Transformer vibration signal extraction method, system, equipment and medium

Abstract

The invention relates to the technical field of transformer vibration signal processing, in particular to a transformer vibration signal extraction method, system and equipment and a medium, and the method comprises the steps: collecting a vibration signal of a transformer in an operation process, and carrying out the preprocessing of the vibration signal; performing wavelet transform on the preprocessed vibration signal to obtain an energy time-frequency diagram of the vibration signal, and obtaining a wavelet energy-time distribution curve according to the energy time-frequency diagram; and determining an extreme point of the wavelet energy-time distribution curve, determining a starting point and an ending point of the vibration signal according to the set extreme point, and further extracting two periodic signal time domain waveforms in a power frequency period. According to the method, the time domain waveform of the transformer vibration signal can be efficiently and accurately obtained.

Description

Technical Field

[0001] The invention relates to the technical field of transformer vibration signal processing, and in particular to a transformer vibration signal extraction method, system, equipment and medium. Background Art

[0002] As an important device for realizing electric energy transmission and distribution, the transformer plays a decisive role in the stable operation of the power system. Once a fault or damage occurs, the impact is extremely wide. Under the action of electromagnetic force or mechanical force, the mechanical structure of the transformer winding and core undergoes irreversible changes, including winding loosening, warping, bulging and misalignment, core loosening, inter-laminar wear, etc., which are hidden dangers to the safe and stable operation of the transformer. Therefore, it is of great significance to carry out transformer mechanical status detection and diagnosis.

[0003] When the mechanical state of transformer windings and cores changes, it is often not reflected by conventional insulation tests such as dissolved gas in oil and partial discharge. Vibration analysis measures the vibration signal of the transformer box as the basis for diagnosing the mechanical state. It has the advantages of convenient live detection, no direct electrical connection with the transformer, and strong anti-interference performance. It has been a hot topic in recent years.

[0004] At present, the research on vibration analysis is focused on the spectrum analysis of vibration signals. The mechanical state of transformer windings or cores is diagnosed by extracting the 100Hz vibration fundamental frequency component, 50Hz odd-number multiple components, and 50Hz even-number multiple components. By analyzing the vibration principle of the transformer, it can be known that due to the effect of electrodynamic force and magnetostriction, the fundamental frequency of the transformer is twice the grid power frequency when it is running, that is, one power frequency cycle contains two cycles of vibration signals. Time domain waveform extraction can analyze the vibration signals of these two cycles separately and reveal the difference in changes between them, which is particularly important for diagnosing the mechanical state of the transformer under complex working conditions. When the mechanical state of the transformer occurs, the vibration signal waveform is distorted, and the changes of the vibration signals of these two cycles are often inconsistent. In order to accurately extract the time domain waveform of the vibration signal, it is necessary to keep synchronization with the grid frequency. However, in actual operation, due to the slight fluctuation of the grid frequency and the limitation of the measurement equipment, the synchronization accuracy may be affected, resulting in errors in the extracted waveform. The transformer vibration signal is collected continuously, and the amount of data is huge. In the real-time processing process, how to efficiently and accurately extract the time domain waveform while ensuring the real-time and stability of the system is an urgent problem to be solved. Summary of the invention

[0005] The technical problem to be solved by the present invention is to provide a transformer vibration signal extraction method, system, device and medium in view of the deficiencies in the above-mentioned prior art, with the aim of solving the problem that the time domain waveform of the transformer vibration signal cannot be extracted efficiently and accurately.

[0006] The objective of the present invention is achieved by the following technical solutions: In a first aspect, the present invention provides a transformer vibration signal extraction method, comprising: Collect the vibration signal of the transformer during operation and pre-process the vibration signal; Performing wavelet transform on the preprocessed vibration signal to obtain an energy time-frequency diagram of the vibration signal, and obtaining a wavelet energy-time distribution curve according to the energy time-frequency diagram; The extreme points of the wavelet energy-time distribution curve are determined, and the starting and ending points of the vibration signal are determined according to the set extreme points, thereby extracting the time domain waveforms of two periodic signals within one power frequency cycle.

[0007] As a further improvement of the present invention, the preprocessing of the vibration signal specifically includes: the preprocessing step is to use a low-pass filter for processing.

[0008] As a further improvement of the present invention, the wavelet transform of the preprocessed vibration signal to obtain the energy time-frequency diagram of the vibration signal specifically includes: performing a wavelet transform on the vibration pulse signal to form an energy time-frequency diagram, and analyzing the energy time-frequency diagram to obtain a wavelet transform coefficient; the wavelet transform coefficient is:

[0009] In the formula, is the wavelet transform coefficient, a is the scale parameter, b is the time parameter, is the wavelet basis function go through a and b The wavelet function cluster formed by the change, yes The conjugation of.

[0010] As a further improvement of the present invention, obtaining the wavelet energy-time distribution curve according to the energy time-frequency diagram specifically includes: The wavelet transform coefficients are integrated along the frequency axis to obtain the wavelet energy distribution of the vibration signal over time, and a wavelet energy-time distribution curve is drawn based on the wavelet energy distribution of the vibration signal over time.

[0011] As a further improvement of the present invention, the wavelet energy distribution of the vibration signal over time is:

[0012] In the formula, is the wavelet energy distribution of the vibration signal over time, is the wavelet transform coefficient, ais the scale parameter, b is the time parameter.

[0013] As a further improvement of the present invention, the step of determining the extreme point of the wavelet energy-time distribution curve and determining the starting point and the ending point of the vibration signal according to the extreme point specifically includes: Determine all extreme points based on the wavelet energy-time distribution curve and determine the time interval between adjacent extreme points; According to the set time threshold, the set extreme value points are screened out, and the starting point and the ending point of the vibration signal are located according to the set extreme value points.

[0014] As a further improvement of the present invention, the time threshold is 2-5 ms.

[0015] In a second aspect, the present invention provides a transformer vibration signal extraction system, which is used to implement the above-mentioned transformer vibration signal extraction method, comprising: A data acquisition module is used to collect vibration signals of the transformer during operation and pre-process the vibration signals; A data processing module is used to perform wavelet transform on the preprocessed vibration signal to obtain an energy time-frequency diagram of the vibration signal, and obtain a wavelet energy-time distribution curve according to the energy time-frequency diagram; The signal extraction module is used to determine the extreme points of the wavelet energy-time distribution curve, determine the starting point and the ending point of the vibration signal according to the set extreme points, and then extract the time domain waveforms of two periodic signals within one power frequency cycle.

[0016] In a third aspect, the present invention provides a computer-readable storage medium storing one or more programs, wherein the one or more programs include instructions, which, when executed by a computing device, enable the computing device to execute the above-mentioned transformer vibration signal extraction method.

[0017] In a fourth aspect, the present invention provides a computing device, comprising: One or more processors, a memory and one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the one or more processors, and the one or more programs include steps for executing the above-mentioned transformer vibration signal extraction method.

[0018] The beneficial effects of the present invention are as follows: the present invention provides a transformer vibration signal extraction method, which pre-processes the collected vibration signal, removes background noise and interference signals, improves signal quality, and performs wavelet transform on the pre-processed vibration signal. Through wavelet transform, the vibration signal can be decomposed into sub-signals of different frequency components, and then the energy distribution of each frequency component is analyzed. Based on the energy time-frequency diagram, the characteristic frequency and energy changes in the vibration signal can be clearly displayed, and the extreme points are determined on the wavelet energy-time distribution curve. The extreme points usually correspond to characteristic events or state changes in the vibration signal. The starting point and the end point of the vibration signal are determined according to the set extreme points. These points will be used to extract the time domain waveforms of two periodic signals within a power frequency cycle, and the extracted time domain waveforms can be used to further analyze the operating status and fault characteristics of the transformer. Through the application of transformation and energy time-frequency diagram, the characteristics of the vibration signal are more obvious and accurate, which is convenient for identification and analysis. The extracted time domain waveforms of the two periodic signals within the power frequency cycle provide an important basis for early fault diagnosis of the transformer. The method can realize the time domain waveform extraction of the transformer vibration signal, provide important support for the mechanical state assessment of the transformer, and has good practical value.

[0019] Furthermore, the collected vibration signal is preprocessed by low-pass filtering to effectively remove high-frequency noise and interference signals in the vibration signal and improve the signal quality.

[0020] Furthermore, wavelet transform can provide information about the signal in both the time and frequency domains. By converting frequency information into energy information through integration, the energy changes of the signal in different time periods can be more intuitively displayed. By transforming the wavelet transform and integrating along the frequency axis, the influence of these noise components on the signal energy can be suppressed to a certain extent, making the useful information in the signal more prominent.

[0021] Furthermore, by drawing the wavelet energy-time distribution curve, the trend of energy change over time can be clearly observed, thereby identifying the abnormal state of equipment operation or the time point when a fault occurs. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] 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 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.

[0023] Figure 1 1 is a schematic diagram of a time domain waveform flow of a vibration signal in an embodiment of the present invention; Figure 2 is a schematic diagram of a vibration signal in an embodiment of the present invention; Figure 3 is a schematic diagram of the time-frequency distribution of vibration signal energy in an embodiment of the present invention; Figure 4 is a schematic diagram of a wavelet energy-time curve of a vibration signal in an embodiment of the present invention; Figure 5 Schematic diagram of vibration signal extraction of two cycles within one power frequency cycle in an embodiment of the present invention; Figure 6 It is a schematic diagram of the structure of the transformer vibration signal extraction system in an embodiment of the present invention. DETAILED DESCRIPTION

[0024] In order to make the purpose and technical solution of the present invention clearer and easier to understand, the present invention is further described in detail below in conjunction with the accompanying drawings and embodiments. The specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0025] The concept of the present invention is to provide a transformer vibration signal extraction method, system, device and medium. The method steps provided by the present invention only need to include: Collect the vibration signal of the transformer during operation and pre-process the vibration signal; Performing wavelet transform on the preprocessed vibration signal to obtain an energy time-frequency diagram of the vibration signal, and obtaining a wavelet energy-time distribution curve according to the energy time-frequency diagram; The extreme points of the wavelet energy-time distribution curve are determined, and the starting and ending points of the vibration signal are determined according to the set extreme points, thereby extracting the time domain waveforms of two periodic signals within one power frequency cycle.

[0026] The extracted two periodic signal time domain waveforms within the power frequency cycle provide an important basis for early fault diagnosis of the transformer. This method can realize the extraction of transformer vibration signal time domain waveform, provide important support for transformer mechanical state assessment, and has good practical value.

[0027] The technical solution of the present invention will be clearly and completely described below in conjunction with the accompanying drawings and specific embodiments, wherein the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments.

[0028] Example 1 like Figure 1-Figure 5As shown, this embodiment provides a transformer vibration signal extraction method, which uses an acceleration sensor to monitor the vibration signal of an operating transformer and collects vibration signals of a certain length. First, the vibration signal is preprocessed to remove the interference of the vibration pulse signal; then, the vibration signal is subjected to wavelet transform to obtain the energy time-frequency diagram of the vibration signal; then, the vibration signal wavelet energy-time distribution curve is obtained, and the extreme value point is found; finally, by setting the time threshold, the starting point and the end point of the vibration signal are obtained, and the extraction of two period vibration signals within one power frequency cycle is realized. The following is a specific implementation method.

[0029] Firstly, the vibration signal of the transformer during operation is collected and preprocessed.

[0030] Among them, the technical means of using the vibration signal of the transformer include vibration accelerometer or voiceprint recognition technology. The vibration accelerometer is mainly set at the key position of the transformer, such as the oil tank wall, core or winding of the transformer to capture the vibration signal during the operation of the transformer. The voiceprint recognition technology measures the voiceprint signal of the transformer at a long distance through a microphone array. When a defect or failure occurs in the equipment, the mechanical deformation of the internal components or structures will cause the acoustic fingerprint (voiceprint) to change. These voiceprint signals can be used as important characteristic parameters for diagnosing defects and failures. This embodiment uses a vibration accelerometer to collect vibration signals.

[0031] The acceleration sensor is used to collect vibration signals of a certain length of time on the surface of the oil tank of the running transformer. , N Indicates vibration signal The number of sampling points. In this embodiment, the vibration signal collected is as follows Figure 2 As shown, the acquisition duration is 500ms, the sampling rate is 20kS / s, and the number of sampling points is 10000.

[0032] The collected vibration signal is preprocessed, and the collected original vibration signal is filtered, denoised, etc. to remove background noise and interference signals and improve signal quality. In this embodiment, a low-pass filter is used to remove the pulse signal in the vibration signal. The cut-off frequency of the low-pass filter in this embodiment is 3000 Hz.

[0033] Secondly, the pre-processed vibration signal is subjected to wavelet transformation to obtain an energy time-frequency diagram of the vibration signal, and a wavelet energy-time distribution curve is obtained according to the energy time-frequency diagram.

[0034] Specifically, the vibration pulse signal is subjected to wavelet transform to form an energy time-frequency diagram, and the wavelet transform coefficient is obtained by analyzing the energy time-frequency diagram; wherein the wavelet transform coefficient is:

[0035] In the formula, is the wavelet transform coefficient, a is the scale parameter, b is the time parameter, is the wavelet basis function go through a and b The wavelet function cluster formed by the change, yes The conjugation of.

[0036] The energy time-frequency distribution of the vibration signal in this embodiment is as follows: Figure 3 As shown in Figure 2, it can be seen that the vibration signal energy is mainly concentrated at 100Hz, 200Hz and 300Hz.

[0037] The wavelet transform coefficients are integrated along the frequency axis to obtain the wavelet energy distribution of the vibration signal over time, and a wavelet energy-time distribution curve is drawn based on the wavelet energy distribution of the vibration signal over time.

[0038] Wavelet energy distribution of vibration signal over time The situation is:

[0039] In the formula, is the wavelet energy distribution of the vibration signal over time, is the wavelet transform coefficient, a is the scale parameter, b is the time parameter.

[0040] In this embodiment, taking the vibration signal of 200ms to 300ms as an example, the wavelet energy-time distribution of the vibration signal is as follows: Figure 4 As shown. Figure 4 As shown, the wavelet energy-time curve of the vibration signal is approximately a sine curve, showing regular fluctuations.

[0041] Finally, the extreme points of the wavelet energy-time distribution curve are determined, and the starting and ending points of the vibration signal are determined according to the set extreme points, and then the time domain waveforms of two periodic signals within one power frequency cycle are extracted.

[0042] Specifically, all extreme value points are determined according to the wavelet energy-time distribution curve, and the time intervals between adjacent extreme value points are determined; According to the set time threshold, the set extreme value points are screened out, and the starting point and the ending point of the vibration signal are located according to the set extreme value points.

[0043] In this embodiment, the wavelet energy-time curve of the vibration signal in the time period of 200ms to 300ms is taken as an example, and its extreme points are as follows: Figure 4 As shown, the red box represents the maximum point, and the time interval between adjacent extreme points is 10ms.

[0044] A time threshold is set, and the range of the time threshold is 2-5 ms. If the time interval between two adjacent extreme value points is less than the time threshold, the largest extreme value point is retained. In this embodiment, the time threshold is set to 3 ms, and all extreme value points meet the requirements.

[0045] Based on the extreme point, the starting point and the end point of the vibration signal are located, and the vibration signals of two cycles within one power frequency cycle are successfully extracted. In this embodiment, the vibration signals of two cycles within one power frequency cycle are as follows: Figure 5 As shown in the figure, in this case, the vibration signal ① and the vibration signal ② are basically the same. It can be seen that this method can accurately and effectively extract the vibration signals of two cycles.

[0046] In summary, the transformer extraction method in this embodiment performs wavelet transform on the preprocessed vibration signal. Through wavelet transform, the vibration signal can be decomposed into sub-signals of different frequency components, and then the energy distribution of each frequency component can be analyzed. Based on the time-frequency diagram, the characteristic frequency and energy changes in the vibration signal can be determined on the wavelet energy-time distribution curve. The extreme point usually corresponds to the characteristic event or state change in the vibration signal. The starting point and the end point of the vibration signal are determined according to the set extreme point. These points will be used to extract the time domain waveforms of two periodic signals within a power frequency cycle, and the extracted time domain waveforms can be used to further analyze the operating status and fault characteristics of the transformer. Through the application of transformation and energy time-frequency diagram, the characteristics of the vibration signal are more obvious, which is convenient for identification and analysis. The extracted time domain waveforms of the two periodic signals within the power frequency cycle provide an important basis for early fault diagnosis of the transformer. This method can realize the time domain waveform extraction of the transformer vibration signal, provide important support for the mechanical state assessment of the transformer, and has good practical value.

[0047] Example 2 like Figure 6 As shown, this embodiment provides a transformer vibration signal extraction system, which implements the transformer vibration signal extraction method described in Example 1. The system includes: A data acquisition module is used to collect vibration signals of the transformer during operation and pre-process the vibration signals; A data processing module is used to perform wavelet transform on the preprocessed vibration signal to obtain an energy time-frequency diagram of the vibration signal, and obtain a wavelet energy-time distribution curve according to the energy time-frequency diagram; The signal extraction module is used to determine the extreme points of the wavelet energy-time distribution curve, determine the starting point and the ending point of the vibration signal according to the set extreme points, and then extract the time domain waveforms of two periodic signals within one power frequency cycle.

[0048] The technicians in the relevant field can clearly understand that for the convenience and simplicity of description, only the division of the above-mentioned functional units and modules is used as an example for illustration. In practical applications, the above-mentioned function allocation can be completed by different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above. The functional units and modules in the embodiment can be integrated in a processing unit, or each unit can exist physically separately, or two or more units can be integrated in one unit. The above-mentioned integrated unit can be implemented in the form of hardware or in the form of software functional units. In addition, the specific names of the functional units and modules are only for the convenience of distinguishing each other, and are not used to limit the scope of protection of this application. The specific working process of the units and modules in the above-mentioned system can refer to the corresponding process in the aforementioned method embodiment, which will not be repeated here.

[0049] In the above embodiments, the description of each embodiment has its own emphasis. For parts that are not described or recorded in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0050] Example 3 In another embodiment of the present invention, a computing device (i.e., a terminal device) is provided, the terminal device including a processor and a memory, the memory is used to store a computer program, the computer program includes program instructions, and the processor is used to execute the program instructions stored in the computer storage medium. The processor may be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gates or transistor logic devices, discrete hardware components, etc. It is the computing core and control core of the terminal, which is suitable for implementing one or more instructions, and is specifically suitable for loading and executing one or more instructions to implement the corresponding method flow or corresponding functions; the processor described in the embodiment of the present invention can be used for the operation of the transformer vibration signal extraction method, including: Collect the vibration signal of the transformer during operation and pre-process the vibration signal; Performing wavelet transform on the preprocessed vibration signal to obtain an energy time-frequency diagram of the vibration signal, and obtaining a wavelet energy-time distribution curve according to the energy time-frequency diagram; The extreme points of the wavelet energy-time distribution curve are determined, and the starting and ending points of the vibration signal are determined according to the set extreme points, thereby extracting the time domain waveforms of two periodic signals within one power frequency cycle.

[0051] Example 4 In another embodiment of the present invention, the present invention also provides a storage medium, specifically a computer-readable storage medium (Memory), which is a memory device in a terminal device for storing programs and data. It is understandable that the computer-readable storage medium here can include both the built-in storage medium in the terminal device and the extended storage medium supported by the terminal device, and can be any tangible medium containing or storing a program, which can be used by an instruction execution system, device or device or used in combination with it. The computer-readable storage medium provides a storage space, which stores the operating system of the terminal. In addition, one or more instructions suitable for being loaded and executed by the processor are also stored in the storage space, and these instructions can be one or more computer programs (including program codes). It should be noted that more specific examples (non-exhaustive list) of the computer-readable storage medium here include: an electrical connection with one or more wires, a portable disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above.

[0052] Computer readable storage media also include data signals propagated in baseband or as part of a carrier wave, which carry readable program codes. Such propagated data signals can take a variety of forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the above. The readable storage medium can also be any readable medium other than a readable storage medium, which can send, propagate, or transmit a program for use by or in conjunction with an instruction execution system, device, or device. The program code contained on the readable storage medium can be transmitted using any appropriate medium, including but not limited to wireless, wired, optical cable, RF, etc., or any suitable combination of the above.

[0053] Program code for performing the operations of the present invention may be written in any combination of one or more programming languages, including object-oriented programming languages ​​such as Java, C++, etc., and conventional procedural programming languages ​​such as "C" or similar programming languages. The program code may be executed entirely on the user computing device, partially on the user device, as a separate software package, partially on the user computing device and partially on a remote computing device, or entirely on a remote computing device or server. In the case of a remote computing device, the remote computing device may be connected to the user computing device through any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computing device (e.g., through the Internet using an Internet service provider).

[0054] The processor may load and execute one or more instructions stored in a computer-readable storage medium to implement the corresponding steps of the transformer vibration signal extraction method in the above embodiment; the processor may load and execute the following steps: Collect the vibration signal of the transformer during operation and pre-process the vibration signal; Performing wavelet transform on the preprocessed vibration signal to obtain an energy time-frequency diagram of the vibration signal, and obtaining a wavelet energy-time distribution curve according to the energy time-frequency diagram; The extreme points of the wavelet energy-time distribution curve are determined, and the starting and ending points of the vibration signal are determined according to the set extreme points, thereby extracting the time domain waveforms of two periodic signals within one power frequency cycle.

[0055] Those skilled in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed in the present invention can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of the present invention.

[0056] In the embodiments provided by the present invention, it should be understood that the disclosed systems / terminals and methods can be implemented in other ways. For example, the device / terminal embodiments described above are only schematic. For example, the division of the modules or units is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0057] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0058] In addition, each functional unit in each embodiment of the present invention may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

Claims

1. A transformer vibration signal extraction method, characterized in that: include: Collect the vibration signal of the transformer during operation and pre-process the vibration signal; Performing wavelet transform on the preprocessed vibration signal to obtain an energy time-frequency diagram of the vibration signal, and obtaining a wavelet energy-time distribution curve according to the energy time-frequency diagram; The extreme points of the wavelet energy-time distribution curve are determined, and the starting and ending points of the vibration signal are determined according to the set extreme points, thereby extracting the time domain waveforms of two periodic signals within one power frequency cycle.

2. The transformer vibration signal extraction method according to claim 1, characterized in that: The preprocessing of the vibration signal specifically includes: a preprocessing step of using a low-pass filter for processing.

3. The transformer vibration signal extraction method according to claim 1, characterized in that: The method of performing wavelet transform on the pre-processed vibration signal to obtain the energy time-frequency diagram of the vibration signal specifically includes: performing wavelet transform on the vibration pulse signal to form an energy time-frequency diagram, and obtaining wavelet transform coefficients based on the analysis of the energy time-frequency diagram; the wavelet transform coefficients are: In the formula, is the wavelet transform coefficient, a is the scale parameter, b is the time parameter, is the wavelet basis function go through a and b The wavelet function cluster formed by the change, yes The conjugation of.

4. The transformer vibration signal extraction method according to claim 3, characterized in that: The step of obtaining the wavelet energy-time distribution curve according to the energy time-frequency diagram specifically includes: The wavelet transform coefficients are integrated along the frequency axis to obtain the wavelet energy distribution of the vibration signal over time, and a wavelet energy-time distribution curve is drawn based on the wavelet energy distribution of the vibration signal over time.

5. The transformer vibration signal extraction method according to claim 4, characterized in that: The wavelet energy distribution of the vibration signal over time is: In the formula, is the wavelet energy distribution of the vibration signal over time, is the wavelet transform coefficient, a is the scale parameter, b is the time parameter.

6. The transformer vibration signal extraction method according to claim 4, characterized in that: The step of determining the extreme point of the wavelet energy-time distribution curve and determining the starting point and the ending point of the vibration signal according to the extreme point specifically includes: Determine all extreme points based on the wavelet energy-time distribution curve and determine the time interval between adjacent extreme points; According to the set time threshold, the set extreme value points are screened out, and the starting point and the ending point of the vibration signal are located according to the set extreme value points.

7. The transformer vibration signal extraction method according to claim 6, characterized in that: The time threshold is 2-5 ms.

8. A transformer vibration signal extraction system, used to implement the transformer vibration signal extraction method according to any one of claims 1 to 7, characterized in that: include: A data acquisition module is used to collect vibration signals of the transformer during operation and pre-process the vibration signals; A data processing module is used to perform wavelet transform on the preprocessed vibration signal to obtain an energy time-frequency diagram of the vibration signal, and obtain a wavelet energy-time distribution curve according to the energy time-frequency diagram; The signal extraction module is used to determine the extreme points of the wavelet energy-time distribution curve, determine the starting point and the ending point of the vibration signal according to the set extreme points, and then extract the time domain waveforms of two periodic signals within one power frequency cycle.

9. A computer-readable storage medium storing one or more programs, characterized in that: The one or more programs include instructions, which, when executed by a computing device, cause the computing device to execute the transformer vibration signal extraction method according to any one of claims 1 to 7.

10. A computing device, characterized in that include: One or more processors, a memory and one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the one or more processors, and the one or more programs include steps for executing the transformer vibration signal extraction method according to any one of claims 1 to 7.

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