S14 comprises:

[0079] S141: performing Fourier transform on the target waveform sequence S0(t) to obtain a target frequency spectrum sequence S0(w);

[0080] S142: performing normalization processing on the target waveform sequence S0(t) and the target frequency spectrum sequence S0(w) to obtain a sample waveform sequence and a sample frequency spectrum sequence

[0081] In the optional embodiment of the application, step S142 comprises: performing normalization processing on the target waveform sequence S0(t) and the target frequency spectrum sequence S0(w) according to the following formula:

[0082]

[0083] Wherein, t0 is the maximum discharge value in the target waveform sequence S0(t), and w0 is the maximum discharge value in the target frequency spectrum sequence S0(w).

[0084] In the optional embodiment of the application, step S31 comprises:

[0085] The to-be-processed waveform sequence and the sample waveform sequence after the weighted scaling processing are calculated by the following formula Euclidean distance:

[0086]

[0087] in, For the sample waveform sequence, Here is the waveform sequence to be processed, and k is the weighting value;

[0088] exist When the minimum Euclidean distance is found, the minimum Euclidean distance is obtained.

[0089] Where p1+p2+1 is the length of the waveform sequence to be processed.

[0090] Secondly, this application provides an apparatus for separating partial discharge signals. The apparatus for separating partial discharge signals includes one or more processors and a memory. The processor, input device, output device, and memory are connected via a bus. The memory stores a computer program, which includes program instructions, and the processor executes the program instructions stored in the memory. The processor is configured to invoke the program instructions to perform the operation of any method of the first aspect.

[0091] It should be understood that, in the embodiments of this application, the processor may be a Central Processing Unit (CPU), but it may also be other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor may be a microprocessor or any conventional processor.

[0092] The memory may include read-only memory and random access memory, and provides instructions and data to the processor. A portion of the memory may also include non-volatile random access memory. For example, the memory may also store information about the device type.

[0093] In specific implementations, the processor, input device, and output device described in the embodiments of this application can execute the implementation method described in any of the methods in the first aspect, or they can execute the implementation method of the terminal device described in the embodiments of this application, which will not be repeated here.

[0094] In a third aspect, the present application provides a computer readable storage medium, which stores a computer program. The computer program comprises program instructions. When the program instructions are executed by a processor, the steps of any method of the first aspect are implemented.

[0095] The computer readable storage medium can be an internal storage unit of the terminal device, for example, a hard disk or a memory of the terminal device. The computer readable storage medium can also be an external storage device of the terminal device, for example, a plug-in hard disk, a smart media card (SMC), a secure digital (SD) card, a flash card, etc. equipped on the terminal device. Further, the computer readable storage medium can include both the internal storage unit and the external storage device of the terminal device. The computer readable storage medium is used to store the computer program and other programs and data required by the terminal device. The computer readable storage medium can also be used to temporarily store data that has been output or will be output.

[0096] Those skilled in the art can realize that the units and algorithm steps of each example described in combination with the embodiments disclosed herein can be realized in electronic hardware, computer software or a combination of both. In order to clearly illustrate the interchangeability of hardware and software, the components and steps of each example have been described in general terms in the above description. Whether the functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. A person skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of the present application.

[0097] In several embodiments provided in the present application, it should be understood that the disclosed terminal device and method can be implemented in other ways. For example, the above-described device embodiments are only schematic, for example, the division of the above-mentioned units is only a logical function division, and actual implementation can have another division manner, for example, a plurality of units or components can be combined or integrated into another system, or some features can be ignored or not executed. In addition, the coupling or direct coupling or communication connection between the units or components shown or discussed can be indirect coupling or communication connection through some interfaces, devices or units, and can also be electrical, mechanical or other forms of connection.

[0098] The units described as separate components above can or can not be physically separate, and the components shown as units can or can not be physical units, i.e., can be located in one place, or can be distributed to multiple network units. Part or all of the units can be selected according to actual needs to achieve the purpose of the embodiments of the present application.

[0099] In addition, each functional unit in each embodiment of the present application can be integrated in one processing unit, or each unit can exist physically, or two or more units can be integrated in one unit. The integrated unit can be realized in the form of hardware or in the form of a software functional unit.

[0100] The integrated unit, if realized in the form of a software functional unit and sold or used as an independent product, can be stored in a computer readable storage medium. Based on this understanding, the technical solutions of the present application essentially or the part of the prior art that contributes to the technical solutions, or all or part of the technical solutions can be embodied in the form of a software product. The computer software product is stored in a storage medium, and includes a number of instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods in the various embodiments of the present application. The foregoing storage medium includes: a U disk, a mobile hard disk, a read-only memory (ROM, Read-Only Memory), a random access memory (RAM, Random Access Memory), a magnetic disk or an optical disk, and various program code storage media.

[0101] The expressions "first", "second", "the first" or "the second" used in various embodiments of the present disclosure can modify various components regardless of order and / or importance, but these expressions do not limit the corresponding components. The above expressions are only configured for the purpose of distinguishing the elements from other elements. For example, the first user equipment and the second user equipment represent different user equipment, although both are user equipment. For example, the first element can be referred to as the second element, and similarly, the second element can be referred to as the first element without departing from the scope of the present disclosure.

[0102] When an element (e.g., a first element) is referred to as being “(operatively or communicatively) coupled with” or “(operatively or communicatively) coupled to” or “connected to” another element (e.g., a second element), it should be understood that the one element is either directly connected to the other element or that one element is indirectly connected to the other element through yet another element (e.g., a third element). Conversely, when an element (e.g., a first element) is referred to as being “directly connected” or “directly coupled” to another element (a second element), then no element (e.g., a third element) is interposed between them.

[0103] It has to be noted that, as used herein, the terms “includes,” “including,” “has,” “having” or the like are intended to be open-ended: namely, the foregoing terms are intended to mean that the processes, methods, articles, or apparatuses disclosed herein include, but are not limited to, those stated items, and that any items including, but not limited to, those stated items are also contemplated. Further, the terms “comprises”, “comprising”, “comcluded”, “including”, or the like are to be construed as meaning “including, but not limited to”, unless otherwise indicated.

[0104] The above description is only optional embodiments of the present application and the explanation of the principles of the applied technology. It should be understood by those skilled in the art that the scope of the invention involved in the present application is not limited to the technical solutions formed by the specific combinations of the above technical features, and should also cover other technical solutions formed by the combinations of the above technical features or their equivalent features without departing from the above inventive concept. For example, the technical solutions formed by the mutual replacement of the above features and the technical features disclosed in the present application (but not limited to) having similar functions.

[0105] Depending on the context, the word “if’ as used herein can be interpreted to mean “when” or “while” or “in response to determining” or “in response to detecting.” Similarly, depending on the context, the phrase “if it is determined” or “if it is detected (a stated condition or event)” can be interpreted to mean “upon determining” or “in response to determining” or “upon detecting (the stated condition or event)” or “in response to detecting (the stated condition or event).”

[0106] The above description is merely exemplary of optional embodiments and the principles of the application. It is not intended to limit the scope of the application to the described technical solutions. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the application shall be included in the scope of protection of the application.

[0107] The above description is merely exemplary of optional embodiments and the principles of the application. It is not intended to limit the scope of the application to the described technical solutions. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the application shall be included in the scope of protection of the application.

Claims

1. A method of partial discharge signal separation, characterized by, The method comprises the steps of: S1: Obtain the synchronization signal and the partial discharge signal simultaneously collected by the partial discharge detector in a target time period, and screen and calculate a sample waveform sequence of a target abscissa length according to the synchronization signal and the partial discharge signal and a sample spectrum sequence ; S2: obtaining at least two to-be-processed signals collected by the partial discharge detector after the target time period, taking the target horizontal coordinate length with different horizontal coordinate starting points as a target horizontal coordinate range, and extracting at least two to-be-processed waveform sequences of the to-be-processed signals from the target horizontal coordinate range; S3: calculating a signal waveform fitting degree characteristic value and a frequency spectrum fitting degree characteristic value according to the at least two to-be-processed waveform sequences; S4: taking the signal waveform fitting degree characteristic value and the frequency spectrum fitting degree characteristic value as coordinates, generating a two-dimensional signal separation spectrum, circling a signal concentration area from the two-dimensional signal separation spectrum, and generating a corresponding target two-dimensional spectrum The step S1 comprises: S11: Obtain the synchronization signal and the partial discharge signal simultaneously collected by the partial discharge detector in the target time period, and generate a real-time two-dimensional spectrum; S12: selecting a signal with the maximum discharge amount absolute value from the synchronization signal and the partial discharge signal as a sample signal; S13: According to the preset horizontal coordinate range, a target waveform sequence of the sample signal is extracted ; S14: a target waveform sequence obtained by performing a change process on the target waveform sequence and a sample spectrum sequence ; The step S3 comprises: S31: performing weighted scaling processing on the to-be-processed waveform sequence, to obtain the to-be-processed waveform sequence and the sample waveform sequence of the minimum Euclidean distance; S32: screening out the minimum Euclidean distance minimum as a signal waveform fitting degree characteristic value; S33: performing Fourier transform on the to-be-processed waveform sequence corresponding to the signal waveform fitting degree characteristic value to obtain a to-be-processed frequency spectrum sequence; S34: weighting and scaling processing on the to-be-processed spectrum sequence, to obtain the to-be-processed spectrum sequence and the sample spectrum sequence the minimum Euclidean distance of the to-be-processed spectrum sequence and the sample spectrum sequence as a signal spectrum fitting degree characteristic value.

2. The method of partial discharge signal separation according to claim 1, characterized in that, The step S14 comprises: S141: Fourier transforming the target waveform sequence to obtain a target frequency spectrum sequence ; S142: normalizing the target waveform sequence and the target spectrum sequence to obtain a sample waveform sequence and a sample spectrum sequence .

3. The method for separating partial discharge signals according to claim 2, characterized in that, The step S142 includes: performing normalization processing on the target waveform sequence and the target spectrum sequence according to the following formula: and the target spectrum sequence ​ ； wherein, is the target waveform sequence is the maximum absolute value of the discharge amount in the target waveform sequence is the target waveform sequence is the maximum absolute value of the discharge amount in the target waveform sequence 4. The method for separating partial discharge signals according to claim 1, characterized in that, The target horizontal coordinate length is consistent with the horizontal coordinate length of the preset horizontal coordinate range, and the horizontal coordinate starting point of at least one target horizontal coordinate range is consistent with the horizontal coordinate starting point of the preset horizontal coordinate range.

5. The method for separating partial discharge signals according to claim 4, characterized in that, In the step S2, the target horizontal coordinate length with different horizontal coordinate starting points is taken as a target horizontal coordinate range, which comprises: taking the horizontal coordinate starting point of the preset horizontal coordinate range as a standard starting point; taking the target horizontal coordinate length of each horizontal coordinate point after the standard starting point as each target horizontal coordinate range.

6. The method for separating partial discharge signals according to claim 1, characterized in that, The step S31 comprises: The weighted scaling processed said to-be-processed waveform sequence and the sample waveform sequence are calculated by the following formula: The Euclidean distance of ； wherein, is the sample waveform sequence, is the waveform sequence to be processed, is a weighting value; In The minimum Euclidean distance is obtained when wherein, is the length of the sequence of waveforms to be processed.

7. A device for separating partial discharge signals, characterized in that, The device comprises a processor and a memory connected to each other, wherein the memory is used to store a computer program, the computer program comprises program instructions, and the processor is configured to invoke the program instructions to execute the method according to any one of claims 1 to 6.

8. A computer readable storage medium, characterized in that, The computer storage medium stores a computer program, the computer program comprises program instructions, and the program instructions make the processor execute the method according to any one of claims 1 to 6 when executed by the processor.

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