Time Difference Estimation Method for Multi-Source Partial Discharge Ultrasound Signals

Abstract

A time difference estimation method for multi-source partial discharge ultrasonic signals is disclosed. In the method, ultrasonic signals of multiple partial discharge sources are collected; in the frequency domain, one signal is multiplied by the complex conjugate of another signal for the two-channel collected signals; a moving window operation is performed on the resulting frequency domain expression to obtain an amplitude spectrum threshold and the spectrum is intercepted according to the threshold; the phase spectrum remains unchanged and the amplitude spectrum is normalized; peak extraction is performed in the time domain to obtain the time difference of the corresponding homologous signals in the multi-source partial discharge signals. The present invention has the advantages of being simple and easy to use, having strong anti-noise ability, and small computational complexity, and has high value for partial discharge location in the field of power equipment condition diagnosis.

Description

Technical Field

[0001] The present invention belongs to the technical field of partial discharge detection of transformers, and particularly relates to a method for estimating the time difference of multi-source partial discharge ultrasonic signals. Background Art

[0002] In the field of partial discharge detection of transformers, traditionally, according to the changing physical and chemical characteristics generated at the location of partial discharge inside the transformer when partial discharge occurs, the operating state of the equipment insulation structure during partial discharge is described. There are pulse current detection techniques, ultra-high frequency electromagnetic wave detection techniques, ultrasonic detection techniques, etc. These traditional detection techniques only reflect the impact of partial discharge on the transformer in terms of the number of discharges, discharge intensity, discharge type, etc. However, the location of partial discharge also plays an extremely important role in the safe and stable operation of the transformer, and the partial discharge ultrasonic positioning technology based on TDOA can solve this problem.

[0003] For the partial discharge ultrasonic positioning technology based on TDOA, the existing technical route mainly focuses on the single-source field. Specifically, after filtering and denoising the ultrasonic signals collected by the sensor array generated by the partial discharge source, the time difference estimation algorithm is used to judge the time difference between the two signals, and the obtained time difference is substituted into the spherical equation system or the hyperbolic equation system to solve this non-linear equation system to obtain the positioning coordinates of the single source. The biggest pain point of the existing method that is not applicable to the multi-source field is that there is no algorithm for directly estimating the time difference of corresponding homologous signals in the original multi-source partial discharge signals. A relatively classic method for solving the multi-source time difference estimation problem is to first perform blind source separation on the obtained signals, and then perform single-source time delay estimation according to the separated signals. However, this method has characteristics such as local optimal solutions and poor separation effects, and the signals after blind source separation will cause a certain degree of distortion to the original signals, thereby increasing the error of subsequent time difference estimation. There are also some methods that use heuristic algorithms such as clustering analysis to solve the multi-source time difference estimation problem, but these methods still have the problem of falling into local optimal solutions, and such algorithms use black box models, which may lead to biased results.

[0004] The above information disclosed in the background art section is only used to enhance the understanding of the background of the present invention, and therefore may include information that does not constitute the prior art known to those of ordinary skill in the art. Summary of the Invention

[0005] Aiming at the problems existing in the prior art, the present invention proposes a method for estimating the time difference of multi-source partial discharge ultrasonic signals, which solves the problems of high computational complexity, large time difference estimation error, and inability to directly estimate the time difference of homologous signals of the original signal in the existing processing of multi-source partial discharge ultrasonic signals.

[0006] The object of the present invention is achieved by the following technical solutions. A method for estimating the time difference of multi-source partial discharge ultrasonic signals includes:

[0007] Step 1: Sensor node a and sensor node b respectively collect N-source partial discharge ultrasonic signals a(t) and b(t). The expressions of a(t) and b(t) are as follows:

[0008]

[0009]

[0010] In the formula: * represents convolution; σ(t) represents an impulse function; x1(t), x2(t), …, x N (t) is the initial signal of the partial discharge ultrasonic wave emitted by the nth signal source among the N signal sources; t a，1 , t a，2 , …, t a，N and t b，1 , t b,2 , …, t b,N are the time delays of the nth signal reaching sensors a and b respectively; n a (t) and n b (t) represent noise;

[0011] Step 2: In the frequency domain, the N-source partial discharge ultrasonic signals a(t) and b(t) are respectively represented as A(ω) and B(ω). Multiply A(ω) and to obtain F ab (ω). The expression of F ab (ω) is as follows:

[0012]

[0013] In the formula: ω is the angular frequency; e is the natural constant; j is the imaginary unit; A(ω) is the expression of a(t) transformed to the frequency domain by FFT; B(ω) is the expression of b(t) transformed to the frequency domain by FFT; represents the complex conjugate of B(ω); X1(ω), X2(ω), …, X N (ω), N a (ω), N b (ω) are the expressions of x1(t), x2(t), …, x N (t), n a (t), n b (t) transformed to the frequency domain by FFT; The first N terms of this formula are called effective terms, the dominant frequency band is called the effective frequency band, the N + 1th term is called the noise term, and the remaining terms are called interference terms. The frequency bands dominated by the noise term and the interference terms are interference frequency bands;

[0014] Step 3: For Fab (ω) Calculate the threshold by using moving window operation;

[0015] Step 4: Set to zero the part of the amplitude spectrum in F ab (ω) that is less than the threshold T, to obtain a new frequency-domain expression F′ ab (ω);

[0016] Step 5: Keep the phase spectrum of F′ ab (ω) unchanged, and perform normalization on the amplitude spectrum to obtain F″ ab (ω) that highlights the impulse function characteristics of the time difference of the corresponding homologous signals in the multi-source signals;

[0017] Step 6: Perform inverse fast Fourier transform on F″ ab (ω) to the time domain to obtain f″ ab (t);

[0018] Step 7: Extract the peaks of f″ ab (t), and select the most prominent N peaks to obtain the time differences of the signals emitted by N signal sources to two different sensor nodes.

[0019] In the time difference estimation method for multi-source partial discharge ultrasonic signals, in the said step 3, the operation expression for calculating the threshold by moving window is as follows:

[0020] T = λ(min(max|F ab (ω)|, i ≤ ω ≤ i + w), 0 ≤ i ≤ ω max - w),

[0021] Where: T is the threshold; F ab (ω) is the frequency-domain expression of the signal; ω is the angular frequency; i is the starting point of the window; w is the width of the window; λ is the threshold selection coefficient.

[0022] In the time difference estimation method for multi-source partial discharge ultrasonic signals, the range of the threshold selection coefficient λ is 5 to 6.

[0023] In the time difference estimation method for multi-source partial discharge ultrasonic signals, in step 5, when keeping the phase spectrum of F′ ab (ω) unchanged and performing normalization on the amplitude spectrum, the two discharge signals are processed by using the same weight method.

[0024] In the time difference estimation method for multi-source partial discharge ultrasonic signals, the expression for normalizing the amplitude spectrum of F′ ab (ω) in step 5 is as follows:

[0025]

[0026] Where: G aa(ω) is G bb (ω) is G ab (ω) is

[0027] In the time difference estimation method of the multi-source partial discharge ultrasonic signal, the peak extraction in step 7 is to obtain the envelope of f″ ab (t), and extract the largest N discontinuous peaks therefrom.

[0028] In the time difference estimation method of the multi-source partial discharge ultrasonic signal, the envelope is drawn using cubic spline interpolation.

[0029] Compared with the prior art, the present invention has the following advantages: The present invention performs multi-source time difference estimation on the original ultrasonic signals of multiple partial discharge sources in a transformer collected by sensors, and has the characteristics of directly processing the original signals and high robustness to noise. The present invention has the following advantages:

[0030] (1) The computational complexity is small, avoiding error accumulation caused by overly complex operation processes.

[0031] (2) This algorithm does not require preprocessing of the signals and can directly operate on the original signals to obtain the time difference between relevant signals, which is simple and easy to use.

[0032] (3) This algorithm reduces the interference of noise on the phase spectrum by utilizing the amplitude spectrum characteristics of the effective signal and noise, and has good anti-noise ability.

[0033] (4) The time difference extracted by this algorithm through multi-source time difference operation is the time difference of the corresponding homologous signals in the multi-source partial discharge signals and will not be interfered by non-correlated signals. BRIEF DESCRIPTION OF THE DRAWINGS

[0034] By reading the detailed description of the preferred specific embodiments below, various other advantages and benefits of the present invention will become clear to those of ordinary skill in the art. The accompanying drawings in the specification are only for the purpose of showing the preferred embodiments and are not considered to be a limitation of the present invention. Obviously, the drawings described below are only some embodiments of the present invention, and those of ordinary skill in the art can obtain other drawings based on these drawings without creative efforts. Moreover, throughout the drawings, the same reference numerals are used to represent the same components.

[0035] In the drawings:

[0036] Figure 1 is a flowchart of the time difference estimation method of the multi-source partial discharge ultrasonic signal provided by an embodiment of the present invention;

[0037] Figure 2 It is a schematic diagram of the simulation waveform of the multi-source partial discharge ultrasonic signal of a transformer provided by an embodiment of the present invention;

[0038] Figure 3 It is a schematic time-domain diagram of the result of the multi-source partial discharge ultrasonic signal of the time difference estimation method of the multi-source partial discharge ultrasonic signal provided by an embodiment of the present invention.

[0039] The present invention will be further explained below with reference to the drawings and embodiments. Specific Embodiments

[0040] The following will refer to the attached Figures 1 to 3 The specific embodiments of the present invention will be described in more detail. Although specific embodiments of the present invention are shown in the drawings, it should be understood that the present invention can be implemented in various forms and should not be limited by the embodiments set forth herein. On the contrary, these embodiments are provided so that the present invention can be more thoroughly understood and the scope of the present invention can be fully conveyed to those skilled in the art.

[0041] It should be noted that certain terms are used in the specification and claims to refer to specific components. Those skilled in the art should understand that technicians may use different terms to refer to the same component. The specification and claims do not use the difference in terms as a way to distinguish components, but use the difference in the functions of components as the criterion for distinction. As mentioned throughout the specification and claims, "comprising" or "including" is an open-ended term and should be interpreted as "including but not limited to". The subsequent description of the specification is for the purpose of implementing the preferred embodiments of the present invention, but the description is for the general principle of the specification and is not intended to limit the scope of the present invention. The protection scope of the present invention shall be defined by the appended claims.

[0042] For the convenience of understanding the embodiments of the present invention, the following will further explain with specific embodiments as examples in conjunction with the drawings, and each drawing does not constitute a limitation on the embodiments of the present invention.

[0043] For better understanding, as Figures 1 to 3 shown, the time difference estimation method of the multi-source partial discharge ultrasonic signal includes

[0044] A time difference estimation method of the multi-source partial discharge ultrasonic signal includes:

[0045] Step 1: Sensor node a and sensor node b respectively collect the N-source partial discharge ultrasonic signals a(t) and b(t), and the expressions of a(t) and b(t) are as follows:

[0046]

[0047]

[0048] In the formula: * represents convolution; σ(t) represents the impulse function; x1(t), x2(t), …, x N (t) is the initial signal of the partial discharge ultrasound emitted by the nth signal source among N signal sources; t a，1 , t a，2 , …, t a，N and t b，1 , t b，2 , …, t b，N are the time delays when the nth signal arrives at sensors a and b respectively; n a (t) and n b (t) represent noise;

[0049] Step 2: In the frequency domain, the N-source partial discharge ultrasound signals a(t) and b(t) are respectively expressed as A(ω) and B(ω). Multiply A(ω) and to obtain F ab (ω). The expression of F ab (ω) is as follows:

[0050]

[0051] In the formula: ω is the angular frequency; e is the natural constant; j is the imaginary unit; A(ω) is the expression of a(t) transformed to the frequency domain by FFT; B(ω) is the expression of b(t) transformed to the frequency domain by FFT; represents the complex conjugate of B(ω); X1(ω), X2(ω), …, X N (ω), N a (ω), N b (ω) are the expressions of x1(t), x2(t), …, x N (t), n a (t), n b (t) transformed to the frequency domain by FFT; The first N terms of this formula are called effective terms, the dominant frequency band is called the effective frequency band, the (N + 1)th term is called the noise term, and the remaining terms are called interference terms. The frequency bands dominated by the noise term and the interference term are interference frequency bands;

[0052] Step 3: Calculate the threshold for F ab (ω) using the moving window operation.

[0053] Step 4: Set to zero the part of the amplitude spectrum of F ab (ω) that is less than the threshold T to obtain a new frequency domain expression F′ ab (ω);

[0054] Step 5: For F′ ab(ω) Keep the phase spectrum unchanged and normalize the amplitude spectrum to obtain the impulse function feature F″ that highlights the time difference of the corresponding homologous signals in the multi-source signals. ab (ω);

[0055] Step 6: Perform the inverse fast Fourier transform on F″ ab (ω) to the time domain to obtain f″ ab (t);

[0056] Step 7: Extract the peaks of f″ ab (t), and select the most prominent N peaks to obtain the time differences of the signals emitted by N signal sources to two different sensor nodes.

[0057] In the preferred embodiment of the time difference estimation method for multi-source partial discharge ultrasonic signals, in the step 3, the operation expression for calculating the threshold by moving window is as follows:

[0058] T = λ(min(max|F ab (ω)|, i ≤ ω ≤ i + w), 0 ≤ i ≤ ω max - w),

[0059] Where: T is the threshold; F ab (ω) is the frequency domain expression of the signal; ω is the angular frequency; i is the starting point of the window; w is the width of the window; λ is the threshold selection coefficient.

[0060] In the preferred embodiment of the time difference estimation method for multi-source partial discharge ultrasonic signals, the range of the threshold selection coefficient λ is 5 - 6.

[0061] In the preferred embodiment of the time difference estimation method for multi-source partial discharge ultrasonic signals, in step 5, when keeping the phase spectrum unchanged and normalizing the amplitude spectrum for F′ ab (ω), the two discharge signals are processed by the method with the same weight.

[0062] In the preferred embodiment of the time difference estimation method for multi-source partial discharge ultrasonic signals, the amplitude spectrum normalization processing of F′ ab (ω) in step 5 adopts the following expression:

[0063]

[0064] Where: G aa (ω) is G bb (ω) is G ab (ω) is

[0065] In the preferred embodiment of the method for estimating the time difference of multi-source partial discharge ultrasonic signals, the peak extraction in step 7 is to obtain the envelope of f″ ab (t) and extract the largest N discontinuous peaks from it.

[0066] In the preferred embodiment of the method for estimating the time difference of multi-source partial discharge ultrasonic signals, the envelope is drawn using cubic spline interpolation.

[0067] In one embodiment, the method includes the following steps:

[0068] (1) The sensor node a and the sensor node b collect the N-source partial discharge ultrasonic signals a(t) and b(t), and the expressions of a(t) and b(t) are as follows:

[0069]

[0070]

[0071] Where: * represents convolution; σ(t) represents the impulse function; x1(t), x2(t), …, x N (t) is the initial signal of the partial discharge ultrasonic wave emitted by the nth signal source among the N signal sources; t a，1 , t a，2 , …, t a，N and t b,1 , t b,2 , …, t b,N are the time delays of the nth signal reaching the sensors a and b respectively; n a (t) and n b (t) represent noise;

[0072] (2) In the frequency domain, a(t) and b(t) are expressed as A(ω) and B(ω), and A(ω) and are multiplied to obtain F ab (ω). The expression of F ab (ω) is as follows:

[0073]

[0074] Where: ω is the angular frequency; e is the natural constant; j is the imaginary unit; A(ω) is the expression of a(t) transformed to the frequency domain by FFT; B(ω) is the expression of b(t) transformed to the frequency domain by FFT; represents the complex conjugate of B(ω); X1(ω), X2(ω), …, X N (ω), N a (ω), N b (ω) are x1(t), x2(t), …, x N (t), na (t), n b (t) The expression after FFT transformation to the frequency domain; the first N terms of this expression are called effective terms, the dominant frequency band is called the effective frequency band, the (N + 1)-th term is called the noise term, and the remaining terms are called interference terms. The frequency bands dominated by the noise term and the interference terms are interference frequency bands;

[0075] (3) For F ab (ω), calculate the threshold using the moving window operation. The rule for threshold selection is that it can remove the influence of the interference frequency band on the phase spectrum without making the phase spectrum too sparse to show the characteristics of the effective frequency band. The operation expression for calculating the threshold by moving window is as follows:

[0076] T = λ(min(max|F ab (ω)|, i ≤ ω ≤ i + w), 0 ≤ i ≤ ω max -w)

[0077] In the formula: T is the threshold; F ab (ω) is the frequency domain expression of the signal; ω is the angular frequency; i is the starting point of the window; w is the width of the window; λ is the threshold selection coefficient. The range of the threshold selection coefficient λ is 5 - 6.

[0078] (4) Set to zero the part of the amplitude spectrum in F ab (ω) that is less than the threshold T to obtain a new frequency domain expression F′ ab (ω).

[0079] (5) Keep the phase spectrum of F′ ab (ω) unchanged and normalize the amplitude spectrum to obtain F″ ab (ω) which highlights the impulse function characteristics of the time difference of the corresponding homologous signals in the multi-source signals. The amplitude spectrum normalization process processes F′ ab (ω) by the method of using the same weights for the two original signals. The present invention proposes the following operation expression:

[0080]

[0081] In the formula: G aa (ω) is G bb (ω) is G ab (ω) is

[0082] (6) Transform F″ ab (ω) to the time domain through the inverse fast Fourier transform to obtain f″ ab (t).

[0083] (7) Peak extraction. For f″ abThe envelope is obtained by cubic spline interpolation, and the largest N discontinuous peaks are the time differences of the signals from N signal sources arriving at two different sensor nodes.

[0084] Appendix Figure 1 is the implementation flowchart of an embodiment: collecting ultrasonic signals of multiple partial discharge sources; cross-correlating the two-channel collected signals; performing a moving window operation on its frequency domain expression to obtain the amplitude spectrum threshold and intercepting the spectrum according to the threshold; keeping the phase spectrum unchanged and normalizing the amplitude spectrum; extracting peaks in the time domain to obtain the time differences of the corresponding homologous signals in the multi-source partial discharge signals.

[0085] Appendix Figure 2 is the image of the simulated dual-source partial discharge ultrasonic signals a(t) and b(t) by a double-exponential oscillatory decay signal and adding 10 dB noise to the signals.

[0086] The expression of the double-exponential oscillatory decay signal is as follows:

[0087]

[0088] In the formula: A is the signal amplitude; t0 is the starting discharge moment; τ c is the attenuation coefficient; f c is the oscillation coefficient; e is the base of the natural logarithm.

[0089] Suppose the parameters of the original signals x1(t) and x2(t) are as follows:

[0090]

[0091] The signals a(t) and b(t) received by the sensor are obtained by delaying the original signals x1(t) and x2(t) respectively:

[0092] a(t) = x1(t) * σ(t1) + x2(t) * σ(t2)

[0093] b(t) = x1(t) * σ(t3) + x2(t) * σ(t4)

[0094] In the formula: σ(t) represents the impulse function; t1 is 200 μs; t2 is 500 μs; t3 is 100 μs; t4 is 300 μs.

[0095] Appendix Figure 3 is the time domain image after processing the signals a(t) and b(t) by the algorithm of the present invention. It can be seen from the figure that the moments corresponding to the two most prominent peaks are 100 μs and 200 μs respectively, which correspond to the time differences of the original signals x1(t) and x2(t) arriving at different sensors and are the same as the set time differences, proving that this algorithm is effective.

[0096] This method is directly applied to the original signals collected by ultrasonic sensing devices. In the frequency domain, interference frequency bands are excluded by setting the amplitude spectrum threshold. The amplitude spectrum normalization highlights the impulse function characteristics of the time difference of multi-source signals, and the time difference corresponding to the homologous signals is directly obtained. The main steps of this method are as follows: collecting ultrasonic signals of multiple partial discharge sources; multiplying one signal by the complex conjugate of another signal in the frequency domain for the two-channel collected signals; performing a moving window operation on the resulting frequency domain expression to obtain the amplitude spectrum threshold and intercepting the frequency spectrum according to the threshold; keeping the phase spectrum unchanged and normalizing the amplitude spectrum; extracting the peak value in the time domain to obtain the time difference of the homologous signals in the multi-source partial discharge signals. The present invention has the advantages of being simple and easy to use, strong anti-noise ability, and small computational complexity, and has high value for the localization of partial discharges in the field of power equipment condition diagnosis.

[0097] Although the embodiments of the present invention have been described above in conjunction with the accompanying drawings, the present invention is not limited to the above specific embodiments and application fields. The above specific embodiments are merely illustrative and guiding, rather than restrictive. Those of ordinary skill in the art can also make many forms under the inspiration of this specification and without departing from the scope protected by the claims of the present invention, and all of these fall within the scope of protection of the present invention.

Claims

1. A method for estimating the time difference of multi-source partial discharge ultrasonic signals, characterized in that, It includes the following steps. Step 1: Sensor node a and sensor node b respectively collect N-source partial discharge ultrasonic signals and , and The expressions are as follows: ， ， Where: * represents convolution; represents the impulse function; , , …, is the initial signal of the partial discharge ultrasound emitted by the nth signal source among N signal sources; , , …, and , , …, are the time delays of the nth signal reaching sensors a and b respectively; and represent noise; Step 2: In the frequency domain, the N-source partial discharge ultrasonic signals and are respectively represented as and . Multiply and to obtain . The expression of is as follows: ， Wherein: is the angular frequency; is the natural constant; is the imaginary unit; is the expression after FFT transformation to the frequency domain; is the expression after FFT transformation to the frequency domain; represents the complex conjugate of; , ,…, , , are , ,…, , , the expressions after FFT transformation to the frequency domain; the first N terms of this formula are called effective terms, the dominant frequency band is called the effective frequency band, the (N + 1)-th term is called the noise term, and the remaining terms are called interference terms. The frequency bands dominated by the noise term and the interference term are the interference frequency bands; Step 3: For calculate the threshold value by using moving window operation; Step 4: Set to zero the part in whose amplitude spectrum is less than the threshold to obtain a new frequency-domain expression ; Step 5: For while keeping the phase spectrum unchanged, perform normalization on the amplitude spectrum to obtain the impulse function feature that highlights the time difference of the corresponding homologous signals in the multi-source signals ; Step 6: Inverse fast Fourier transform to the time domain to obtain ; Step 7: For peak extraction, select the most prominent N peaks to obtain the time differences of the signals emitted by N signal sources to two different sensor nodes.

2. The time difference estimation method for multi-source partial discharge ultrasonic signals according to claim 1, wherein, In step 3, the operation expression for moving the windowed calculation threshold is as follows: ， Wherein: is the threshold value; is the frequency-domain expression of the signal; is the angular frequency; is the starting point of the window; is the width of the window; is the threshold selection coefficient.

3. The time difference estimation method for multi-source partial discharge ultrasonic signals according to claim 2, wherein, Threshold selection coefficient ranges from 5 to 6.

4. The method for estimating the time difference of multi-source partial discharge ultrasonic signals according to claim 1, wherein, Step 5, for When keeping the phase spectrum unchanged and normalizing the amplitude spectrum, the two discharge signals are processed using the same weight method.

5. The method for estimating the time difference of multi-source partial discharge ultrasonic signals according to claim 4, wherein, In step 5, the amplitude spectrum normalization of adopts the following expression: ， In the formula: is ; is ; is .

6. The method for estimating the time difference of multi-source partial discharge ultrasonic signals according to claim 1, wherein, The peak extraction in step 7 is to obtain the envelope and extract the largest N discontinuous peaks therefrom.

7. The method for estimating the time difference of multi-source partial discharge ultrasonic signals according to claim 6, wherein, The envelope is drawn using cubic spline interpolation.

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