A fault analysis method and related apparatus

Abstract

The embodiment of the application discloses a fault analysis method and related device, and processing equipment can determine the energy band quantity corresponding to the vibration signal to be analyzed first, and the energy band quantity can reflect whether the transformer is disturbed by harmonic interference. In response to the energy band quantity being greater than a preset threshold, the processing equipment can determine that the transformer has received harmonic interference, thereby determining a harmonic interference vibration signal. Then, the processing equipment can determine a harmonic characteristic frequency used to reflect the vibration characteristics of the transformer to be analyzed under harmonic interference, determine whether the transformer to be analyzed has a fault according to the similarity between the harmonic characteristic frequencies corresponding to the plurality of harmonic interference vibration signals, and if the similarity is high, it indicates that the transformer has relatively stable vibration characteristics in a plurality of time periods, and there is a high probability that the transformer has no fault, thereby realizing fault analysis on the transformer disturbed by harmonic interference and accurate judgment on the transformer fault.

Description

Technical Field

[0001] This application relates to the field of data analysis technology, and in particular to a fault analysis method and related apparatus. Background Technology

[0002] With the development of converter stations, substations, ultra-high voltage direct current transmission projects, and the grid connection of new energy power generation such as wind and solar power, a large number of nonlinear devices such as switching devices and semiconductor components are being used in power systems. While these devices improve the flexibility and efficiency of power grid operation and control, they inevitably inject a large number of harmonic sources into the power system. The large amount of harmonic injection in the power grid has a significant impact on the vibration characteristics of traditional transformers. The influence of harmonics on vibration characteristics and the influence of faults on vibration characteristics are often overlapping and difficult to distinguish.

[0003] In related technologies, there is a lack of a method to detect faults in transformers subjected to harmonic interference, which makes it impossible to determine whether a transformer has malfunctioned when it is subjected to harmonic interference, and thus cannot guarantee the normal operation of the transformer. Summary of the Invention

[0004] To address the aforementioned technical problems, this application provides a fault analysis method that can accurately analyze the faults of transformers that may be affected by harmonic interference.

[0005] The embodiments of this application disclose the following technical solutions:

[0006] In a first aspect, embodiments of this application disclose a fault analysis method, characterized in that the method includes:

[0007] A set of vibration signals to be analyzed is obtained, which includes vibration signals to be analyzed corresponding to the transformer to be analyzed in multiple detection periods.

[0008] Multiple vibration signals to be analyzed are respectively used as target vibration signals to be analyzed, and the number of energy bands corresponding to the target vibration signals to be analyzed is determined.

[0009] In response to the number of energy bands being greater than a preset threshold, the target vibration signal to be analyzed is determined to be a harmonic interference vibration signal;

[0010] The harmonic characteristic frequencies corresponding to multiple harmonic interference vibration signals among the multiple vibration signals to be analyzed are determined. The harmonic characteristic frequencies are used to reflect the vibration characteristics of the transformer to be analyzed under harmonic interference.

[0011] Based on the similarity between the harmonic characteristic frequencies corresponding to the multiple harmonic interference vibration signals, it is determined whether the transformer to be analyzed has a fault.

[0012] In one possible implementation, determining whether the transformer to be analyzed is faulty based on the similarity between the harmonic characteristic frequencies corresponding to the plurality of harmonic interference vibration signals includes:

[0013] Determine the high-frequency vibration distribution vectors corresponding to the plurality of harmonic interference vibration signals;

[0014] Determine the consistency feature value of multiple high-frequency vibration distribution vectors corresponding to the multiple harmonic interference vibration signals. The consistency feature value is used to reflect the similarity between the multiple high-frequency vibration distribution vectors. The consistency feature value is the number of distribution center points of the multiple high-frequency vibration distribution vectors.

[0015] If the consistency feature value is 1, it is determined that the transformer to be analyzed has not experienced a fault;

[0016] If the consistency feature value is not 1, it is determined that the transformer to be analyzed has a fault.

[0017] In one possible implementation, determining the number of energy bands corresponding to the target vibration signal to be analyzed includes:

[0018] Determine the discrete spectrum sequence corresponding to the target vibration signal to be analyzed;

[0019] The discrete spectrum sequence is smoothed by filtering to construct a smooth spectrum sequence;

[0020] The average smoothed spectrum corresponding to the target vibration signal to be analyzed is determined based on the smoothed spectrum sequence.

[0021] The number of energy bands in the average smooth spectrum is determined as the number of energy bands corresponding to the target vibration signal to be analyzed.

[0022] In one possible implementation, determining the harmonic characteristic frequencies corresponding to the multiple harmonic interference vibration signals among the plurality of vibration signals to be analyzed includes:

[0023] The plurality of harmonic interference vibration signals are respectively taken as target harmonic interference vibration signals, and the average smooth spectrum corresponding to the target harmonic interference vibration signals is determined.

[0024] Determine the effective values ​​corresponding to the multiple energy bands in the average smooth spectrum, and the effective values ​​are used to identify the energy intensity of the excitation source that causes the generation of the energy bands;

[0025] The frequency corresponding to the energy band with the highest effective value is determined as the harmonic frequency characteristic of the target harmonic interference vibration signal.

[0026] In one possible implementation, determining the effective values ​​corresponding to the multiple energy bands in the average smoothed spectrum includes:

[0027] Each of the multiple energy bands is taken as a target energy band, and multiple local peak points are determined within the target energy band;

[0028] The effective value of the target energy band is determined based on the difference between the frequencies corresponding to the multiple local peak points and the preset frequency, as well as the peak values ​​corresponding to the multiple local peak points. The preset frequency is the frequency of the energy band not generated by harmonics.

[0029] Secondly, embodiments of this application disclose a fault analysis device, the device comprising an acquisition unit, a first determination unit, a second determination unit, a third determination unit, and a fourth determination unit:

[0030] The acquisition unit is used to acquire a set of vibration signals to be analyzed, which includes vibration signals to be analyzed corresponding to the transformer to be analyzed in multiple detection periods.

[0031] The first determining unit is used to take multiple vibration signals to be analyzed as target vibration signals to be analyzed, and determine the number of energy bands corresponding to the target vibration signals to be analyzed;

[0032] The second determining unit is used to determine the target vibration signal to be analyzed as a harmonic interference vibration signal in response to the number of energy bands being greater than a preset threshold.

[0033] The third determining unit is used to determine the harmonic characteristic frequencies corresponding to the multiple harmonic interference vibration signals among the multiple vibration signals to be analyzed. The harmonic characteristic frequencies are used to reflect the vibration characteristics of the transformer to be analyzed under harmonic interference.

[0034] The fourth determining unit is used to determine whether the transformer to be analyzed has a fault based on the similarity between the harmonic characteristic frequencies corresponding to the plurality of harmonic interference vibration signals.

[0035] In one possible implementation, the fourth determining unit is specifically used for:

[0036] Determine the high-frequency vibration distribution vectors corresponding to the plurality of harmonic interference vibration signals;

[0037] Determine the consistency feature value of multiple high-frequency vibration distribution vectors corresponding to the multiple harmonic interference vibration signals. The consistency feature value is used to reflect the similarity between the multiple high-frequency vibration distribution vectors. The consistency feature value is the number of distribution center points of the multiple high-frequency vibration distribution vectors.

[0038] If the consistency feature value is 1, it is determined that the transformer to be analyzed has not experienced a fault;

[0039] If the consistency feature value is not 1, it is determined that the transformer to be analyzed has a fault.

[0040] In one possible implementation, the first determining unit is specifically used for:

[0041] Determine the discrete spectrum sequence corresponding to the target vibration signal to be analyzed;

[0042] The discrete spectrum sequence is smoothed by filtering to construct a smooth spectrum sequence;

[0043] The average smoothed spectrum corresponding to the target vibration signal to be analyzed is determined based on the smoothed spectrum sequence.

[0044] The number of energy bands in the average smooth spectrum is determined as the number of energy bands corresponding to the target vibration signal to be analyzed.

[0045] In one possible implementation, the third determining unit is specifically used for:

[0046] The plurality of harmonic interference vibration signals are respectively taken as target harmonic interference vibration signals, and the average smooth spectrum corresponding to the target harmonic interference vibration signals is determined.

[0047] Determine the effective values ​​corresponding to the multiple energy bands in the average smooth spectrum, and the effective values ​​are used to identify the energy intensity of the excitation source that causes the generation of the energy bands;

[0048] The frequency corresponding to the energy band with the highest effective value is determined as the harmonic frequency characteristic of the target harmonic interference vibration signal.

[0049] In one possible implementation, the third determining unit is specifically used for:

[0050] Each of the multiple energy bands is taken as a target energy band, and multiple local peak points are determined within the target energy band;

[0051] The effective value of the target energy band is determined based on the difference between the frequencies corresponding to the multiple local peak points and the preset frequency, as well as the peak values ​​corresponding to the multiple local peak points. The preset frequency is the frequency of the energy band not generated by harmonics.

[0052] Thirdly, embodiments of this application disclose a computer device, which includes a processor and a memory:

[0053] The memory is used to store program code and transmit the program code to the processor;

[0054] The processor is used to execute the fault analysis method described in any one of the first aspects according to the instructions in the program code.

[0055] Fourthly, embodiments of this application disclose a computer-readable storage medium for storing a computer program for executing the fault analysis method described in any one of the first aspects.

[0056] Fifthly, embodiments of this application disclose a computer program product including instructions that, when run on a computer, cause the computer to execute the fault analysis method described in any one of the first aspects.

[0057] As can be seen from the above technical solution, this application provides a fault analysis method. First, a set of vibration signals to be analyzed is obtained, including vibration signals of the transformer to be analyzed corresponding to different detection periods. Then, these multiple vibration signals are used as target vibration signals to be analyzed, and the number of energy bands corresponding to the target vibration signals is determined. The number of energy bands indicates whether the transformer is subject to harmonic interference. If the number of energy bands exceeds a preset threshold, the processing device can determine that the transformer has received harmonic interference, thus identifying the target vibration signal as a harmonic interference vibration signal. Then, the processing device can determine the harmonic characteristic frequencies corresponding to the multiple harmonic interference vibration signals among the multiple vibration signals to be analyzed. These harmonic characteristic frequencies reflect the vibration characteristics of the transformer under harmonic interference. Based on the similarity between the harmonic characteristic frequencies corresponding to the multiple harmonic interference vibration signals, the processing device determines whether the transformer to be analyzed has a fault. If the similarity is high, it indicates that the transformer has relatively stable vibration characteristics in multiple periods, and is likely not faulty. Conversely, if the similarity is low, it indicates that the transformer's vibration is unstable in multiple periods, which is usually caused by a fault, and therefore, the transformer can be considered faulty. Therefore, this application can first determine whether a transformer is subject to harmonic interference, and can perform fault analysis on transformers subject to harmonic interference, thereby achieving accurate fault diagnosis of transformers. Attached Figure Description

[0058] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0059] Figure 1 A flowchart of a fault analysis method provided in an embodiment of this application;

[0060] Figure 2 A schematic diagram illustrating a fault analysis method in a practical application scenario provided by an embodiment of this application;

[0061] Figure 3 A schematic diagram illustrating a fault analysis method in a practical application scenario provided by an embodiment of this application;

[0062] Figure 4 A schematic diagram illustrating a fault analysis method in a practical application scenario provided by an embodiment of this application;

[0063] Figure 5 This is a structural block diagram of a fault analysis device provided in an embodiment of this application. Detailed Implementation

[0064] The embodiments of this application will now be described with reference to the accompanying drawings.

[0065] Understandably, this method can be applied to processing devices capable of fault analysis, such as terminal devices or servers with fault analysis functions. This method can be executed independently by a terminal device or server, or it can be applied in network scenarios where the terminal device and server communicate, executing in cooperation. The terminal device can be a computer, mobile phone, or similar device. The server can be an application server or a web server; in actual deployment, this server can be a standalone server or a cluster server.

[0066] See Figure 1 , Figure 1 A flowchart of a fault analysis method provided in this application embodiment, the method including:

[0067] S101: Obtain the set of vibration signals to be analyzed.

[0068] The set of vibration signals to be analyzed includes vibration signals of the transformer to be analyzed corresponding to multiple detection periods. The vibration signals to be analyzed are generated based on the vibration of the transformer to be analyzed.

[0069] S102: Take multiple vibration signals to be analyzed as target vibration signals to be analyzed, and determine the number of energy bands corresponding to the target vibration signals to be analyzed.

[0070] The purpose of using multiple vibration signals to be analyzed as target vibration signals is to achieve traversal analysis of multiple vibration signals to be analyzed. The energy band refers to the concentrated distribution band of the vibration signal on the frequency spectrum.

[0071] S103: In response to the number of energy bands being greater than a preset threshold, the target vibration signal to be analyzed is determined to be a harmonic interference vibration signal.

[0072] Research has shown that when a transformer is not subject to harmonic interference, the number of energy bands in the transformer's vibration signal spectrum is relatively uniform, typically not exceeding a preset threshold (which can be set to 3). Even in the event of a fault, energy bands will only appear in the high-frequency range, and the total number of energy bands will still not exceed the preset threshold. However, when a transformer is subject to harmonic interference, the number of energy bands increases due to the increase in the vibration excitation source. Therefore, processing equipment can analyze whether the transformer is subject to harmonic interference based on the number of energy bands.

[0073] If the number of energy bands exceeds the preset threshold, it indicates that more excitation sources have appeared to excite the transformer to vibrate compared to the normal operating state. Therefore, it can be determined that the transformer to be analyzed is subjected to harmonic interference. The processing equipment can identify the target vibration signal to be analyzed as a harmonic interference vibration signal, that is, a vibration signal with harmonic interference.

[0074] S104: Determine the harmonic characteristic frequencies corresponding to multiple harmonic interference vibration signals among multiple vibration signals to be analyzed.

[0075] The harmonic characteristic frequency is used to reflect the vibration characteristics of the transformer under harmonic interference, that is, the harmonic characteristic frequency can reflect the vibration characteristics of the transformer vibration generated by the harmonic excitation source.

[0076] S105: Determine whether the transformer to be analyzed has a fault based on the similarity between the harmonic characteristic frequencies corresponding to multiple harmonic interference vibration signals.

[0077] It is understandable that if a transformer is not faulty, its vibration characteristics should be relatively consistent, and therefore the vibration features exhibited across multiple time periods should also be relatively consistent. However, when a transformer is faulty, due to the instability of its own vibration characteristics, the vibration characteristics generated at different time periods after a harmonic excitation source is applied to the transformer will vary significantly. Based on this, the processing equipment can determine whether the transformer under analysis is faulty based on the similarity of the harmonic interference vibration signals at different time periods. That is, if the similarity is high, it indicates that the transformer still has relatively consistent vibration characteristics under harmonic interference, and the probability of fault is low; if the similarity is low, it indicates that the transformer's vibration characteristics fluctuate greatly under harmonic interference, and therefore the probability of fault is high. Thus, the processing equipment can analyze whether the transformer under analysis is faulty based on similarity.

[0078] As can be seen from the above technical solution, this application provides a fault analysis method. First, a set of vibration signals to be analyzed is obtained, including vibration signals of the transformer to be analyzed corresponding to different detection periods. Then, these multiple vibration signals are used as target vibration signals to be analyzed, and the number of energy bands corresponding to the target vibration signals is determined. The number of energy bands indicates whether the transformer is subject to harmonic interference. If the number of energy bands exceeds a preset threshold, the processing device can determine that the transformer has received harmonic interference, thus identifying the target vibration signal as a harmonic interference vibration signal. Then, the processing device can determine the harmonic characteristic frequencies corresponding to the multiple harmonic interference vibration signals among the multiple vibration signals to be analyzed. These harmonic characteristic frequencies reflect the vibration characteristics of the transformer under harmonic interference. Based on the similarity between the harmonic characteristic frequencies corresponding to the multiple harmonic interference vibration signals, the processing device determines whether the transformer to be analyzed has a fault. If the similarity is high, it indicates that the transformer has relatively stable vibration characteristics in multiple periods, and is likely not faulty. Conversely, if the similarity is low, it indicates that the transformer's vibration is unstable in multiple periods, which is usually caused by a fault, and therefore, the transformer can be considered faulty. Therefore, this application can first determine whether a transformer is subject to harmonic interference, and can perform fault analysis on transformers subject to harmonic interference, thereby achieving accurate fault diagnosis of transformers.

[0079] In one possible implementation, when determining whether the transformer to be analyzed has a fault based on the similarity between the harmonic characteristic frequencies corresponding to the plurality of harmonic interference vibration signals, the processing device can first determine the high-frequency vibration distribution vector corresponding to the plurality of harmonic interference vibration signals, which can reflect the vibration characteristics of the transformer to be analyzed.

[0080] Then, the processing device can determine the consistency feature value of multiple high-frequency vibration distribution vectors corresponding to the multiple harmonic interference vibration signals. The consistency feature value is used to reflect the similarity between the multiple high-frequency vibration distribution vectors. The consistency feature value is the number of distribution center points of the multiple high-frequency vibration distribution vectors. That is, if the similarity between the multiple high-frequency vibration distribution vectors is high, then there is usually only one distribution center point, and the consistency feature value is 1. If the similarity between the multiple high-frequency vibration distribution vectors is low, then multiple distribution center points will be generated, and the consistency feature value is a number greater than 1.

[0081] Therefore, if the consistency feature value is 1, the processing device can determine that the similarity between multiple high-frequency vibration distribution vectors is high, thereby determining that the transformer to be analyzed has not failed; if the consistency feature value is not 1, the processing device can determine that the similarity between multiple high-frequency vibration distribution vectors is low, thereby determining that the transformer to be analyzed has failed.

[0082] In one possible implementation, the processing device can determine the number of energy bands corresponding to the target vibration signal to be analyzed in the following way: The processing device can first determine the discrete spectrum sequence corresponding to the target vibration signal to be analyzed, and then perform smoothing filtering on the discrete spectrum sequence to construct a smooth spectrum sequence.

[0083] The processing device can determine the average smooth spectrum corresponding to the target vibration signal to be analyzed based on the smooth spectrum sequence, and then determine the number of energy bands in the average smooth spectrum as the number of energy bands corresponding to the target vibration signal to be analyzed.

[0084] In one possible implementation, the processing device can determine the harmonic characteristic frequencies corresponding to multiple harmonic interference vibration signals among the multiple vibration signals to be analyzed in the following way. It is understood that these harmonic characteristic frequencies are used to reflect the vibration characteristics of the transformer under harmonic interference; therefore, the stronger the harmonic excitation, the more obvious the vibration characteristics reflected by the harmonic characteristic frequencies. Thus, the processing device can determine the harmonic characteristic frequencies based on the energy generated by a stronger excitation source.

[0085] The processing device can use the multiple harmonic interference vibration signals as target harmonic interference vibration signals, determine the average smooth spectrum corresponding to the target harmonic interference vibration signals, and then determine the effective values ​​corresponding to multiple energy bands in the average smooth spectrum. These effective values ​​are used to identify the energy intensity of the excitation source that causes the energy bands to form. The processing device can then determine the frequency corresponding to the energy band with the highest effective value as the harmonic frequency characteristic corresponding to the target harmonic interference vibration signal.

[0086] Specifically, in one possible implementation, when determining the effective value corresponding to each energy band, the processing device can use the multiple energy bands as target energy bands, then determine multiple local peak points included in the target energy bands, and then determine the effective value corresponding to the target energy bands based on the difference between the frequencies corresponding to the multiple local peak points and a preset frequency, as well as the peak values ​​corresponding to the multiple local peak points. The preset frequency is the frequency corresponding to the energy bands not generated by harmonics. The difference between the frequency and the preset frequency reflects the magnitude of the excitation source corresponding to the energy band.

[0087] To facilitate understanding of the technical solutions provided in the embodiments of this application, the fault analysis method provided in the embodiments of this application will be introduced next in conjunction with a practical application scenario.

[0088] See Figure 2 The fault analysis method may include the following steps:

[0089] Step (1): The processing equipment can arrange multiple vibration sensors on the surface of the transformer tank directly opposite the winding position, and collect the vibration signals of each vibration sensor under normal energized operation conditions for a certain length at regular intervals. For each vibration sensor, calculate the Fourier transform of each vibration sampling sample of the vibration sensor within a day, and extract the amplitude of the 50Hz and its harmonic vibrations to construct a discrete spectrum sequence. Then, average the spectrum sequences of all measurement points to obtain the average discrete spectrum sequence.

[0090] Step (2): The processing device can perform smoothing filtering on the discrete spectrum sequence of vibration at each measuring point, construct a smooth spectrum sequence, and average the smooth spectrum sequences of vibration at each measuring point to obtain the average smooth spectrum.

[0091] Step (3): The processing device can analyze the peak value of the average smooth spectrum and identify all effective energy bands in the smooth spectrum. If the number of effective energy bands in the average smooth spectrum is less than or equal to 3, it can be determined that the harmonic interference level of the current excitation source is close to 0. When the number of effective energy bands in the average smooth spectrum is greater than 3, it can be determined that the current excitation source may be affected by harmonics.

[0092] Step (4): The processing device can average and smooth the discrete spectrum of all samples affected by harmonics at all measurement points to obtain the average smooth spectrum, extract the effective energy band peak frequency and amplitude of all smooth spectrum, and perform effectiveness scoring, and select the frequency with the highest effectiveness score as the harmonic characteristic frequency.

[0093] Step (5): For each vibration sample affected by harmonics from a vibration sensor, extract the amplitude of the high-frequency characteristic frequency of the harmonics and construct a high-frequency vibration distribution vector;

[0094] Step (6): Construct a spatiotemporal matrix of vibration distribution vector for continuous monitoring for 24 hours, extract high-frequency distribution consistency features, and then evaluate the transformer operating status based on these features.

[0095] Furthermore, the number of vibration sensors arranged in step (1) can be set to K. The vibration signal of each vibration sensor and the current signal of the power transformer are collected once every Δt time interval within a day. The sampling time is T seconds, the sampling frequency is f, N is a natural number greater than 1, Δt should be greater than 1 minute, and T should be greater than 0.02 seconds.

[0096] Furthermore, the specific implementation of step (1) is as follows:

[0097] A1. Take one day's worth of data and divide it into multiple samples. Each sample includes vibration signals v from various vibration sensors within the same sampling time period. m,k =[v m,k (0),v m,k (1 / f),…,v m,k (T)];

[0098] Where: vm,1(t) is the signal value of the vibration signal of the first vibration sensor in the m-th sample at time t, vm,K(x) is the signal value of the vibration signal of the K-th vibration sensor in the m-th sample at time t, t=0,1 / f,2*1 / f,...,T, 0 is the sampling start time of the m-th sample, m is a natural number and 1≤m≤M, M is the number of samples;

[0099] A2. Calculate v m,n N-point Discrete Fourier Transform V m,n and I m :

[0100] in:

[0101] A3. Finding V m,n The 50Hz frequency and its harmonics components:

[0102]

[0103] V m,n,50l =V m,n (k l )

[0104] Where k l =round(50 / f*N*l);

[0105] A4. Construct a discrete spectral sequence of 50Hz and its harmonics.

[0106] V m,n,50 =[V m,n,50 V m,n,100 … V m,n,3000 ]

[0107] Furthermore, the specific implementation of step (2) is as follows:

[0108] A1. Perform local scatter plot smoothing (LOESS) on the discrete spectral sequence of vibration at each measuring point to obtain a smoothed spectral sequence:

[0109]

[0110] Where smooth() represents smoothing;

[0111] A2. Then average the smoothed spectral sequences of all measurement points to obtain the average smoothed spectral sequence:

[0112]

[0113] Where N is the number of vibration sensors.

[0114] Furthermore, the specific implementation of step (3) is as follows:

[0115] A1. Traverse the average smoothed spectral sequence to find all effective local peaks. One of the following conditions must be met:

[0116] Condition one:

[0117] or

[0118] Condition two:

[0119] and and

[0120] Where max() means to retrieve the maximum value in the sequence;

[0121] A2. Count the number of effective local peaks, Num.

[0122] A3. If the number of effective energy bands Num in the average smooth spectrum is less than or equal to 3, then the harmonic interference level of the current excitation source can be determined to be close to 0.

[0123] A4. When the number of effective energy bands Num in the average smooth spectrum is greater than 3, it is determined that the current excitation source may be affected by harmonics.

[0124] Furthermore, the specific implementation method of step (4) is as follows: Figure 3 As shown:

[0125] A1. Traverse the 24-hour vibration samples to find all vibration samples affected by harmonics, and construct the total average discrete spectrum sequence of 50Hz and its harmonic components.

[0126]

[0127] Where m′ represents the sample number affected by harmonics, and M′ represents the total number of samples affected by harmonics.

[0128] A2. Perform local scatter smoothing on the total average discrete spectrum sequence to obtain the total average smoothed spectrum sequence:

[0129]

[0130] A3. Traverse the overall average smoothed spectrum sequence to find all effective local peaks, and denote the effective local peaks as p. i (f i ), where i represents the i-th peak point, f i This indicates the frequency of the i-th peak.

[0131] A4. Construct a validity score for all local peak frequencies:

[0132]

[0133] A5. Select the frequency with the highest validity score as the harmonic characteristic frequency:

[0134]

[0135] Furthermore, the specific implementation of step (5) is as follows:

[0136] A1. For each vibration signal sample from a vibration sensor affected by harmonics, extract the amplitude of the high-frequency characteristic harmonics:

[0137]

[0138] in Let m′ be the vibration amplitude of the nth vibration sensor at the characteristic frequency of the harmonic, which is the sample affected by the harmonic.

[0139] A2. Construct the high-frequency vibration distribution vector;

[0140] VHf m′ =[VHf m′,1 ,VHf m′,2 ,…,VHf m′,N ]

[0141] Furthermore, the specific implementation of step (6) is as follows: Figure 4 As shown:

[0142] A1. Regarding VHf m′ Zero-mean normalization was performed to construct the spatiotemporal matrix of the vibration distribution vector after 24 hours of continuous monitoring.

[0143]

[0144] in, Represents the normalized VHf m′ .

[0145] A2. Then calculate the covariance matrix corresponding to H, and then decompose the matrix using EVD or SVD.

[0146]

[0147] In this matrix U, each column represents an eigenvector, Λ = diag{λ1,λ2,...,λ M'} contains all eigenvalues, and λ1≥λ2≥…≥λ M' .

[0148] A3. Construct consistency features to characterize the stability of the transformer's mechanical structure under harmonic influence:

[0149]

[0150] When this eigenvalue is close to 1, it indicates that the mechanical structure remains stable and unchanged under high-frequency excitation. When the internal mechanical structure of the transformer changes, such as when the windings deform, the uniformity of the high-frequency vibration distribution deteriorates, and the eigenvalue tends to 0.

[0151] Based on the fault analysis method provided in the above embodiments, this application also provides a fault analysis device, see [link to previous document]. Figure 5 , Figure 5 This application provides a structural block diagram of a fault analysis device 500, which includes an acquisition unit 501, a first determination unit 502, a second determination unit 503, a third determination unit 504, and a fourth determination unit 505.

[0152] The acquisition unit 501 is used to acquire a set of vibration signals to be analyzed, which includes vibration signals to be analyzed corresponding to the transformer to be analyzed in multiple detection periods.

[0153] The first determining unit 502 is used to take multiple vibration signals to be analyzed as target vibration signals to be analyzed, and determine the number of energy bands corresponding to the target vibration signals to be analyzed.

[0154] The second determining unit 503 is used to determine the target vibration signal to be analyzed as a harmonic interference vibration signal in response to the number of energy bands being greater than a preset threshold.

[0155] The third determining unit 504 is used to determine the harmonic characteristic frequencies corresponding to the multiple harmonic interference vibration signals among the multiple vibration signals to be analyzed. The harmonic characteristic frequencies are used to reflect the vibration characteristics of the transformer to be analyzed under harmonic interference.

[0156] The fourth determining unit 505 is used to determine whether the transformer to be analyzed has a fault based on the similarity between the harmonic characteristic frequencies corresponding to the plurality of harmonic interference vibration signals.

[0157] In one possible implementation, the fourth determining unit 505 is specifically used for:

[0158] Determine the high-frequency vibration distribution vectors corresponding to the plurality of harmonic interference vibration signals;

[0159] Determine the consistency feature value of multiple high-frequency vibration distribution vectors corresponding to the multiple harmonic interference vibration signals. The consistency feature value is used to reflect the similarity between the multiple high-frequency vibration distribution vectors. The consistency feature value is the number of distribution center points of the multiple high-frequency vibration distribution vectors.

[0160] If the consistency feature value is 1, it is determined that the transformer to be analyzed has not experienced a fault;

[0161] If the consistency feature value is not 1, it is determined that the transformer to be analyzed has a fault.

[0162] In one possible implementation, the first determining unit 502 is specifically used for:

[0163] Determine the discrete spectrum sequence corresponding to the target vibration signal to be analyzed;

[0164] The discrete spectrum sequence is smoothed by filtering to construct a smooth spectrum sequence;

[0165] The average smoothed spectrum corresponding to the target vibration signal to be analyzed is determined based on the smoothed spectrum sequence.

[0166] The number of energy bands in the average smooth spectrum is determined as the number of energy bands corresponding to the target vibration signal to be analyzed.

[0167] In one possible implementation, the third determining unit 504 is specifically used for:

[0168] The plurality of harmonic interference vibration signals are respectively taken as target harmonic interference vibration signals, and the average smooth spectrum corresponding to the target harmonic interference vibration signals is determined.

[0169] Determine the effective values ​​corresponding to the multiple energy bands in the average smooth spectrum, and the effective values ​​are used to identify the energy intensity of the excitation source that causes the generation of the energy bands;

[0170] The frequency corresponding to the energy band with the highest effective value is determined as the harmonic frequency characteristic of the target harmonic interference vibration signal.

[0171] In one possible implementation, the third determining unit 504 is specifically used for:

[0172] Each of the multiple energy bands is taken as a target energy band, and multiple local peak points are determined within the target energy band;

[0173] The effective value of the target energy band is determined based on the difference between the frequencies corresponding to the multiple local peak points and the preset frequency, as well as the peak values ​​corresponding to the multiple local peak points. The preset frequency is the frequency of the energy band not generated by harmonics.

[0174] Those skilled in the art will understand that all or part of the steps of the above method embodiments can be implemented by hardware related to program instructions. The aforementioned program can be stored in a computer-readable storage medium. When the program is executed, it performs the steps of the above method embodiments. The aforementioned storage medium can be at least one of the following media: read-only memory (ROM), RAM, magnetic disk, or optical disk, etc., and other media capable of storing program code.

[0175] It should be noted that the various embodiments in this specification are described in a progressive manner, and the same or similar parts between the various embodiments can be referred to mutually. Each embodiment focuses on describing the differences from other embodiments. In particular, for the device and system embodiments, since they are basically similar to the method embodiments, the description is relatively simple, and the relevant parts can be referred to the description of the method embodiments. The device and system embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of the solution in this embodiment according to actual needs. Those skilled in the art can understand and implement this without creative effort.

[0176] The above description is merely one specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

Claims

1. A fault analysis method, characterized in that, The method includes: A set of vibration signals to be analyzed is obtained, which includes vibration signals to be analyzed corresponding to the transformer to be analyzed in multiple detection periods. Multiple vibration signals to be analyzed are respectively used as target vibration signals to be analyzed, and the number of energy bands corresponding to the target vibration signals to be analyzed is determined. In response to the number of energy bands being greater than a preset threshold, the target vibration signal to be analyzed is determined to be a harmonic interference vibration signal; The harmonic characteristic frequencies corresponding to multiple harmonic interference vibration signals among the multiple vibration signals to be analyzed are determined. The harmonic characteristic frequencies are used to reflect the vibration characteristics of the transformer to be analyzed under harmonic interference. Based on the similarity between the harmonic characteristic frequencies corresponding to the multiple harmonic interference vibration signals, it is determined whether the transformer to be analyzed has a fault. The step of determining whether the transformer to be analyzed has a fault based on the similarity between the harmonic characteristic frequencies corresponding to the multiple harmonic interference vibration signals includes: Determine the high-frequency vibration distribution vectors corresponding to the plurality of harmonic interference vibration signals; Determine the consistency feature value of multiple high-frequency vibration distribution vectors corresponding to the multiple harmonic interference vibration signals. The consistency feature value is used to reflect the similarity between the multiple high-frequency vibration distribution vectors. The consistency feature value is the number of distribution center points of the multiple high-frequency vibration distribution vectors. If the consistency feature value is 1, it is determined that the transformer to be analyzed has not experienced a fault; If the consistency feature value is not 1, it is determined that the transformer to be analyzed has a fault.

2. The method according to claim 1, characterized in that, Determining the number of energy bands corresponding to the target vibration signal to be analyzed includes: Determine the discrete spectrum sequence corresponding to the target vibration signal to be analyzed; The discrete spectrum sequence is smoothed by filtering to construct a smooth spectrum sequence; The average smoothed spectrum corresponding to the target vibration signal to be analyzed is determined based on the smoothed spectrum sequence. The number of energy bands in the average smooth spectrum is determined as the number of energy bands corresponding to the target vibration signal to be analyzed.

3. The method according to claim 1, characterized in that, Determining the harmonic characteristic frequencies corresponding to the multiple harmonic interference vibration signals among the multiple vibration signals to be analyzed includes: The plurality of harmonic interference vibration signals are respectively taken as target harmonic interference vibration signals, and the average smooth spectrum corresponding to the target harmonic interference vibration signals is determined. Determine the effective values ​​corresponding to the multiple energy bands in the average smooth spectrum, and the effective values ​​are used to identify the energy intensity of the excitation source that causes the generation of the energy bands; The frequency corresponding to the energy band with the highest effective value is determined as the harmonic frequency characteristic of the target harmonic interference vibration signal.

4. The method according to claim 3, characterized in that, Determining the effective values ​​corresponding to the multiple energy bands in the average smoothed spectrum includes: Each of the multiple energy bands is taken as a target energy band, and multiple local peak points are determined within the target energy band; The effective value of the target energy band is determined based on the difference between the frequencies corresponding to the multiple local peak points and the preset frequency, as well as the peak values ​​corresponding to the multiple local peak points. The preset frequency is the frequency of the energy band not generated by harmonics.

5. A fault analysis device, characterized in that, The device includes an acquisition unit, a first determination unit, a second determination unit, a third determination unit, and a fourth determination unit: The acquisition unit is used to acquire a set of vibration signals to be analyzed, which includes vibration signals to be analyzed corresponding to the transformer to be analyzed in multiple detection periods. The first determining unit is used to take multiple vibration signals to be analyzed as target vibration signals to be analyzed, and determine the number of energy bands corresponding to the target vibration signals to be analyzed; The second determining unit is used to determine the target vibration signal to be analyzed as a harmonic interference vibration signal in response to the number of energy bands being greater than a preset threshold. The third determining unit is used to determine the harmonic characteristic frequencies corresponding to the multiple harmonic interference vibration signals among the multiple vibration signals to be analyzed. The harmonic characteristic frequencies are used to reflect the vibration characteristics of the transformer to be analyzed under harmonic interference. The fourth determining unit is used to determine whether the transformer to be analyzed has a fault based on the similarity between the harmonic characteristic frequencies corresponding to the plurality of harmonic interference vibration signals. The fourth determining unit is specifically used for: Determine the high-frequency vibration distribution vectors corresponding to the plurality of harmonic interference vibration signals; Determine the consistency feature value of multiple high-frequency vibration distribution vectors corresponding to the multiple harmonic interference vibration signals. The consistency feature value is used to reflect the similarity between the multiple high-frequency vibration distribution vectors. The consistency feature value is the number of distribution center points of the multiple high-frequency vibration distribution vectors. If the consistency feature value is 1, it is determined that the transformer to be analyzed has not experienced a fault; If the consistency feature value is not 1, it is determined that the transformer to be analyzed has a fault.

6. A computer device, characterized in that, The computer device includes a processor and memory: The memory is used to store program code and transmit the program code to the processor; The processor is used to execute the fault analysis method according to any one of claims 1-4 according to the instructions in the program code.

7. A computer-readable storage medium, characterized in that, The computer-readable storage medium is used to store a computer program for executing the fault analysis method according to any one of claims 1-4.

8. A computer program product comprising instructions that, when run on a computer, causes the computer to perform the fault analysis method according to any one of claims 1-4.

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