Direct-current magnetic bias fault diagnosis method for vibration signals of high-frequency transformer and related device

Abstract

The invention discloses a direct-current magnetic bias fault diagnosis method and related device for vibration signals of a high-frequency transformer, and belongs to the technical field of direct-current magnetic bias fault diagnosis. The method comprises the following steps: collecting vibration signals of the surface of a clamping piece of the high-frequency transformer under different working conditions; performing fast Fourier transform on the vibration signal to obtain the amplitude of the vibration signal under each frequency; calculating the frequency proportion of the vibration signal, the odd-even harmonic ratio of the vibration signal and the vibration entropy of the vibration signal; calculating a direct current bias judgment characteristic value based on the frequency proportion, the odd-even harmonic ratio and the vibration entropy; and comparing the direct-current bias judgment characteristic value with a preset threshold value, and judging the direct-current bias state of the high-frequency transformer. According to the method, the complexity of detection and maintenance is reduced, online monitoring can be realized under the normal operation condition of the transformer, potential fault hidden dangers can be found in advance, the defects of magnetostriction and vibration monitoring caused by direct current magnetic bias in the prior art are overcome, and the feasibility of direct current magnetic bias hidden danger detection is improved.

Description

TECHNICAL FIELD

[0001] The application belongs to the technical field of direct current bias fault diagnosis, and particularly relates to a direct current bias fault diagnosis method for high-frequency transformer vibration signals and a related device. BACKGROUND

[0002] At present, as a core component in DC-DC converters and other power electronic devices, the operation reliability of a high-frequency transformer directly affects the stability and safety of a system. In actual operation, the high-frequency transformer often has abnormal vibration phenomena, and the direct current bias is considered as one of the important reasons for the problem. Unlike power frequency power transformers, high-frequency transformers are usually applied to power electronic topologies such as full-bridge, half-bridge or double active bridge, and do not have a neutral point structure. However, due to factors such as asymmetric driving signals, device parameter deviations or unbalanced control strategies, direct current components may be introduced into the excitation current. These direct current components can cause the core to deviate from magnetic saturation within half a working period, thereby causing a series of adverse electromagnetic and mechanical effects.

[0003] Especially when the core is in a half-wave saturation state, the excitation current will have obvious distortion and be accompanied by the generation of a large number of harmonic components. This not only leads to an increase in high-frequency transformer loss and temperature rise, but also intensifies the magnetostriction effect, causing the mechanical vibration and noise of the core and winding to increase. Under long-term operation, internal fasteners may gradually loosen due to vibration, eventually posing a serious threat to the safe operation of the equipment. As can be seen, the direct current bias effect has an undeniable harmful effect on the stable operation of the high-frequency transformer.

[0004] As an improvement, most existing detection methods for direct current bias are based on current signal measurement, such as series connection of Hall sensors in the winding or configuration of a dedicated direct current monitoring circuit to capture the direct current components in the excitation current. Although this method can accurately reflect the direct current bias situation, its system structure is complex, requires additional hardware support, increases the cost, and reduces the overall integration. For high-frequency transformers that pursue miniaturization and high power density, this method is difficult to meet the actual application requirements. At the same time, most high-frequency transformers currently in operation do not have a direct current bias detection device, so related fault risks are difficult to discover in time. Therefore, as described above, the current detection method for direct current bias mostly relies on current sensors or direct current monitoring circuits, and lacks effective monitoring means for the core magnetostriction, vibration enhancement and noise increase caused by direct current bias, making it difficult to directly link vibration signals with direct current bias state, and the online evaluation capability of the transformer operation state needs to be further optimized. SUMMARY

[0005] The application provides a DC bias fault diagnosis method for high-frequency transformer vibration signals and a related device, aiming to solve the problem that current DC bias detection methods mostly rely on current sensors or DC monitoring circuits, lack effective monitoring means for core magnetostriction, vibration enhancement and noise increase caused by DC bias, and are difficult to directly establish a connection between vibration signals and DC bias states, and the online evaluation capability of transformer operating states needs to be further optimized.

[0006] To achieve the above-mentioned purpose, the application adopts the following technical solutions: The DC bias fault diagnosis method for high-frequency transformer vibration signals comprises the following steps: S1, collecting vibration signals on the surface of a clamp of a high-frequency transformer under different operating conditions; S2, performing fast Fourier transform on the vibration signals on the surface of the clamp of the high-frequency transformer under different operating conditions to obtain the amplitudes of the vibration signals at each frequency; S3, calculating the frequency proportion of the vibration signals, the odd-even harmonic ratio of the vibration signals and the vibration entropy of the vibration signals based on the amplitudes of the vibration signals at each frequency; and calculating a DC bias judgment characteristic value based on the frequency proportion, the odd-even harmonic ratio and the vibration entropy; The frequency proportion is the proportion of harmonic components at each frequency in the total energy of the vibration signals, the odd-even harmonic ratio is the ratio of the total power of harmonics in a preset odd harmonic frequency range to the total power of harmonics in a preset even harmonic frequency range, and the vibration entropy is a parameter representing the degree of disorder of the energy distribution of the vibration signals calculated based on the frequency proportion; S4, comparing the DC bias judgment characteristic value with a preset threshold to judge the DC bias state of the high-frequency transformer and complete the DC bias fault diagnosis of the high-frequency transformer vibration signals.

[0007] In some embodiments, in S1, the collection of the vibration signals on the surface of the clamp of the high-frequency transformer under different operating conditions is based on a vibration acceleration sensor installed on the surface of the clamp of the high-frequency transformer.

[0008] In some embodiments, in S2, the fast Fourier transform is used to convert time-domain vibration signals into frequency-domain signals, and then the amplitudes of the vibration signals at each frequency are obtained.

[0009] In some embodiments, in S3, the DC bias judgment characteristic value is calculated as follows: ; Wherein, is the DC bias judgment characteristic value, is the odd-even harmonic ratio of the vibration signals, is the vibration entropy of the vibration signals.

[0010] Further, in S3, the frequency ratio of the vibration signal is obtained by the following formula: ; wherein, is the frequency ratio, is the frequency of the vibration signal spectrum collected by the system, is the amplitude corresponding to the frequency in the vibration spectrum, is the maximum value of the frequency in the vibration spectrum collected by the system.

[0011] Further, in S3, the odd-even harmonic ratio of the vibration signal is obtained by the following formula: ; wherein, is the total power of the odd harmonic of the vibration spectrum, is the total power of the even harmonic of the vibration spectrum; The vibration entropy of the vibration signal is calculated by the following formula: ; wherein, is the vibration entropy of the vibration signal.

[0012] In some embodiments, in S3, determining the DC bias state comprises: when the DC bias judgment characteristic value is less than the first preset threshold, it is determined that there is no DC bias; when the DC bias judgment characteristic value is equal to or between the first preset threshold and the second preset threshold, it is determined that there is a slight DC bias; when the DC bias judgment characteristic value is greater than the second preset threshold, it is determined that the DC bias is serious.

[0013] The application also provides a DC bias fault diagnosis system for high-frequency transformer vibration signals, which is used to implement the high-frequency transformer vibration signal DC bias fault diagnosis method described above, and comprises a vibration signal acquisition module, a vibration signal processing module, a DC bias judgment characteristic value calculation module, and a DC bias state determination module, wherein: The vibration signal acquisition module is used to acquire the vibration signals of the clamping piece surface of the high-frequency transformer under different working conditions. The vibration signal processing module is used to perform fast Fourier transform on the vibration signals of the clamping piece surface of the high-frequency transformer under different working conditions to obtain the amplitude of the vibration signals at each frequency. ​The direct current bias judgment characteristic value calculation module is configured to calculate the frequency proportion of the vibration signal, the odd-even harmonic ratio of the vibration signal and the vibration entropy of the vibration signal based on the amplitudes of the vibration signal at each frequency; and calculate the direct current bias judgment characteristic value based on the frequency proportion, the odd-even harmonic ratio and the vibration entropy; The frequency proportion is the proportion of the harmonic component at each frequency in the total energy of the vibration signal, the odd-even harmonic ratio is the ratio of the total power of the harmonic in the preset odd harmonic frequency range to the total power of the harmonic in the preset even harmonic frequency range, and the vibration entropy is a parameter representing the disorder degree of the energy distribution of the vibration signal calculated based on the frequency proportion; The direct current bias state judgment module is configured to compare the direct current bias judgment characteristic value with a preset threshold, judge the direct current bias state of the high-frequency transformer, and complete the direct current magnetic bias fault diagnosis of the high-frequency transformer vibration signal.

[0014] The present application also provides a computer device, which comprises a memory, a processor and a computer program stored in the memory and executable on the processor, and the processor implements the steps of the above-mentioned direct current magnetic bias fault diagnosis method of the high-frequency transformer vibration signal when executing the computer program.

[0015] The present application also provides a computer readable storage medium, which stores a computer program, and the steps of the above-mentioned direct current magnetic bias fault diagnosis method of the high-frequency transformer vibration signal are implemented when the computer program is executed by the processor.

[0016] Compared with the prior art, the direct current magnetic bias fault diagnosis method of the high-frequency transformer vibration signal and the related device have the following beneficial effects: The direct current magnetic bias fault diagnosis method of the high-frequency transformer vibration signal firstly utilizes the close relationship between the magnetostriction effect of the high-frequency transformer core and the vibration response, realizes the discrimination of the direct current magnetic bias state through the collection and analysis of the external vibration signal, and avoids the complex link of detecting the additional direct current component of the excitation current. Compared with the traditional method which depends on the current sensor or the special direct current monitoring circuit, the present application does not need to change the original electrical structure, has higher system integration, and is more convenient to realize. The detection device of the present application can be directly integrated into the existing high-frequency transformer vibration monitoring system, the detection process is flexible, the cost is low, and the feasibility of engineering application can be significantly improved. The present application not only reduces the complexity of detection and maintenance, but also realizes online monitoring under the normal operation condition of the transformer, can discover potential fault hidden dangers in advance, can effectively make up for the deficiency of the existing magnetostriction and vibration monitoring caused by the direct current magnetic bias, provides technical support for the operation state evaluation of the high-frequency transformer, improves the feasibility and application value of the direct current magnetic bias hidden danger detection, and has engineering applicability. BRIEF DESCRIPTION OF DRAWINGS

[0017] The accompanying drawings, which are included to provide a further understanding of the application and are incorporated in and constitute a part of this application, illustrate embodiments of the application and together with the description serve to explain the application. In the drawings, which are incorporated in and constitute a part of this specification, embodiments of the application and various objects and illustrative embodiments thereof are described.

[0018] Figure 1 The flowchart of the DC bias fault diagnosis method of the high-frequency transformer vibration signal of the application. DETAILED DESCRIPTION

[0019] In order to make the objects, technical solutions and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be described clearly and completely below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only some of the embodiments of the present application but not all of the embodiments. The components of the embodiments of the present application described and shown in the drawings can be arranged and designed in various different configurations.

[0020] Therefore, the following detailed description of the embodiments of the present application provided in the drawings is not intended to limit the scope of the claimed application, but merely represents the selected embodiments of the application. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative work are within the scope of protection of the present application It should be noted that, in this document, the terms "comprising", "containing" or any other variant thereof are intended to cover non-exclusive inclusion, so that a process, method, article or apparatus that includes a list of elements not only includes those elements, but also includes other elements not explicitly listed, or further includes elements inherent in such a process, method, article or apparatus without more limitations. The element defined by the phrase "comprising a" does not exclude the presence of additional identical elements in the process, method, article or apparatus that includes the element It should be noted that the apparatus and methods disclosed in the embodiments herein can also be implemented in other ways than those described above without departing from the spirit and essential characteristics of the embodiments. The above-described apparatus embodiments are merely illustrative, and the flowcharts and block diagrams in the accompanying drawings show only possible implementations according to the embodiments herein, and this is in terms of the architectures, functions, and operations of the apparatus, method and computer program product possible implementations. In this regard, each block in the flowcharts or block diagrams can represent a module, a program segment or a portion of code which comprises one or more executable instructions for implementing the specified logical function. It should also be noted that in some alternative implementations, the functions noted in the blocks can occur in a different order than that noted in the figures. For example, two blocks noted in succession can in fact be executed substantially concurrently or in the reverse order, depending on the functionality involved. It should also be noted that each block in the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, can be implemented by a dedicated hardware-based system that performs specified functions or actions, or can be implemented using a combination of dedicated hardware and computer instructions In addition, each functional module in the various embodiments herein can be integrated together to form an independent part, or each module can exist independently, or two or more modules can be integrated to form an independent part.

[0021] The existing high-frequency transformer DC bias detection method mostly depends on the current sensor or DC monitoring circuit, and although this kind of method can accurately reflect the DC component in the excitation current, the system structure is complex, the cost is high, and it is contrary to the miniaturization and high power density design goal of the high-frequency transformer. In most engineering applications, such detection devices are difficult to mass integrate and popularize, leading to the fact that the DC bias hidden danger is still difficult to find and diagnose in time. At the same time, the existing technology lacks effective monitoring means for the core magnetostriction, vibration enhancement and noise increase caused by DC bias, and cannot directly establish the connection between the vibration signal and the DC bias state, thereby limiting the online evaluation ability of the transformer running state, so it is urgent to propose a DC bias fault diagnosis method suitable for the running environment of the high-frequency transformer, so as to improve the effectiveness and applicability of the DC bias fault diagnosis.

[0022] The DC bias fault diagnosis method for the vibration signal of the high-frequency transformer of the application comprises the following steps: S1, collecting the vibration signal of the clamping piece surface of the high-frequency transformer under different working conditions; S2, performing fast Fourier transform on the vibration signal of the clamping piece surface of the high-frequency transformer under different working conditions to obtain the amplitude of the vibration signal at each frequency; S3, based on the amplitude of the vibration signal at each frequency, calculate the frequency proportion of the vibration signal, the odd-even harmonic ratio of the vibration signal and the vibration entropy of the vibration signal; based on the frequency proportion, the odd-even harmonic ratio and the vibration entropy, calculate the direct current bias judgment characteristic value; Wherein, the frequency proportion is the proportion of the harmonic component at each frequency in the total energy of the vibration signal, the odd-even harmonic ratio is the ratio of the total power of the harmonic in the preset odd harmonic frequency range to the total power of the harmonic in the preset even harmonic frequency range, and the vibration entropy is a parameter representing the degree of disorder of the energy distribution of the vibration signal calculated based on the frequency proportion; S4, compare the direct current bias judgment characteristic value with the preset threshold value, judge the direct current bias state of the high-frequency transformer, and complete the direct current magnetic fault diagnosis of the high-frequency transformer vibration signal.

[0023] The direct current magnetic fault diagnosis method of the high-frequency transformer vibration signal utilizes the strong correlation between the high-frequency transformer core and the clamping piece vibration and the internal magnetization state, realizes the online detection and judgment of the direct current magnetic bias through the analysis of the external vibration signal. Compared with the traditional current monitoring method, the present application has the advantages of high system integration, simple implementation and low cost, and can realize fault diagnosis without changing the original structure of the high-frequency transformer, and improve the effectiveness of the detection of the direct current magnetic bias.

[0024] Specifically, the present application realizes fault judgment by collecting vibration signals and performing frequency domain analysis, and calculating characteristic parameters, avoids introducing additional sensors in the electrical circuit by collecting the vibration signals on the surface of the high-frequency transformer clamping piece, and is more consistent with the miniaturization and high power density design goals of the high-frequency transformer; the vibration signal is converted into frequency domain data by using fast Fourier transform, which can deeply mine the harmonic characteristics in the signal, so as to more accurately reflect the core magnetostriction and vibration changes caused by the direct current magnetic bias; by calculating the frequency proportion, the odd-even harmonic ratio and the vibration entropy characteristic parameters, the distribution of vibration energy and the harmonic component can be comprehensively evaluated, so as to enhance the recognition ability of the direct current magnetic bias state. The frequency proportion reflects the contribution of each frequency component in the total energy, the odd-even harmonic ratio highlights the harmonic asymmetry caused by the direct current magnetic bias, and the vibration entropy quantifies the energy disorder degree of the vibration signal, improving the comprehensiveness and reliability of the diagnosis. Finally, by comparing the direct current bias judgment characteristic value with the preset threshold value, the standardized judgment of the direct current magnetic bias state is realized, which can realize online monitoring without changing the original structure of the transformer, not only reduces the detection complexity and cost, but also improves the accuracy and real-time performance of the fault diagnosis, providing a guarantee for the safe operation of the high-frequency transformer.

[0025] The application ensures the directness and accuracy of vibration signal collection by using a vibration acceleration sensor installed on the surface of a high-frequency transformer clamp, because the clamp surface is a key conduction part of transformer mechanical vibration and can effectively capture the magnetostriction vibration of the core and winding caused by DC bias magnetization.

[0026] The application converts the time-domain vibration signal into a frequency-domain signal by using fast Fourier transform to obtain the amplitude at each frequency, thereby ensuring the normativity and repeatability of frequency-domain analysis and providing accurate basic data for subsequent feature calculation.

[0027] The application also provides a DC bias fault diagnosis system for high-frequency transformer vibration signals, which comprises a vibration signal collection module, a vibration signal processing module, a DC bias judgment feature value calculation module and a DC bias state judgment module. The vibration signal collection module is used to collect the vibration signals of the clamp surface of the high-frequency transformer under different working conditions. The vibration signal processing module is used to perform fast Fourier transform on the vibration signals of the clamp surface of the high-frequency transformer under different working conditions to obtain the amplitudes of the vibration signals at each frequency. The DC bias judgment feature value calculation module is used to calculate the frequency proportion of the vibration signal, the odd-even harmonic ratio of the vibration signal and the vibration entropy of the vibration signal based on the amplitudes of the vibration signal at each frequency, and calculate the DC bias judgment feature value based on the frequency proportion, the odd-even harmonic ratio and the vibration entropy. The frequency proportion is the proportion of the harmonic component at each frequency in the total energy of the vibration signal, the odd-even harmonic ratio is the ratio of the total power of the harmonic in the preset odd harmonic frequency range to the total power of the harmonic in the preset even harmonic frequency range, and the vibration entropy is a parameter representing the degree of disorder of the energy distribution of the vibration signal calculated based on the frequency proportion. The DC bias state judgment module is used to compare the DC bias judgment feature value with a preset threshold, judge the DC bias state of the high-frequency transformer and complete the DC bias fault diagnosis of the high-frequency transformer vibration signal.

[0028] The application also provides a computer device comprising a memory, a processor and a computer program stored in the memory and executable on the processor, and the processor implements the steps of the DC bias fault diagnosis method for high-frequency transformer vibration signals when executing the computer program.

[0029] The present invention also provides a computer-readable storage medium storing a computer program, which, when executed by a processor, implements the steps of the DC bias fault diagnosis method for high-frequency transformer vibration signals as described above.

[0030] like Figure 1 As shown below, the DC bias fault diagnosis method for high-frequency transformer vibration signals of the present invention will be further described in detail through specific embodiments.

[0031] A method for diagnosing DC bias magnetic faults in high-frequency transformer vibration signals, implemented through the following steps: A vibration acceleration sensor is installed on the surface of the high-frequency transformer clamp, and the vibration signal of the clamp surface under different operating conditions is measured by the vibration acceleration sensor. The vibration signals of the clamp surface of the high-frequency transformer under different operating conditions were subjected to Fast Fourier Transform (FFT) to obtain the frequencies. The amplitude corresponding to the location ; Using the amplitudes of vibrations at each frequency, the frequency weight is determined. : Based on formula ; in, Frequency proportion The frequency of the vibration signal spectrum acquired by the system. In the vibration spectrum The amplitude corresponding to the location This represents the maximum frequency value in the vibration spectrum collected by the system.

[0032] ; Frequency proportion mainly characterizes frequency f The proportion of harmonic components at a given location (calculated from an energy perspective). Calculate the odd-even harmonic ratio of the vibration signal: ; In the formula, the numerator is the total power of odd harmonics below 20kHz, and the denominator is the total power of even harmonics below 1kHz; Calculate the vibration entropy of the vibration signal ; DC bias judgment characteristic value .

[0033] The DC bias of the high-frequency power transformer is determined based on the characteristic values ​​of the different vibration signals obtained. when At that time, there is no DC bias; when When the DC bias is slight, When the DC bias is slight, When the DC bias is severe.

[0034] The specific calculation of the DC bias judgment characteristic value of the present application, i.e., the ratio of the odd-even harmonic ratio and the vibration entropy, combines the harmonic characteristics and energy distribution disorder in the vibration signal, creates a comprehensive index to quantify the degree of DC bias, and through the use of the odd-even harmonic ratio, the harmonic asymmetry phenomenon caused by the DC bias can be captured, and the vibration entropy reflects the dispersion of the vibration energy, and the combination of the two makes the characteristic value more comprehensively reflect the fault state, and enhances the practicability. The specific calculation of the frequency proportion of the present application quantifies the proportion of each frequency component in the total vibration energy through the square sum normalization processing of each frequency amplitude, can effectively highlight the contribution of the key frequency components in the vibration signal, avoids the deviation caused by the signal amplitude fluctuation, and improves the stability of the feature extraction. The specific calculation of the odd-even harmonic ratio and the vibration entropy of the present application, wherein the odd-even harmonic ratio is calculated by defining the frequency range and power of the odd and even harmonics, and the vibration entropy is solved based on the frequency proportion, and the vibration characteristics caused by the DC bias are optimized.

[0035] The present application sets the specific threshold condition for judging the DC bias state, and divides the degree of DC bias into three levels of nonexistence, slightness and severity through the first preset threshold and the second preset threshold. The diagnostic result is more detailed, which is convenient for users to take corresponding maintenance measures according to different degrees, improves the practicability and guiding value of the method, and enhances the operability and reliability of the diagnostic method.

[0036] Finally, it should be noted that: the above described, only for the preferred embodiments of the present application, not to the present application in any form of limitation; for ordinary skilled in the art can be shown in the specification and the above described while smoothly implementing the present application, using the above disclosed technical content and make a little change, modification and evolution of equivalent changes, such as the equivalent embodiments of the present application; at the same time, any equivalent changes of the above embodiments according to the essential technology of the present application, all still belong to the protection scope of the technical solutions of the present application.

Claims

1. A DC bias fault diagnosis method for high-frequency transformer vibration signals, characterized in that, The method comprises the following steps: S1, collecting vibration signals of a clamping piece surface of a high-frequency transformer under different working conditions; S2, performing fast Fourier transform on the vibration signals of the clamping piece surface of the high-frequency transformer under different working conditions to obtain amplitudes of the vibration signals at each frequency; S3, calculating frequency proportions of the vibration signals, odd-even harmonic ratios of the vibration signals, and vibration entropy of the vibration signals based on the amplitudes of the vibration signals at each frequency; and calculating a DC bias judgment characteristic value based on the frequency proportions, the odd-even harmonic ratios, and the vibration entropy; The frequency proportion is a proportion of harmonic components at each frequency in total energy of the vibration signals, the odd-even harmonic ratio is a ratio of total power of harmonics in a preset odd harmonic frequency range to total power of harmonics in a preset even harmonic frequency range, and the vibration entropy is a parameter representing a degree of disorder of energy distribution of the vibration signals and is calculated based on the frequency proportions; S4, comparing the DC bias judgment characteristic value with a preset threshold value to judge a DC bias state of the high-frequency transformer and complete DC bias fault diagnosis of the vibration signals of the high-frequency transformer.

2. The method according to claim 1, wherein In the S1, the vibration signals of the clamping piece surface of the high-frequency transformer under different working conditions are collected based on a vibration acceleration sensor, and the vibration acceleration sensor is installed on the clamping piece surface of the high-frequency transformer.

3. The method according to claim 1, wherein the method is characterized by, In the S2, the fast Fourier transform is used to convert time-domain vibration signals into frequency-domain signals to obtain the amplitudes of the vibration signals at each frequency.

4. The method according to claim 1, wherein In the S3, the DC bias judgment characteristic value is calculated as follows: ； wherein, is a DC bias judgment characteristic value, is a vibration signal odd-even harmonic ratio, is a vibration entropy of the vibration signal.

5. The method according to claim 4, wherein the DC bias fault diagnosis method of the high-frequency transformer vibration signal is characterized by, In the S3, the frequency proportion of the vibration signals is obtained by the following formula: ； Wherein, is the frequency ratio, is the frequency of the vibration signal spectrum collected by the system, is the amplitude corresponding to the frequency in the vibration spectrum, is the amplitude corresponding to the frequency in the vibration spectrum, is the maximum value of the frequency in the vibration spectrum collected by the system.

6. The method according to claim 5, wherein the DC bias fault diagnosis of the high frequency transformer vibration signal is characterized by, In the S3, the odd-even harmonic ratio of the vibration signals is calculated by the following formula: ； wherein, the total power of the odd harmonics of the vibration spectrum, is the total power of the even harmonics of the vibration spectrum; The vibration entropy of the vibration signals is calculated by the following formula: ； wherein, is the vibrational entropy of the vibrational signal.

7. The method according to claim 1, wherein In the S3, the DC bias state is judged as follows: When the DC bias judgment characteristic value is less than a first preset threshold value, it is judged that there is no DC bias; When the DC bias judgment characteristic value is equal to or between the first preset threshold value and a second preset threshold value, it is judged that there is slight DC bias; When the DC bias judgment characteristic value is greater than the second preset threshold value, it is judged that the DC bias is serious.

8. A DC bias fault diagnosis system for high-frequency transformer vibration signals, characterized by, The system is used to implement the DC bias fault diagnosis method of the vibration signals of the high-frequency transformer according to any one of claims 1-7, and the system comprises a vibration signal collection module, a vibration signal processing module, a DC bias judgment characteristic value calculation module, and a DC bias state judgment module, wherein: The vibration signal collection module is used to collect the vibration signals of the clamping piece surface of the high-frequency transformer under different working conditions; The vibration signal processing module is used to perform fast Fourier transform on the vibration signals of the clamping piece surface of the high-frequency transformer under different working conditions to obtain amplitudes of the vibration signals at each frequency; The DC bias judgment characteristic value calculation module is used to calculate frequency proportions of the vibration signals, odd-even harmonic ratios of the vibration signals, and vibration entropy of the vibration signals based on the amplitudes of the vibration signals at each frequency; and calculate a DC bias judgment characteristic value based on the frequency proportions, the odd-even harmonic ratios, and the vibration entropy; The frequency ratio is the ratio of the harmonic component at each frequency in the total energy of the vibration signal, the odd-even harmonic ratio is the ratio of the total power of the harmonics in the preset odd harmonic frequency range to the total power of the harmonics in the preset even harmonic frequency range, and the vibration entropy is a parameter representing the degree of disorder of the energy distribution of the vibration signal calculated based on the frequency ratio. The DC bias state determination module is configured to compare the DC bias judgment characteristic value with a preset threshold value, determine the DC bias state of the high-frequency transformer, and complete the DC bias fault diagnosis of the high-frequency transformer vibration signal.

9. A computer device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, The processor executes the computer program to implement the steps of the DC bias fault diagnosis method of the high-frequency transformer vibration signal according to any one of claims 1-7.

10. A computer-readable storage medium storing a computer program, the computer program comprising instructions that, when executed by a computer, cause the computer to perform the method of any one of claims 1 to 9. The computer program is executed by the processor to implement the steps of the DC bias fault diagnosis method of the high-frequency transformer vibration signal according to any one of claims 1-7.

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