Transformer winding fault diagnosis method and device, medium and equipment

Abstract

The invention discloses a transformer winding fault diagnosis method and device, a medium and equipment, the frequency response amplitude of a transformer winding is obtained on a test platform, and the mode of signal injection of a high-voltage side and a medium-voltage side and signal acquisition of a low-voltage side is specifically adopted. And calculating the variance of the frequency response amplitude and obtaining the fault weight based on the variance. And finally calculating a winding fault judgment factor by preprocessing the data and combining a fault weight. When the factor exceeds a preset threshold, it can be determined that the transformer winding has a fault. According to the method, the health condition of the transformer winding can be continuously monitored, and by calculating and diagnosing the winding fault in time, potential problems can be found as early as possible, sudden faults are avoided, and the stability and reliability of a power system are guaranteed.

Description

Technical Field

[0001] The present invention relates to the technical field of transformer winding fault diagnosis, and in particular to a transformer winding fault diagnosis method, device, medium and equipment. Background Art

[0002] Transformers are essential key equipment in power systems. They play a central role in voltage conversion, power transmission, and power distribution. Transformers are essential to maintaining the stability and reliability of power grids due to their ability to efficiently convert power between different voltage levels. However, transformer failures not only seriously affect the continuity of power supply, but may also trigger a chain reaction, leading to more extensive power system failures, resulting in huge economic losses and social impacts. Among the many types of transformer failures, winding failures dominate. These failures usually stem from problems such as degradation of the insulation material, mechanical damage, or thermal stress of the windings. Over time, the windings may gradually age due to long-term exposure to electric and magnetic fields, resulting in a decrease in insulation performance. Once a winding failure occurs, such as a turn-to-turn short circuit or ground fault, the operating efficiency and safety of the transformer will be seriously threatened. Therefore, continuous monitoring and timely diagnosis of the health of transformer windings are of great significance for preventing major power accidents and ensuring the safe operation of the power grid. Summary of the invention

[0003] Based on this, it is necessary to provide a transformer winding fault diagnosis method, device, medium and equipment to solve the problem of being unable to continuously monitor and timely diagnose the health status of the transformer winding.

[0004] A transformer winding fault diagnosis method is applied to a test platform, the method comprising:

[0005] Acquire multiple first frequency response amplitudes and multiple second frequency response amplitudes; wherein the first frequency response amplitude is the amplitude of the frequency response curve determined when a signal is injected into the high-voltage side bushing of the test platform and a signal is collected from the low-voltage side bushing, and the second frequency response amplitude is the amplitude of the frequency response curve determined when a signal is injected into the medium-voltage side bushing of the test platform and a signal is collected from the low-voltage side bushing;

[0006] Calculating the variance of the plurality of first frequency response amplitudes to obtain a first variance, and calculating the variance of the plurality of second frequency response amplitudes to obtain a second variance;

[0007] Calculating a fault weight according to the first variance to obtain a first fault weight, and calculating a fault weight according to the second variance to obtain a second fault weight;

[0008] Preprocessing the plurality of first frequency response amplitudes to obtain a first preprocessing result, and preprocessing the plurality of second frequency response amplitudes to obtain a second preprocessing result;

[0009] A winding fault judgment factor is calculated according to the first fault weight, the second fault weight, the first preprocessing result and the second preprocessing result. If the winding fault judgment factor is greater than or equal to a preset fault threshold, it is determined that a transformer winding has a fault.

[0010] In one embodiment, the variance of the plurality of first frequency response amplitudes is calculated to obtain a first variance expression as:

[0011]

[0012] In the above formula, Var H is the first variance; r H_n is the amplitude of the nth first frequency response after normalization; μ H is the average value of the plurality of first frequency response amplitudes; a m is the nth first frequency response amplitude, and N is the total number of frequency response amplitudes;

[0013] The variance of the plurality of second frequency response amplitudes is calculated to obtain a second variance expression as follows:

[0014]

[0015] In the above formula, Var M is the second variance; r M_n is the amplitude of the nth second frequency response after normalization; μ M is the average value of the plurality of second frequency response amplitudes; b n is the nth second frequency response amplitude.

[0016] In one embodiment, the fault weight is calculated according to the first variance to obtain a first fault weight expressed as:

[0017]

[0018] In the above formula, w H is the first fault weight;

[0019] The fault weight is calculated according to the second variance to obtain the second fault weight expressed as:

[0020]

[0021] In the above formula, w M is the second fault weight.

[0022] In one embodiment, the preprocessing of the plurality of first frequency response amplitudes to obtain a first preprocessing result is expressed as:

[0023]

[0024] In the above formula, Y H_n is the first preprocessing result of the nth first frequency response amplitude;

[0025] The preprocessing of the plurality of second frequency response amplitudes to obtain a second preprocessing result is expressed as:

[0026]

[0027] In the above formula, Y M_n is the second preprocessing result of the nth second frequency response amplitude.

[0028] In one embodiment, the winding fault judgment factor calculated according to the first fault weight, the second fault weight, the first preprocessing result and the second preprocessing result is expressed as:

[0029]

[0030] In the above formula, β is the winding fault judgment factor.

[0031] A transformer winding fault diagnosis device, the transformer winding fault diagnosis device comprising:

[0032] An acquisition module, used to acquire multiple first frequency response amplitudes and multiple second frequency response amplitudes; wherein the first frequency response amplitude is the amplitude of the frequency response curve determined when a signal is injected into the high-voltage side bushing of the test platform and a signal is collected from the low-voltage side bushing, and the second frequency response amplitude is the amplitude of the frequency response curve determined when a signal is injected into the medium-voltage side bushing of the test platform and a signal is collected from the low-voltage side bushing;

[0033] A variance calculation module, configured to calculate the variance of the plurality of first frequency response amplitudes to obtain a first variance, and calculate the variance of the plurality of second frequency response amplitudes to obtain a second variance;

[0034] a fault weight calculation module, configured to calculate the fault weight according to the first variance to obtain a first fault weight, and to calculate the fault weight according to the second variance to obtain a second fault weight;

[0035] A preprocessing module, configured to preprocess the plurality of first frequency response amplitudes to obtain a first preprocessing result, and preprocess the plurality of second frequency response amplitudes to obtain a second preprocessing result;

[0036] A fault judgment module is used to calculate a winding fault judgment factor according to the first fault weight, the second fault weight, the first preprocessing result and the second preprocessing result. If the winding fault judgment factor is greater than or equal to a preset fault threshold, it is determined that there is a fault in the transformer winding.

[0037] In one embodiment, the variance of the plurality of first frequency response amplitudes is calculated to obtain a first variance expression as:

[0038]

[0039] In the above formula, Var H is the first variance; r H_n is the amplitude of the nth first frequency response after normalization; μ H is the average value of the plurality of first frequency response amplitudes; a n is the nth first frequency response amplitude, and N is the total number of frequency response amplitudes;

[0040] The variance of the plurality of second frequency response amplitudes is calculated to obtain a second variance expression as follows:

[0041]

[0042] In the above formula, Var M is the second variance; r M_n is the amplitude of the nth second frequency response after normalization; μ M is the average value of the plurality of second frequency response amplitudes; b n is the nth second frequency response amplitude.

[0043] In one embodiment, the fault weight is calculated according to the first variance to obtain a first fault weight expressed as:

[0044]

[0045] In the above formula, w H is the first fault weight;

[0046] The fault weight is calculated according to the second variance to obtain the second fault weight expressed as:

[0047]

[0048] In the above formula, w M is the second fault weight.

[0049] A computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the processor executes the steps of the above-mentioned transformer winding fault diagnosis method.

[0050] A terminal device comprises a memory and a processor, wherein the memory stores a computer program, and when the computer program is executed by the processor, the processor executes the steps of the above-mentioned transformer winding fault diagnosis method.

[0051] The present invention provides a transformer winding fault diagnosis method, device, medium and equipment, which obtains the frequency response amplitude of the transformer winding on a test platform, specifically adopts the method of signal injection on the high-voltage side and the medium-voltage side and signal collection on the low-voltage side. Then the variance of the frequency response amplitude is calculated and the fault weight is derived based on this. By preprocessing these data and combining the fault weight, the winding fault judgment factor is finally calculated. When the factor exceeds the preset threshold, it can be determined that the transformer winding is faulty. This method can realize continuous monitoring of the health status of the transformer winding, and by timely calculating and diagnosing the winding fault, it helps to discover potential problems early, avoid sudden faults, and ensure the stability and reliability of the power system. BRIEF DESCRIPTION OF THE DRAWINGS

[0052] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0053] in:

[0054] Figure 1 It is a flow chart of a transformer winding fault diagnosis method;

[0055] Figure 2 It is a structural schematic diagram of a transformer winding fault diagnosis device;

[0056] Figure 3 This is a structural block diagram of the terminal equipment. DETAILED DESCRIPTION

[0057] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0058] The terms "first", "second", etc. in the specification and claims of this application and the above-mentioned drawings are used to distinguish different objects, rather than to describe a specific order. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions. For example, a process, method, system, product or device that includes a series of steps or units is not limited to the listed steps or units, but optionally includes steps or units that are not listed, or optionally includes other steps or units inherent to these processes, methods, products or devices.

[0059] Reference to "embodiments" herein means that a particular feature, structure, or characteristic described in conjunction with the embodiments may be included in at least one embodiment of the present application. The appearance of the phrase in various locations in the specification does not necessarily refer to the same embodiment, nor is it an independent or alternative embodiment that is mutually exclusive with other embodiments. It is explicitly and implicitly understood by those skilled in the art that the embodiments described herein may be combined with other embodiments.

[0060] like Figure 1 As shown, Figure 1 FIG. 1 is a flow chart of a transformer winding fault diagnosis method in an embodiment. The steps provided by the transformer winding fault diagnosis method in this embodiment include:

[0061] S101, obtaining a plurality of first frequency response amplitudes and a plurality of second frequency response amplitudes.

[0062] Specifically, we use a computer to generate a high-frequency voltage signal through a digital signal generator. The digital signal generator will inject the high-frequency signal into the bushing of the transformer through a coupling capacitor to test the frequency response of the transformer. In order to obtain different frequency response data, two different signal injection methods are used.

[0063] Among them, method 1 is used to obtain the first frequency response amplitude: the operation configuration is to close the switch A of the transformer and open the switch B of the transformer. In this configuration, the signal will be injected through the high-voltage side bushing of the test platform, and the signal will be collected at the low-voltage side bushing. The amplitude of these collected frequency response data is the first frequency response amplitude, expressed as X H =[a1,a2…a n …a N ].

[0064] Method 2 is used to obtain the second frequency response amplitude: the operation configuration is to close the transformer switch B and open the transformer switch A. In this configuration, the signal will be injected through the medium voltage side bushing of the test platform, and the signal will be collected from the low voltage side bushing. The amplitude of the collected frequency response data is the second frequency response amplitude, expressed as X M =[b1,b2…bn …b N ].

[0065] It can be understood that different frequency response data help to reveal the electrical characteristics of the transformer windings. By comparing and analyzing these two sets of data, the health status of the transformer windings can be more accurately assessed.

[0066] S102, calculating the variance of a plurality of first frequency response amplitudes to obtain a first variance, and calculating the variance of a plurality of second frequency response amplitudes to obtain a second variance.

[0067] Variance is a statistical measure of the degree of dispersion of a data set, indicating the degree of deviation between the data and the mean. Calculating variance can help us understand the volatility of frequency response data.

[0068] Optionally, the variance of the plurality of first frequency response amplitudes is calculated to obtain a first variance expression as:

[0069]

[0070] In the above formula, Var H is the first variance; r H_n is the amplitude of the nth first frequency response after normalization; μ H is the average value of multiple first frequency response amplitudes; a n is the nth first frequency response amplitude, and N is the total number of frequency response amplitudes;

[0071] The variance of the multiple second frequency response amplitudes is calculated to obtain the second variance expression as:

[0072]

[0073] In the above formula, Var M is the second variance; r M_n is the amplitude of the nth second frequency response after normalization; μ M is the average value of multiple second frequency response amplitudes; b n is the nth second frequency response amplitude.

[0074] S103, calculating the fault weight according to the first variance to obtain a first fault weight, and calculating the fault weight according to the second variance to obtain a second fault weight.

[0075] The fault weight is a coefficient used to quantify the importance of the variance of the frequency response data to fault diagnosis.

[0076] Optionally, the larger the variance, the higher the fault weight, indicating that the signal data is more likely to be an indication of a fault. Conversely, frequency response data with a smaller variance has a weaker indication of a fault.

[0077] Optionally, the fault weight is calculated according to the first variance to obtain a first fault weight expressed as:

[0078]

[0079] In the above formula, w H is the first fault weight;

[0080] The fault weight is calculated according to the second variance to obtain the second fault weight expressed as:

[0081]

[0082] In the above formula, w M is the second fault weight.

[0083] In the fault weight calculation formula of the above specific embodiment, the dimension difference of the data is eliminated, so that the data of different frequency responses can be compared fairly. And by using cosine and sine functions to weight the data, the periodicity and phase information of the frequency response are included in the calculation, so that the type and location of the fault can be more accurately reflected.

[0084] S104, preprocessing the plurality of first frequency response amplitudes to obtain a first preprocessing result, and preprocessing the plurality of second frequency response amplitudes to obtain a second preprocessing result.

[0085] In this step, the goal of preprocessing is to optimize the performance of the frequency response data through mathematical calculations, enhance the features that may be hidden in the data, and thus improve the accuracy of fault diagnosis.

[0086] Optionally, a plurality of first frequency response amplitudes are preprocessed to obtain a first preprocessing result represented as:

[0087]

[0088] In the above formula, Y H_n The first preprocessing result of the nth first frequency response amplitude; the first part The amplitude is enhanced by nested exponential functions, so that sensitive data of transformer winding faults can be amplified or highlighted. The difference between the maximum and minimum values ​​of the first and second frequency responses is calculated and weighted by an exponential function. This is probably to reduce the extreme gap between different frequency responses and make the calculation of the eigenvalue more balanced. The normalized first frequency response amplitudes are summed and the deviation of each value from the mean is processed by an exponential function to reduce the influence of abnormal data deviating from the mean on the results.

[0089] The plurality of second frequency response amplitudes are preprocessed to obtain a second preprocessing result expressed as:

[0090]

[0091] In the above formula, Y M_n is the second preprocessing result of the nth second frequency response amplitude. This formula is the same as the previous formula, and will not be repeated here.

[0092] These two formulas pre-process the first frequency response amplitude and the second frequency response amplitude through a series of complex mathematical calculations, aiming to highlight important features in the data and enhance the identifiability of abnormal or extreme responses.

[0093] S105, calculating a winding fault judgment factor according to the first fault weight, the second fault weight, the first preprocessing result and the second preprocessing result, and if the winding fault judgment factor is greater than or equal to a preset fault threshold, determining that the transformer winding has a fault.

[0094] Among them, the winding fault judgment factor is a comprehensive indicator used to evaluate whether the transformer winding has a fault. The higher the value of this factor, the greater the possibility of a fault. By comparing with the preset fault threshold, it is determined whether a winding fault has occurred. The fault threshold is a constant related to the transformer model, winding signal injection method, and external equipment.

[0095] Optionally, the winding fault judgment factor is calculated according to the first fault weight, the second fault weight, the first preprocessing result, and the second preprocessing result and is expressed as:

[0096]

[0097] In the above formula, β is the winding fault judgment factor.

[0098] In the above formula, those frequency responses with large changes are highlighted through weighting and exponential amplification, thereby increasing the sensitivity to faults. And combined with cosine and sine, the periodic characteristics of frequency response data are considered. The calculated winding fault judgment factor can be updated in real time during the operation of the transformer, and potential winding faults can be discovered in time, and measures can be taken in advance to avoid larger faults.

[0099] The above transformer winding fault diagnosis method obtains the frequency response amplitude of the transformer winding on the test platform, specifically using the signal injection on the high-voltage side and the medium-voltage side and the signal acquisition on the low-voltage side. Then the variance of the frequency response amplitude is calculated and the fault weight is derived based on it. By preprocessing these data and combining the fault weight, the winding fault judgment factor is finally calculated. When the factor exceeds the preset threshold, it can be determined that the transformer winding is faulty. This method can realize continuous monitoring of the health status of the transformer winding. By timely calculating and diagnosing winding faults, it helps to detect potential problems early, avoid sudden faults, and ensure the stability and reliability of the power system.

[0100] In one embodiment, Figure 2 As shown, a transformer winding fault diagnosis device is proposed, the device comprising:

[0101] The acquisition module 201 is used to acquire a plurality of first frequency response amplitudes and a plurality of second frequency response amplitudes; wherein the first frequency response amplitude is the amplitude of the frequency response curve determined when a signal is injected into a high-voltage side bushing of the test platform and a signal is collected from a low-voltage side bushing, and the second frequency response amplitude is the amplitude of the frequency response curve determined when a signal is injected into a medium-voltage side bushing of the test platform and a signal is collected from a low-voltage side bushing;

[0102] A variance calculation module 202, configured to calculate the variance of a plurality of first frequency response amplitudes to obtain a first variance, and calculate the variance of a plurality of second frequency response amplitudes to obtain a second variance;

[0103] A fault weight calculation module 203, configured to calculate the fault weight according to the first variance to obtain a first fault weight, and to calculate the fault weight according to the second variance to obtain a second fault weight;

[0104] A preprocessing module 204, configured to preprocess the plurality of first frequency response amplitudes to obtain a first preprocessing result, and to preprocess the plurality of second frequency response amplitudes to obtain a second preprocessing result;

[0105] The fault judgment module 205 is used to calculate the winding fault judgment factor according to the first fault weight, the second fault weight, the first preprocessing result and the second preprocessing result. If the winding fault judgment factor is greater than or equal to a preset fault threshold, it is determined that the transformer winding has a fault.

[0106] Figure 3 FIG. 2 shows an internal structure diagram of a terminal device in an embodiment. Figure 3As shown, the terminal device includes a processor, a memory and a network interface connected via a system bus. The memory includes a non-volatile storage medium and an internal memory. The non-volatile storage medium of the terminal device stores an operating system and may also store a computer program. When the computer program is executed by the processor, the processor may implement a transformer winding fault diagnosis method. The internal memory may also store a computer program. When the computer program is executed by the processor, the processor may implement a transformer winding fault diagnosis method. Those skilled in the art will understand that Figure 3 The structure shown in the figure is only a block diagram of a partial structure related to the scheme of the present application, and does not constitute a limitation on the terminal device to which the scheme of the present application is applied. The specific terminal device may include more or fewer components than those shown in the figure, or combine certain components, or have a different arrangement of components.

[0107] A computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the following steps are implemented: obtaining a plurality of first frequency response amplitudes and a plurality of second frequency response amplitudes; wherein the first frequency response amplitude is the amplitude of a frequency response curve determined when a signal is injected into a high-voltage side bushing of a test platform and a signal is collected from a low-voltage side bushing, and the second frequency response amplitude is the amplitude of a frequency response curve determined when a signal is injected into a medium-voltage side bushing of the test platform and a signal is collected from a low-voltage side bushing; calculating the variance of the plurality of first frequency response amplitudes to obtain a first variance, and calculate the variance of multiple second frequency response amplitudes to obtain a second variance; calculate the fault weight according to the first variance to obtain a first fault weight, and calculate the fault weight according to the second variance to obtain a second fault weight; preprocess the multiple first frequency response amplitudes to obtain a first preprocessing result, and preprocess the multiple second frequency response amplitudes to obtain a second preprocessing result; calculate the winding fault judgment factor according to the first fault weight, the second fault weight, the first preprocessing result and the second preprocessing result, and if the winding fault judgment factor is greater than or equal to the preset fault threshold, it is determined that the transformer winding has a fault.

[0108] A terminal device comprises a memory, a processor and a computer program stored in the memory and executable on the processor, wherein the processor implements the following steps when executing the computer program: obtaining a plurality of first frequency response amplitudes and a plurality of second frequency response amplitudes; wherein the first frequency response amplitude is the amplitude of a frequency response curve determined when a signal is injected into a high-voltage side bushing of a test platform and a signal is collected from a low-voltage side bushing, and the second frequency response amplitude is the amplitude of a frequency response curve determined when a signal is injected into a medium-voltage side bushing of the test platform and a signal is collected from a low-voltage side bushing; and calculating the variance of the plurality of first frequency response amplitudes. , to obtain a first variance, and calculate the variance of multiple second frequency response amplitudes to obtain a second variance; calculate the fault weight according to the first variance to obtain the first fault weight, and calculate the fault weight according to the second variance to obtain the second fault weight; preprocess the multiple first frequency response amplitudes to obtain a first preprocessing result, and preprocess the multiple second frequency response amplitudes to obtain a second preprocessing result; calculate the winding fault judgment factor according to the first fault weight, the second fault weight, the first preprocessing result and the second preprocessing result, and if the winding fault judgment factor is greater than or equal to the preset fault threshold, it is determined that the transformer winding has a fault.

[0109] It should be noted that the above-mentioned transformer winding fault diagnosis method, device, equipment and computer-readable storage medium belong to a general inventive concept, and the contents in the embodiments of the transformer winding fault diagnosis method, device, equipment and computer-readable storage medium are applicable to each other.

[0110] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the program can be stored in a non-volatile computer-readable storage medium. When the program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, storage, database or other media used in the embodiments provided in this application can include non-volatile and / or volatile memory. Non-volatile memory may include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. Volatile memory may include random access memory (RAM) or external cache memory. As an illustration and not limitation, RAM is available in many forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).

[0111] The technical features of the above embodiments may be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0112] The above embodiments only express several implementation methods of the present application, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the present application. It should be pointed out that, for a person of ordinary skill in the art, several modifications and improvements can be made without departing from the concept of the present application, and these all belong to the protection scope of the present application. Therefore, the protection scope of the present application shall be subject to the attached claims.

Claims

1. A transformer winding fault diagnosis method, characterized in that: Applied to a test platform, the method comprises: Acquire multiple first frequency response amplitudes and multiple second frequency response amplitudes; wherein the first frequency response amplitude is the amplitude of the frequency response curve determined when a signal is injected into the high-voltage side bushing of the test platform and a signal is collected from the low-voltage side bushing, and the second frequency response amplitude is the amplitude of the frequency response curve determined when a signal is injected into the medium-voltage side bushing of the test platform and a signal is collected from the low-voltage side bushing; Calculating the variance of the plurality of first frequency response amplitudes to obtain a first variance, and calculating the variance of the plurality of second frequency response amplitudes to obtain a second variance; Calculating a fault weight according to the first variance to obtain a first fault weight, and calculating a fault weight according to the second variance to obtain a second fault weight; Preprocessing the plurality of first frequency response amplitudes to obtain a first preprocessing result, and preprocessing the plurality of second frequency response amplitudes to obtain a second preprocessing result; A winding fault judgment factor is calculated according to the first fault weight, the second fault weight, the first preprocessing result and the second preprocessing result. If the winding fault judgment factor is greater than or equal to a preset fault threshold, it is determined that a transformer winding has a fault.

2. The method according to claim 1, characterized in that The calculation of the variance of the plurality of first frequency response amplitudes to obtain a first variance is expressed as: In the above formula, Var H is the first variance; r H_n is the amplitude of the nth first frequency response after normalization; μ H is the average value of the plurality of first frequency response amplitudes; a n is the nth first frequency response amplitude, and N is the total number of frequency response amplitudes; The variance of the plurality of second frequency response amplitudes is calculated to obtain a second variance expression as follows: In the above formula, Var M is the second variance; r M_n is the amplitude of the nth second frequency response after normalization; μ M is the average value of the plurality of second frequency response amplitudes; b n is the nth second frequency response amplitude.

3. The method according to claim 2, characterized in that The fault weight is calculated according to the first variance to obtain a first fault weight expressed as: In the above formula, w H is the first fault weight; The fault weight is calculated according to the second variance to obtain the second fault weight expressed as: In the above formula, w M is the second fault weight.

4. The method according to claim 2, characterized in that: The preprocessing of the plurality of first frequency response amplitudes to obtain a first preprocessing result is expressed as: In the above formula, Y H_n is the first preprocessing result of the nth first frequency response amplitude; The preprocessing of the plurality of second frequency response amplitudes to obtain a second preprocessing result is expressed as: In the above formula, Y M_n is the second preprocessing result of the nth second frequency response amplitude.

5. The method according to claim 4, characterized in that The winding fault judgment factor calculated according to the first fault weight, the second fault weight, the first preprocessing result and the second preprocessing result is expressed as: In the above formula, β is the winding fault judgment factor.

6. A transformer winding fault diagnosis device, characterized in that: The transformer winding fault diagnosis device comprises: An acquisition module, used to acquire multiple first frequency response amplitudes and multiple second frequency response amplitudes; wherein the first frequency response amplitude is the amplitude of the frequency response curve determined when a signal is injected into the high-voltage side bushing of the test platform and a signal is collected from the low-voltage side bushing, and the second frequency response amplitude is the amplitude of the frequency response curve determined when a signal is injected into the medium-voltage side bushing of the test platform and a signal is collected from the low-voltage side bushing; A variance calculation module, configured to calculate the variance of the plurality of first frequency response amplitudes to obtain a first variance, and calculate the variance of the plurality of second frequency response amplitudes to obtain a second variance; a fault weight calculation module, configured to calculate the fault weight according to the first variance to obtain a first fault weight, and to calculate the fault weight according to the second variance to obtain a second fault weight; A preprocessing module, configured to preprocess the plurality of first frequency response amplitudes to obtain a first preprocessing result, and preprocess the plurality of second frequency response amplitudes to obtain a second preprocessing result; A fault judgment module is used to calculate a winding fault judgment factor according to the first fault weight, the second fault weight, the first preprocessing result and the second preprocessing result. If the winding fault judgment factor is greater than or equal to a preset fault threshold, it is determined that there is a fault in the transformer winding.

7. The transformer winding fault diagnosis device according to claim 6, characterized in that: The calculation of the variance of the plurality of first frequency response amplitudes to obtain a first variance is expressed as: In the above formula, Var H is the first variance; r H_n is the amplitude of the nth first frequency response after normalization; μ H is the average value of the plurality of first frequency response amplitudes; a n is the nth first frequency response amplitude, and N is the total number of frequency response amplitudes; The variance of the plurality of second frequency response amplitudes is calculated to obtain a second variance expression as follows: In the above formula, Var M is the second variance; r M_n is the amplitude of the nth second frequency response after normalization; μ M is the average value of the plurality of second frequency response amplitudes; b n is the nth second frequency response amplitude.

8. The transformer winding fault diagnosis device according to claim 7, characterized in that: The fault weight is calculated according to the first variance to obtain a first fault weight expressed as: In the above formula, w H is the first fault weight; The fault weight is calculated according to the second variance to obtain the second fault weight expressed as: In the above formula, w M is the second fault weight.

9. A computer-readable storage medium, characterized in that: A computer program is stored, and when the computer program is executed by a processor, the processor is caused to perform the steps of the method according to any one of claims 1 to 5.

10. A terminal device, characterized in that: The method comprises a memory and a processor, wherein the memory stores a computer program, and when the computer program is executed by the processor, the processor executes the steps of the method according to any one of claims 1 to 5.

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