A method and device for detecting partial discharge of power equipment

Abstract

The application provides a kind of electric power equipment partial leakage detection method and device, belongs to partial leakage detection technical field, its method includes: obtaining the vibration signal of electric power equipment based on grating array vibration sensing optical cable collection and the sound wave signal of electric power equipment based on grating array sound wave sensing optical cable collection;Sound wave intensity probability distribution map is constructed based on sound wave signal, and target signal width is determined based on sound wave intensity probability distribution map;First partial leakage detection result is determined based on target signal width;Wavelet packet decomposition is carried out based on preset wavelet base to vibration signal, obtain multiple signal frequency bands, and second partial leakage detection result is determined based on multiple signal frequency bands;When first partial leakage detection result and second partial leakage detection result are same, first partial leakage detection result or second partial leakage detection result is regarded as final partial leakage detection result.The application improves the detection accuracy of detecting partial leakage of electric power equipment.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of partial discharge detection, and particularly relates to a partial discharge detection method and device for power equipment. BACKGROUND

[0002] Partial discharge is the main cause of insulation deterioration and damage of power equipment, and strong partial discharge can quickly reduce the insulation strength. Therefore, it is of great significance to detect the partial discharge of large power equipment online.

[0003] The common partial discharge detection method is the ultrahigh frequency method, which is affected by gas composition and electromagnetic noise in the environment, resulting in high requirements for the detection environment. Therefore, the acoustic wave method is the mainstream detection method, but the acoustic wave has defects such as low reliability and large error.

[0004] Therefore, it is necessary to provide a partial discharge detection method and device for power equipment to improve the accuracy of partial discharge detection of power equipment. SUMMARY

[0005] Therefore, it is necessary to provide a partial discharge detection method and device for power equipment to improve the accuracy of partial discharge detection of power equipment.

[0006] In one aspect, to solve the above technical problems, the present application provides a partial discharge detection method for power equipment, comprising:

[0007] obtaining a vibration signal of the power equipment collected based on a grating array vibration sensing optical cable and an acoustic wave signal of the power equipment collected based on a grating array acoustic wave sensing optical cable;

[0008] constructing an acoustic wave intensity probability distribution map based on the acoustic wave signal, and determining a target signal width based on the acoustic wave intensity probability distribution map;

[0009] determining a first partial discharge detection result based on the target signal width;

[0010] wavelet packet decomposition of the vibration signal based on a preset wavelet basis, obtaining a plurality of signal frequency bands, and determining a second partial discharge detection result based on the plurality of signal frequency bands;

[0011] When the first partial discharge detection result and the second partial discharge detection result are the same, the first partial discharge detection result or the second partial discharge detection result is taken as the final partial discharge detection result.

[0012] In a possible implementation, the sound wave signal comprises a plurality of sound wave sub-signals with different sound wave intensities; and the constructing of the sound wave intensity probability distribution map based on the sound wave signal comprises:

[0013] dividing the sound wave intensity into a plurality of sound wave intensity intervals and determining a statistical number of sound wave sub-signals in each sound wave intensity interval;

[0014] obtaining a total number of signals in the sound wave signal, taking a ratio of the statistical number and the total number of signals as a sound wave intensity probability distribution, and constructing the sound wave intensity probability distribution map based on the sound wave intensity probability distribution.

[0015] In a possible implementation, the determining of the target signal width based on the sound wave intensity probability distribution map comprises:

[0016] determining a maximum signal intensity based on the sound wave intensity probability distribution map;

[0017] determining an intensity cumulative probability in an extension range centered on the maximum signal intensity and extending to both ends with a preset step length;

[0018] determining a target extension range based on the intensity cumulative probability, and taking a signal width of the target extension range as the target signal width.

[0019] In a possible implementation, the determining of the first local electric leakage detection result based on the target signal width comprises:

[0020] determining whether the target signal width is less than a signal width threshold value;

[0021] when the target signal width is less than the signal width threshold value, the first local electric leakage detection result is that there is local electric leakage.

[0022] In a possible implementation, the determining of the second local electric leakage detection result based on the plurality of signal frequency bands comprises:

[0023] dividing the plurality of signal frequency bands into a plurality of low signal frequency bands and the plurality of high signal frequency bands, and determining a low signal energy sum of the plurality of low signal frequency bands and a high signal energy sum of the plurality of high signal frequency bands;

[0024] determining an energy ratio of the low signal energy sum and the high signal energy sum;

[0025] determining whether the energy ratio is greater than an energy ratio threshold value, and when the energy ratio is greater than the energy ratio threshold value, the second local electric leakage detection result is that there is local electric leakage.

[0026] In a possible implementation, the method further comprises:

[0027] when the final local leakage detection result is that there is local leakage, determining a first local leakage position based on the acoustic wave signal and determining a second local leakage position based on the vibration signal;

[0028] determining whether a position difference between the first local leakage position and the second local leakage position is less than a preset difference value, and if so, taking the first local leakage position or the second local leakage position as a final local leakage position.

[0029] In a possible implementation, the grating array acoustic wave sensing optical cable includes a plurality of acoustic wave sensors, and the acoustic wave signal includes a plurality of acoustic wave sub-signals corresponding to the plurality of acoustic wave sensors; and the determining the first local leakage position based on the acoustic wave signal includes:

[0030] performing wavelet denoising on the plurality of acoustic wave sub-signals to obtain a plurality of denoised sub-signals;

[0031] performing Fourier transform on the plurality of denoised sub-signals to obtain a plurality of Fourier transform signals;

[0032] performing convolution processing on any two of the Fourier transform signals to obtain a signal cross power spectrum;

[0033] performing inverse Fourier transform on the signal cross power spectrum to obtain a cross-correlation coefficient;

[0034] determining the first local leakage position based on the cross-correlation coefficient.

[0035] In a possible implementation, the grating array vibration sensing optical cable includes a plurality of vibration sensors, and the vibration signal includes a plurality of vibration sub-signals corresponding to the plurality of vibration sensors; and the determining the second local leakage position based on the vibration signal includes:

[0036] determining a short-time energy of each of the vibration sub-signals based on a short-time energy algorithm;

[0037] when the short-time energy is greater than an energy threshold value, determining that local leakage occurs at a position of a vibration sensor corresponding to the short-time energy, and determining the second local leakage position based on the position of the vibration sensor.

[0038] In a possible implementation, after the vibration signal of the power equipment collected based on the grating array vibration sensing optical cable and the acoustic wave signal of the power equipment collected based on the grating array acoustic wave sensing optical cable are acquired, the method further includes:

[0039] respectively performing denoising processing on the vibration signal and the acoustic wave signal.

[0040] In another aspect, the present application also provides a partial electric leakage detection device for electric equipment, comprising:

[0041] a signal acquisition unit configured to acquire a vibration signal of the electric equipment collected based on a grating array vibration sensing optical cable and an acoustic wave signal of the electric equipment collected based on a grating array acoustic wave sensing optical cable;

[0042] an acoustic wave signal analysis unit configured to construct an acoustic wave intensity probability distribution map based on the acoustic wave signal and determine a target signal width based on the acoustic wave intensity probability distribution map;

[0043] a first partial electric leakage detection unit configured to determine a first partial electric leakage detection result based on the target signal width;

[0044] a second partial electric leakage detection unit configured to perform wavelet packet decomposition on the vibration signal based on a preset wavelet basis to obtain a plurality of signal frequency bands and determine a second partial electric leakage detection result based on the plurality of signal frequency bands;

[0045] a final partial electric leakage detection unit configured to determine a final partial electric leakage detection result as the first partial electric leakage detection result or the second partial electric leakage detection result when the first partial electric leakage detection result and the second partial electric leakage detection result are the same.

[0046] The present application has the following beneficial effects: The partial electric leakage detection method for electric equipment provided by the present application acquires two different types of grating array sensing signals, i.e., a vibration signal and an acoustic wave signal, and analyzes the acoustic wave signal and the vibration signal respectively to obtain corresponding first and second partial electric leakage detection results, and finally determines a final partial electric leakage detection result based on the first and second partial electric leakage detection results, thereby solving the technical problem of unreliable and inaccurate results when partial electric leakage is determined based on a single acoustic wave signal or other signals and improving the accuracy of the partial electric leakage result.

[0047] Further, since the grating array vibration sensing optical cable and the grating array acoustic wave sensing optical cable are continuous array gratings prepared on a wire drawing tower scale, they have the advantages of multiple measuring points, large capacity, high sensitivity, and long distance, and thus can realize full-area detection of the electric equipment and further improve the comprehensiveness and accuracy of the partial electric leakage detection. BRIEF DESCRIPTION OF DRAWINGS

[0048] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings needed in the embodiment description will be briefly introduced. Obviously, the drawings in the following description are only some embodiments of the present application, and other drawings can be obtained by those skilled in the art without creative effort.

[0049] Figure 1 An embodiment flow chart of the method for detecting partial electric leakage of power equipment provided by the present application is shown in the figure;

[0050] Figure 2 An embodiment flow chart of the method for detecting partial electric leakage of power equipment provided by the present application is shown in the figure; Figure 1 An embodiment flow chart of the method for detecting partial electric leakage of power equipment provided by the present application is shown in the figure;

[0051] Figure 3 An embodiment flow chart of the method for detecting partial electric leakage of power equipment provided by the present application is shown in the figure; Figure 1 An embodiment flow chart of the method for detecting partial electric leakage of power equipment provided by the present application is shown in the figure;

[0052] Figure 4 An embodiment flow chart of the method for detecting partial electric leakage of power equipment provided by the present application is shown in the figure; Figure 1 An embodiment flow chart of the method for detecting partial electric leakage of power equipment provided by the present application is shown in the figure;

[0053] Figure 5 An embodiment flow chart of the method for detecting partial electric leakage of power equipment provided by the present application is shown in the figure;

[0054] Figure 6 An embodiment flow chart of the method for detecting partial electric leakage of power equipment provided by the present application is shown in the figure; Figure 5 An embodiment flow chart of the method for detecting partial electric leakage of power equipment provided by the present application is shown in the figure;

[0055] Figure 7 An embodiment flow chart of the method for detecting partial electric leakage of power equipment provided by the present application is shown in the figure; Figure 5 An embodiment flow chart of the method for detecting partial electric leakage of power equipment provided by the present application is shown in the figure;

[0056] Figure 8 An embodiment structure diagram of the device for detecting partial electric leakage of power equipment provided by the present application is shown in the figure. DETAILED DESCRIPTION

[0057] The technical solutions in the embodiments of the present application will be clearly and completely described with reference to the accompanying drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor fall within the scope of protection of the present application.

[0058] It should be understood that the schematic drawings are not drawn to scale. The flowcharts used in the present application show the operations implemented according to some embodiments of the present application. It should be understood that the operations of the flowcharts can not be implemented in sequence, the steps without logical context relationship can be reversed in sequence or implemented simultaneously. In addition, one or more other operations can be added to the flowcharts or one or more operations can be removed from the flowcharts under the guidance of the content of the present application. Some block diagrams shown in the drawings are functional entities, which do not necessarily have to correspond to physically or logically independent entities. These functional entities can be implemented in the form of software, or in one or more hardware modules or integrated circuits, or in different network and / or processor systems and / or microcontroller systems.

[0059] Reference herein to "an embodiment" means that a particular feature, structure, or characteristic described in connection with an embodiment can be included in at least one embodiment of the application. The appearances of the phrase in various places in the specification are not necessarily all referring to the same embodiment, nor are they necessarily mutually exclusive or alternative embodiments. It is explicitly understood that embodiments described herein can be combined with other embodiments.

[0060] The present application provides a power equipment partial leakage detection method and device, which are described below respectively.

[0061] Figure 1 An embodiment flowchart of the power equipment partial leakage detection method provided by the present application is shown in FIG. 1, which includes the following steps. Figure 1

[0062] S101, acquiring a vibration signal of the power equipment collected based on a grating array vibration sensing optical cable and an acoustic wave signal of the power equipment collected based on a grating array acoustic wave sensing optical cable;

[0063] S102, constructing an acoustic wave intensity probability distribution map based on the acoustic wave signal, and determining a target signal width based on the acoustic wave intensity probability distribution map;

[0064] S103, determining a first partial leakage detection result based on the target signal width;

[0065] S104, performing wavelet packet decomposition on the vibration signal based on a preset wavelet basis, obtaining a plurality of signal frequency bands, and determining a second partial leakage detection result based on the plurality of signal frequency bands;

[0066] S105, when the first partial leakage detection result and the second partial leakage detection result are the same, taking the first partial leakage detection result or the second partial leakage detection result as a final partial leakage detection result. ​

[0067] The power equipment in the embodiments of the present application includes, but is not limited to, power switches and cables.

[0068] It should be understood that before the power equipment partial leakage detection method proposed in the embodiments of the present application is executed, the grating array vibration sensing optical cable and the grating array acoustic wave sensing optical cable need to be laid in the power equipment.

[0069] It should be noted that in step S105, when the first partial leakage detection result and the second partial leakage detection result are different, the detection is re-performed, that is, steps S101-S105 are re-executed.

[0070] In step S104, the preset wavelet basis can be selected from Haar, Daubechies, Biothogonal and other wavelet bases according to requirements. In some embodiments of the present application, the preset wavelet basis is db3 wavelet basis in Daubechies, and then the wavelet packet decomposition of the vibration signal based on the preset wavelet basis in step S104 is specifically:

[0071] Based on the db3 wavelet basis, the vibration signal is decomposed by 4 layers of wavelet packets, and 16 signal frequency bands are obtained, which are f1, f2, f3, f4, f5, f6, f7, f8, f9, f 10 , f 11 , f 12 , f 13 , f 14 , f 15 , and f 16 .

[0072] Compared with the prior art, the power equipment partial leakage detection method provided in the embodiments of the present application acquires two different types of grating array sensing signals, i.e., vibration signals and acoustic wave signals, analyzes the acoustic wave signals and the vibration signals respectively, obtains corresponding first partial leakage detection results and second partial leakage detection results, and finally determines the final partial leakage detection result based on the first partial leakage detection results and the second partial leakage detection results, thereby solving the technical problem of unreliable and inaccurate results when partial leakage is judged based on a single acoustic wave signal or other signals, and improving the accuracy of the partial leakage results.

[0073] Further, since the grating array vibration sensing optical cable and the grating array acoustic wave sensing optical cable are continuous array gratings prepared by a wire drawing tower on a large scale, they have the advantages of multiple measuring points, large capacity, high sensitivity and long distance, and therefore, the full-area detection of the power equipment can be realized, and the comprehensiveness and accuracy of the partial leakage detection are further improved.

[0074] In some embodiments of the present application, the acoustic wave signal includes a plurality of acoustic wave sub-signals with different acoustic wave intensities; then, as shown inFigure 2 As shown in the figure, the step S102 of constructing the sound wave intensity probability distribution map based on the sound wave signal comprises:

[0075] S201, dividing the sound wave intensity into multiple sound wave intensity intervals, and determining the statistical number of the sound wave sub-signals in each sound wave intensity interval;

[0076] S202, obtaining the total number of signals in the sound wave signal, taking the ratio of the statistical number and the total number of signals as the sound wave intensity probability distribution, and constructing the sound wave intensity probability distribution map based on the sound wave intensity probability distribution.

[0077] Since when the power equipment does not have local leakage, the ratio of the statistical number and the total number of signals in each sound wave intensity interval will not have a big difference, that is, the sound wave intensity probability distribution map will not have a significant peak, therefore, the embodiment of the present application can determine whether the power equipment has local leakage through the sound wave intensity probability distribution map.

[0078] Wherein, the intensity of the sound wave sub-signal depends on the intensity range and the signal collection accuracy, for example: when the intensity range is 0-99dB, and the signal collection accuracy is 1dB, the sound wave intensity of the multiple sound wave sub-signals is 0, 1,..., 99dB.

[0079] Wherein, the total number of signals is related to the intensity range, the signal collection accuracy, and the signal collection times.

[0080] It should be understood that the narrower the sound wave intensity interval, the more accurate the detection result, and the size of the sound wave intensity interval can be set in combination with the actual application scene or experience value in actual application.

[0081] In some embodiments of the present application, as Figure 3 As shown in the figure, the step S102 of determining the target signal width based on the sound wave intensity probability distribution map comprises:

[0082] S301, determining the maximum signal intensity based on the sound wave intensity probability distribution map;

[0083] S302, taking the maximum signal intensity as the center, and expanding to both ends with a preset step length, to determine the intensity cumulative probability in the expansion range;

[0084] S303, determining the target expansion range based on the intensity cumulative probability, and taking the signal width of the target expansion range as the target signal width.

[0085] Wherein, the maximum signal intensity in step S301 refers to the sound wave signal intensity corresponding to the maximum value of the sound wave intensity probability distribution.

[0086] Wherein, the intensity cumulative probability in step S302 is the sum of the sound wave intensity probability distribution corresponding to each sound wave intensity when expanding to both ends.

[0087] It should be understood that step S303 specifically judges whether the intensity accumulation probability is greater than the accumulation probability threshold value, and when it is greater, the extension range corresponding to the intensity accumulation probability at this time is the target extension range. The target signal width refers to the total number of sound wave intensities in the target extension range.

[0088] In some embodiments of the present application, step S103 specifically includes:

[0089] judging whether the target signal width is less than a signal width threshold value;

[0090] When the target signal width is less than the signal width threshold value, the first local leakage detection result is that there is local leakage.

[0091] This is because, compared with the sound wave signal without leakage, the sound wave signal with leakage has a narrower width, so that the present embodiment can realize accurate detection of local leakage by setting the signal width threshold value to judge whether local leakage occurs.

[0092] It should be understood that the signal width threshold value can be adjusted according to specific conditions, and the greater the value, the higher the sensitivity to local leakage signals and the higher the detection accuracy.

[0093] In some embodiments of the present application, as shown in Figure 4 the step S104 of determining the second local leakage detection result based on the plurality of signal frequency bands includes:

[0094] S401, dividing the plurality of signal frequency bands into a plurality of low signal frequency bands and a plurality of high signal frequency bands, and determining a low signal energy sum of the plurality of low signal frequency bands and a high signal energy sum of the plurality of high signal frequency bands;

[0095] S402, determining an energy ratio of the low signal energy sum and the high signal energy sum;

[0096] S403, judging whether the energy ratio is greater than an energy ratio threshold value, and when it is greater, the second local leakage detection result is that there is local leakage.

[0097] Since the energy proportion of the low frequency band significantly increases when the electrical equipment has local leakage, the present embodiment can realize accurate judgment of the second local leakage result through the energy ratio of the low signal energy sum and the high signal energy sum.

[0098] In order to avoid noise interference of the ultra-low frequency, in some embodiments of the present application, before step S401, the ultra-low frequency band in the plurality of signal frequency bands is removed, and then steps S401-S403 are performed on the remaining signal frequency bands, so as to improve the detection accuracy of local leakage.

[0099] In specific embodiments of the present application, the frequency range of the vibration signal is 0-12800Hz, and the 16 signal frequency bands f1-f16 are 0-800Hz, 800-1600Hz, 1600-2400Hz, 2400-3200Hz, 3200-4000Hz, 4000-4800Hz, 4800-5600Hz, 5600-6400Hz, 6400-7200Hz, 7200-8000Hz, 8000-8800Hz, 8800-9600Hz, 9600-10400Hz, 10400-11200Hz, 11200-12000Hz, and 12000-12800Hz, respectively. 16 The energy ratio is (f3+f4+f5+f6) / (f3+f4+f5+f6,...,+f16). 16

[0100] In specific embodiments of the present application, the energy ratio threshold is 35%.

[0101] In actual application scenarios, when it is determined that there is partial electric leakage of the power equipment, maintenance personnel need to guide the position of the partial electric leakage for timely processing of the partial electric leakage position. Therefore, in some embodiments of the present application, as shown in the partial electric leakage detection method for power equipment also includes: Figure 5

[0102] S501, when the final partial electric leakage detection result is that there is partial electric leakage, determining a first partial electric leakage position based on the sound wave signal and a second partial electric leakage position based on the vibration signal;

[0103] S502, judging whether the position difference between the first partial electric leakage position and the second partial electric leakage position is less than a preset difference value, and if so, taking the first partial electric leakage position or the second partial electric leakage position as the final partial electric leakage position.

[0104] Similarly, in the embodiments of the present application, the first partial electric leakage position is determined based on the sound wave signal and the second partial electric leakage position is determined based on the vibration signal when determining the final partial electric leakage position, which can ensure the accuracy of the determined final partial electric leakage position.

[0105] In some embodiments of the present application, the grating array sound wave sensing optical cable includes a plurality of sound wave sensors, and the sound wave signal includes a plurality of sound wave sub-signals corresponding one-to-one to the plurality of sound wave sensors; then as shown in the step S501 of determining the first partial electric leakage position based on the sound wave signal includes: Figure 6

[0106] S601, wavelet denoising the plurality of sound wave sub-signals to obtain a plurality of denoised sub-signals;

[0107] S602, Fourier transforming the plurality of denoised sub-signals to obtain a plurality of Fourier transform signals;

[0108] S603, convoluting any two Fourier transform signals to obtain a signal cross power spectrum;

[0109] S604, inverse Fourier transforming the signal cross power spectrum to obtain a cross-correlation coefficient; ​​​

[0110] S605, determine the first local leakage position based on the cross-correlation coefficient.

[0111] Since the cross-correlation coefficient at the local leakage position occurs a peak value, the first local leakage position can be determined by determining the cross-correlation coefficient.

[0112] The basic principle of wavelet denoising in step S601 is that orthogonal wavelet decomposition has the ability of time-frequency local decomposition, and when signal processing is performed, the wavelet component has a large amplitude, which is in sharp contrast with the uniform performance of noise in the high frequency part. After wavelet decomposition, the wavelet coefficients with large amplitude are useful signals, and the wavelet coefficients with small amplitude are noises, that is, the wavelet transform coefficients of useful signals are greater than the wavelet transform coefficients of noises. A suitable threshold is found, and the wavelet coefficients greater than the threshold are retained, so that wavelet denoising can be realized.

[0113] In step S605, the maximum cross-correlation coefficient in the cross-correlation coefficient is determined, and the acoustic sensor corresponding to the maximum cross-correlation coefficient is determined. The spatial position of the acoustic sensor is taken as the first local leakage position.

[0114] In some embodiments of the present application, the grating array vibration sensing optical cable includes a plurality of vibration sensors, and the vibration signal includes a plurality of vibration sub-signals corresponding to the plurality of vibration sensors one by one; then as shown in the figure, Figure 7 the step S501 of determining the second local leakage position based on the vibration signal includes:

[0115] S701, determine the short-time energy of each vibration sub-signal based on the short-time energy algorithm;

[0116] S702, when the short-time energy is greater than the energy threshold, it is determined that local leakage occurs at the position of the vibration sensor corresponding to the short-time energy, and the second local leakage position is determined based on the position of the vibration sensor.

[0117] Since the short-time energy at the local leakage position is much greater than the short-time energy at the position without local leakage when the electrical equipment occurs local leakage, the second local leakage position can be determined based on the short-time energy in the embodiments of the present application.

[0118] Since the electrical equipment generates sound and vibration during operation, the vibration signal and the acoustic signal obtained in step S101 will inevitably be mixed with other noise signals. In order to avoid the influence of noise signals on the detection result, in some embodiments of the present application, after step S101, it further includes:

[0119] The vibration signal and the acoustic signal are respectively subjected to noise reduction processing.

[0120] The noise reduction processing can be processing based on a band-pass filter, a high-pass filter, an amplifier, or the like, and can remove part of the noise.

[0121] In the preferred embodiment of the present application, the noise reduction processing of the vibration signal further includes: reconstructing the vibration signal to obtain a high-dimensional phase space matrix, inputting the high-dimensional phase space matrix into an independent component analysis method, separating the noise from the high-dimensional space, outputting a series of independent components, and classifying the series of independent components obtained after the independent component analysis method processing to obtain an estimated source information component and a noise information component; selecting the estimated source information component to reconstruct the vibration signal and eliminate the noise in the vibration signal.

[0122] In the preferred embodiment of the present application, the noise reduction processing of the acoustic signal further includes: calculating the autocorrelation function of the acoustic signal, determining whether the acoustic signal includes a periodic signal, and filtering out the periodic signal by using a multi-stage filtering method if the acoustic signal includes the periodic signal; decomposing the acoustic signal from which the periodic signal is filtered out by EMD to obtain a series of IMF components, and determining whether the IMF components contain a mutation signal, and discarding a part of the IMF components that do not contain the mutation signal if the IMF components contain the mutation signal; calculating the cross-correlation coefficient of the remaining IMF components after discarding a part of the IMF components that do not contain the mutation signal and the original signal, and discarding the IMF components with small cross-correlation coefficients; performing noise reduction processing on the IMF components after discarding the cross-correlation coefficients, and reconstructing the IMF components after the noise reduction processing to obtain a pure acoustic signal.

[0123] In order to better implement the power equipment partial leakage detection method in the embodiments of the present application, on the basis of the power equipment partial leakage detection method, correspondingly, the embodiments of the present application also provide a power equipment partial leakage detection device, as shown in Figure 8 The power equipment partial leakage detection device 800 includes:

[0124] The signal acquisition unit 801 is configured to acquire the vibration signal of the power equipment collected based on the grating array vibration sensing optical cable and the acoustic signal of the power equipment collected based on the grating array acoustic wave sensing optical cable.

[0125] The acoustic signal analysis unit 802 is configured to construct an acoustic wave intensity probability distribution map based on the acoustic signal, and determine a target signal width based on the acoustic wave intensity probability distribution map.

[0126] The first partial leakage detection unit 803 is configured to determine a first partial leakage detection result based on the target signal width.

[0127] The second partial leakage detection unit 804 is configured to perform wavelet packet decomposition on the vibration signal based on a preset wavelet basis to obtain a plurality of signal frequency bands, and determine a second partial leakage detection result based on the plurality of signal frequency bands.

[0128] The final partial electric leakage detection unit 805 is configured to take the first partial electric leakage detection result or the second partial electric leakage detection result as a final partial electric leakage detection result when the first partial electric leakage detection result and the second partial electric leakage detection result are the same.

[0129] It should be noted that the power equipment partial electric leakage detection device 800 provided by the above embodiment can implement the technical solutions described in the power equipment partial electric leakage detection method embodiments, and the principles or specific implementation details of the above modules or units can be referred to the corresponding content in the power equipment partial electric leakage detection method embodiments, which will not be described here one by one.

[0130] Those skilled in the art can understand that all or part of the processes of the above-mentioned embodiments can be completed by a computer program instructing related hardware (such as a processor, a controller, etc.) to complete, and the computer program can be stored in a computer readable storage medium. The computer readable storage medium is a disk, an optical disk, a read-only memory, or a random access memory, etc.

[0131] The above describes in detail the power equipment partial electric leakage detection method and device provided by the present application. The principles and implementation manners of the present application are described by applying specific examples. The above embodiment is only used to help understand the method of the present application and its core idea. Meanwhile, for those skilled in the art, according to the idea of the present application, the specific implementation manner and application range will be changed. In summary, the content of the specification should not be understood as a limitation of the present application.

Claims

1. A method for detecting a partial discharge of an electric power device, characterized by, The method comprises the following steps: acquiring a vibration signal of the power equipment collected by a grating array vibration sensing optical cable and an acoustic wave signal of the power equipment collected by a grating array acoustic wave sensing optical cable; constructing an acoustic wave intensity probability distribution map based on the acoustic wave signal and determining a target signal width based on the acoustic wave intensity probability distribution map; determining a first local leakage detection result based on the target signal width; performing wavelet packet decomposition on the vibration signal based on a preset wavelet basis to obtain a plurality of signal frequency bands and determining a second local leakage detection result based on the plurality of signal frequency bands; when the first local leakage detection result and the second local leakage detection result are the same, taking the first local leakage detection result or the second local leakage detection result as a final local leakage detection result; when the final local leakage detection result is that there is local leakage, determining a first local leakage position based on the acoustic wave signal and determining a second local leakage position based on the vibration signal; judging whether a position difference between the first local leakage position and the second local leakage position is less than a preset difference value, and if so, taking the first local leakage position or the second local leakage position as a final local leakage position.

2. The power equipment partial discharge detection method according to claim 1, characterized in that, The acoustic wave signal comprises a plurality of acoustic wave sub-signals with different acoustic wave intensities; the step of constructing an acoustic wave intensity probability distribution map based on the acoustic wave signal comprises the following steps: dividing the acoustic wave intensity into a plurality of acoustic wave intensity intervals and determining the statistical number of acoustic wave sub-signals in each acoustic wave intensity interval; acquiring the total number of signals in the acoustic wave signal, taking the ratio of the statistical number to the total number of signals as an acoustic wave intensity probability distribution, and constructing the acoustic wave intensity probability distribution map based on the acoustic wave intensity probability distribution.

3. The power equipment partial discharge detection method according to claim 2, wherein The step of determining a target signal width based on the acoustic wave intensity probability distribution map comprises the following steps: determining a maximum signal intensity based on the acoustic wave intensity probability distribution map; expanding towards both ends with a preset step length with the maximum signal intensity as the center to determine the intensity cumulative probability in the expansion range; determining a target expansion range based on the intensity cumulative probability and taking the signal width of the target expansion range as the target signal width.

4. The power equipment partial discharge detection method according to claim 1, characterized in that, The step of determining a first local leakage detection result based on the target signal width comprises the following steps: judging whether the target signal width is less than a signal width threshold value; when the target signal width is less than the signal width threshold value, the first local leakage detection result is that there is local leakage.

5. The method of claim 1, wherein, The step of determining a second local leakage detection result based on the plurality of signal frequency bands comprises the following steps: dividing the plurality of signal frequency bands into a plurality of low signal frequency bands and a plurality of high signal frequency bands and determining a low signal energy sum of the plurality of low signal frequency bands and a high signal energy sum of the plurality of high signal frequency bands; determining an energy ratio of the low signal energy sum to the high signal energy sum; judging whether the energy ratio is greater than an energy ratio threshold value, and when it is, the second local leakage detection result is that there is local leakage.

6. The power equipment partial discharge detection method according to claim 4, wherein The grating array acoustic wave sensing optical cable includes a plurality of acoustic wave sensors, and the acoustic wave signal includes a plurality of acoustic wave sub-signals corresponding to the plurality of acoustic wave sensors; and the first local electric leakage position is determined based on the acoustic wave signal, including: Wavelet denoising is performed on the plurality of acoustic wave sub-signals to obtain a plurality of denoised sub-signals; Fourier transform is performed on the plurality of denoised sub-signals to obtain a plurality of Fourier transform signals; Convolution processing is performed on any two Fourier transform signals to obtain a signal cross-power spectrum; Inverse Fourier transform is performed on the signal cross-power spectrum to obtain a cross-correlation coefficient; The first local electric leakage position is determined based on the cross-correlation coefficient.

7. The power equipment partial discharge detection method according to claim 1, wherein The grating array vibration sensing optical cable includes a plurality of vibration sensors, and the vibration signal includes a plurality of vibration sub-signals corresponding to the plurality of vibration sensors; and the second local electric leakage position is determined based on the vibration signal, including: Short-time energy of each vibration sub-signal is determined based on a short-time energy algorithm; When the short-time energy is greater than an energy threshold, it is determined that local electric leakage occurs at a position of the vibration sensor corresponding to the short-time energy, and the second local electric leakage position is determined based on the position of the vibration sensor.

8. The power equipment partial discharge detection method according to claim 1, wherein After obtaining the vibration signal of the power equipment collected based on the grating array vibration sensing optical cable and the acoustic wave signal of the power equipment collected based on the grating array acoustic wave sensing optical cable, the method further includes: Respectively performing noise reduction processing on the vibration signal and the acoustic wave signal.

9. An apparatus for detecting partial discharge of an electric power device, characterized by comprising: Including: A signal acquisition unit is configured to acquire a vibration signal of a power equipment collected based on a grating array vibration sensing optical cable and an acoustic wave signal of the power equipment collected based on a grating array acoustic wave sensing optical cable; An acoustic wave signal analysis unit is configured to construct an acoustic wave intensity probability distribution map based on the acoustic wave signal, and determine a target signal width based on the acoustic wave intensity probability distribution map; A first local electric leakage detection unit is configured to determine a first local electric leakage detection result based on the target signal width; A second local electric leakage detection unit is configured to perform wavelet packet decomposition on the vibration signal based on a preset wavelet basis to obtain a plurality of signal frequency bands, and determine a second local electric leakage detection result based on the plurality of signal frequency bands; A final local electric leakage detection unit is configured to, when the first local electric leakage detection result and the second local electric leakage detection result are the same, take the first local electric leakage detection result or the second local electric leakage detection result as a final local electric leakage detection result; when the final local electric leakage detection result indicates that there is local electric leakage, determine a first local electric leakage position based on the acoustic wave signal and a second local electric leakage position based on the vibration signal; and determine whether a position difference between the first local electric leakage position and the second local electric leakage position is less than a preset difference value, and if so, take the first local electric leakage position or the second local electric leakage position as a final local electric leakage position.

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