Method for estimating time difference of homologous partial discharge ultrasonic signals

Abstract

A time difference estimation method of homologous local discharge ultrasonic signals, wherein two-channel homologous ultrasonic signals are collected; the order of a transverse adaptive filter and the number of a cross-correlator are set; the two-channel homologous signals are input into two transverse adaptive filters; the weight coefficients obtained by the two transverse adaptive filters are input into a k-stage cross-correlator; and the time difference between the homologous ultrasonic signals is obtained by peak extraction on the output of the cross-correlator. The method has the advantages of high time resolution, small time difference estimation deviation and good noise resistance, and has high application value in the field of local discharge positioning in power equipment (such as power transformers).

Description

Technical Field

[0001] This invention relates to the field of online monitoring technology for partial discharge in power equipment, and in particular to a method for estimating the time difference of ultrasonic signals of partial discharge from the same source. Background Technology

[0002] Partial discharge is a significant factor contributing to insulation breakdown in power equipment. In the field of online monitoring of partial discharge in power equipment, besides detecting classic characteristic parameters such as the number of discharges, discharge intensity, and apparent charge, determining the discharge location is also crucial for the safe operation of power equipment. Partial discharge location technology can effectively determine the location of partial discharges and is of great significance for assessing the current insulation characteristics of equipment and identifying the type of partial discharge. It can provide engineering guidance and reference value for maintenance personnel to carry out maintenance work and make a series of correct decisions. Compared to some other classic methods, ultrasonic partial discharge detection and location technology is unaffected by electromagnetic interference from surrounding equipment and has high sensitivity; therefore, it is widely used in the field of partial discharge location in power equipment (such as power transformers).

[0003] Based on ultrasonic detection and localization technology for partial discharge (PDD), traditional algorithms include TDOA and DOA. Regardless of the algorithm used, a crucial step is extracting the time difference of the received signal. The accuracy of this extraction significantly impacts the PDD localization calculation. To facilitate integration and installation, reduce costs, and improve equipment space utilization, ultrasonic detection and localization equipment is trending towards miniaturization. However, for ultrasonic receiving devices, miniaturization introduces larger measurement errors, severely affecting the accurate localization of PDD locations. One solution is to use more precise instruments, but this incurs higher costs. Therefore, a new method is urgently needed to address the limitations of current methods for extracting the time difference of ultrasonic signals from the same source, which are constrained by the equipment's sampling rate, and the conflict between the sampling rate and economic cost.

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

[0005] To address the shortcomings or defects of existing technologies, a time difference estimation method for ultrasonic signals of homogeneous partial discharge is provided. This method solves the problems of large time difference extraction errors and low localization accuracy of partial discharge sources caused by the limitation of equipment sampling rate in the extraction resolution of ultrasonic signals of homogeneous partial discharge.

[0006] The objective of this invention is achieved through the following technical solutions.

[0007] A method for estimating the time difference of ultrasonic signals from the same source partial discharge includes,

[0008] Step 1: Acquire two channels of homogeneous ultrasound signals x1(n) and x2(n), initialize the first transverse adaptive filter, the second transverse adaptive filter and the cross-correlator, set the order of the first transverse adaptive filter to 2M+1, the order of the second transverse adaptive filter to 2M+1 and the number of stages of the cross-correlator to k, where M and k are positive integers;

[0009] Step 2: Input the two-channel homogeneous ultrasound signals x1(n) and x2(n) into the first transverse adaptive filter and the second transverse adaptive filter to obtain the weighting coefficients w. 12 (n) and w 21 (n);

[0010] Step 3: Input the weight coefficients of the first and second transverse adaptive filters into a k-stage cross-correlation circuit to obtain the output function.

[0011] Step 4; Output function Peak extraction was performed to obtain the time difference between the two channels of homogeneous ultrasound signals x1(n) and x1(n).

[0012] In the aforementioned time difference estimation method for ultrasonic signals of co-origin partial discharge, the weight coefficient w of the first transverse adaptive filter... 12 The initial value of (n) is a zero vector of length 2M+1, and the weight coefficients w of the second transverse adaptive filter are... 21 The initial value of (n) is a 0 vector of length 2M+1.

[0013] In the aforementioned time difference estimation method for ultrasonic signals of co-origin partial discharge, the weight coefficient w of the first transverse adaptive filter... 12 The update algorithm for (n) is as follows:

[0014] y 12 (n)=w 12 T (n)x1(n)=x1 T (n)w 12 (n)

[0015] e 12 (n)=x2(nM)-y 12 (n)

[0016] w 12 (n+1)=w 12 (n)+2μe 12 (n)x1(n)

[0017] In the formula: y12 (n) is the filter output function, e 12 x1(n) is the error function, μ is a constant, and x1(n) = [x1(n+M)x1(n+M-1)...x1(n)...x1(nM)] T .

[0018] In the time difference estimation method for the ultrasonic signals of co-source partial discharge, the weight coefficient w of the second transverse adaptive filter... 21 The update algorithm for (n) is as follows:

[0019] y 21 (n)=w 21 T (n)x2(n)=x2 T (n)w 21 (n)

[0020] e 21 (n)=x1(nM)-y 21 (n)

[0021] w 21 (n+1)=w 21 (n)+2μe 21 (n)x2(n)

[0022] In the formula: y 21 (n) is the filter output function, e 21 x²(n) is the error function, μ is a constant, and x²(n) = [x²(n+M)x²(n+M-1)...x²(n)...x²(nM)] T .

[0023] In the time difference estimation method for the ultrasonic signals of the same source partial discharge, the expression for the l-th level cross-correlator in the k-th level cross-correlator is as follows:

[0024]

[0025]

[0026] in, ⊙ indicates related operations.

[0027] In the time difference estimation method for homogeneous partial discharge ultrasonic signals, the mathematical expression for peak extraction from the output of the k-level cross-correlator is as follows:

[0028]

[0029] In the formula: f is the estimated time difference of the ultrasonic signals from the same source partial discharge; sThis refers to the device sampling rate.

[0030] Compared with the prior art, the beneficial effects of this disclosure are as follows:

[0031] This disclosure features advantages such as being unaffected by device sampling rate, enabling super-resolution estimation of time differences between homogeneous ultrasonic signals, and strong noise resistance. The time difference estimated through an adaptive filter is not limited by the sensor sampling rate, reducing the deviation of the estimated time difference and thus significantly improving positioning accuracy. It has good noise resistance and can perform time difference estimation under low signal-to-noise ratio conditions. The adaptive filter can dynamically adjust the weight coefficients during iteration, making it applicable to tracking time-varying and dynamic input environments.

[0032] The description provided is merely an overview of the technical solution of this invention. In order to make the technical means of this invention clearer and more understandable, so that those skilled in the art can implement it according to the contents of the specification, and to make the described and other objects, features and advantages of this invention more obvious and understandable, specific embodiments of this invention are described below. Attached Figure Description

[0033] Various other advantages and benefits of the present invention will become apparent to those skilled in the art upon reading the detailed description of the preferred embodiments below. The accompanying drawings are for illustrative purposes only and are not intended to limit the invention. It is obvious that the drawings described below are merely some embodiments of the invention, and those skilled in the art can obtain other drawings based on these drawings without any inventive effort. Furthermore, the same reference numerals denote the same parts throughout the drawings.

[0034] In the attached diagram:

[0035] Figure 1 This is a flowchart illustrating a method for estimating the time difference of ultrasonic signals from the same source partial discharge.

[0036] Figure 2 This is a schematic diagram of the principle of the first transverse adaptive filter in a time difference estimation method for ultrasonic signals of local partial discharge from the same source;

[0037] Figure 3 This is a schematic diagram of the principle of the second transverse adaptive filter in a time difference estimation method for ultrasonic signals of local partial discharge from the same source;

[0038] Figure 4 This is a schematic diagram of the principle of a k-level cross-correlator for a time difference estimation method of ultrasonic signals from the same source partial discharge;

[0039] Figure 5This is a schematic diagram of the simulated waveform of the ultrasonic signal of the same source partial discharge provided in one embodiment of the present invention;

[0040] Figure 6 This is a schematic diagram illustrating the extraction of the time difference in the time domain after processing two channels of signals from the same source, provided in one embodiment.

[0041] The present invention will be further explained below with reference to the accompanying drawings and embodiments. Detailed Implementation

[0042] The following will refer to the appendix. Figures 1 to 6 Specific embodiments of the invention will be described in more detail below. While specific embodiments of the invention are shown in the accompanying drawings, it should be understood that the invention can be implemented in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided to enable a more thorough understanding of the invention and to fully convey the scope of the invention to those skilled in the art.

[0043] It should be noted that certain terms are used in the specification and claims to refer to predetermined components. Those skilled in the art will understand that different terms may be used to refer to the same component. This specification and claims do not distinguish components based on differences in terminology, but rather on differences in function. The terms "comprising" or "including" used throughout the specification and claims are open-ended and should be interpreted as "comprising but not limited to." The following descriptions are preferred embodiments for carrying out the invention; however, these descriptions are for the purpose of understanding the general principles of the specification and are not intended to limit the scope of the invention. The scope of protection of this invention is determined by the appended claims.

[0044] To facilitate understanding of the embodiments of the present invention, the following will provide further explanation and description with reference to the accompanying drawings and several specific embodiments, and the accompanying drawings do not constitute a limitation on the embodiments of the present invention.

[0045] To better understand, such as Figures 1 to 6 As shown, a method for estimating the time difference of ultrasonic signals from the same source partial discharge includes,

[0046] Step 1: Acquire two channels of homogeneous ultrasound signals x1(n) and x2(n), initialize the first transverse adaptive filter, the second transverse adaptive filter and the cross-correlator, set the order of the first transverse adaptive filter to 2M+1, the order of the second transverse adaptive filter to 2M+1 and the number of stages of the cross-correlator to k, where M and k are positive integers;

[0047] Step 2: Input the two-channel homogeneous ultrasound signals x1(n) and x2(n) into the first transverse adaptive filter and the second transverse adaptive filter to obtain the weighting coefficients w. 12(n) and w 21 (n);

[0048] Step 3: Input the weight coefficients of the first and second transverse adaptive filters into a k-stage cross-correlation circuit to obtain the output function.

[0049] Step 4; Peak extraction was performed to obtain the time difference between the two channels of homologous ultrasound signals x1(n) and x2(n).

[0050] In the aforementioned time difference estimation method for ultrasonic signals of co-origin partial discharge, the weight coefficient w of the first transverse adaptive filter... 12 The initial value of (n) is a zero vector of length 2M+1, and the weight coefficients w of the second transverse adaptive filter are... 21 The initial value of (n) is a 0 vector of length 2M+1.

[0051] In the aforementioned time difference estimation method for ultrasonic signals of co-origin partial discharge, the weight coefficient w of the first transverse adaptive filter... 12 The update algorithm for (n) is as follows:

[0052] y 12 (n)=w 12 T (n)x1(n)=x1 T (n)w 12 (n)

[0053] e 12 (n)=x2(nM)-y 12 (n)

[0054] w 12 (n+1)=w 12 (n)+2μe 12 (n)x1(n)

[0055] In the formula: y 12 (n) is the filter output function, e 12 x1(n) is the error function, μ is a constant, and x1(n) = [x1(n+M)x1(n+M-1)...x1(n)...x1(nM)] T .

[0056] In the time difference estimation method for the ultrasonic signals of co-source partial discharge, the weight coefficient w of the second transverse adaptive filter... 21 The update algorithm for (n) is as follows:

[0057] y 21 (n)=w 21 T(n)x2(n)=x2 T (n)w 21 (n)

[0058] e 21 (n)=x1(nM)-y 21 (n)

[0059] w 21 (n+1)=w 21 (n)+2μe 21 (n)x2(n)

[0060] In the formula: y 21 (n) is the filter output function, e 21 x²(n) is the error function, μ is a constant, and x²(n) = [x²(n+M)x²(n+M-1)...x²(n)...x²(nM)] T .

[0061] In the time difference estimation method for the ultrasonic signals of the same source partial discharge, the expression for the l-th level cross-correlator in the k-th level cross-correlator is as follows:

[0062]

[0063]

[0064] in, ⊙ indicates related operations.

[0065] In the time difference estimation method for homogeneous partial discharge ultrasonic signals, the mathematical expression for peak extraction from the output of the k-level cross-correlator is as follows:

[0066]

[0067] In the formula: f is the estimated time difference of the ultrasonic signals from the same source partial discharge; s This refers to the device sampling rate.

[0068] In one embodiment, the method includes the following steps:

[0069] (1) Acquire two channels of the same source ultrasound signals x1(n) and x2(n), and initialize the order of the transverse adaptive filter 2M+1 and the number of cross-correlators k.

[0070] (2) Input the two channels of the same source ultrasound signal as shown in the attached figure. Figure 2 The first transverse adaptive filter shown is as attached. Figure 3 The second transverse adaptive filter shown has weight coefficients w for the first transverse adaptive filter. 12(n) and the weight coefficients w of the second transverse adaptive filter 21 The initial value of (n) is an O vector of length 2M+1, where M and k are positive integers.

[0071] The weight coefficients w of the first transverse adaptive filter 12 The update algorithm for (n) is as follows:

[0072] y 12 (n)=w 12 T (n)x1(n)=x1 T (n)w 12 (n)

[0073] e 12 (n)=x2(nM)-y 12 (n)

[0074] w 12 (n+1)=w 12 (n)+2μe 12 (n)x1(n)

[0075] In the formula: y 12 (n) is the filter output function, e 12 x1(n) is the error function, μ is a constant, and x1(n) = [x1(n+M)x1(n+M-1)...x1(n)...x1(nM)] T .

[0076] The weight coefficients w of the second transverse adaptive filter 21 The update algorithm for (n) is as follows:

[0077] y 21 (n)=w 21 T (n)x2(n)=x2 T (n)w 21 (n)

[0078] e 21 (n)=x1(nM)-y 21 (n)

[0079] w 21 (n+1)=w 21 (n)+2μe 21 (n)x2(n)

[0080] In the formula: y 21 (n) is the filter output function, e 21 x²(n) is the error function, μ is a constant, and x²(n) = [x²(n+M)x²(n+M-1)...x²(n)...x²(nM)]T .

[0081] (3) Input the weight coefficients of the first transverse adaptive filter and the weight coefficients of the second transverse adaptive filter as shown in the attached figure. Figure 4 The k-level cross-correlation converter shown below has the following expression for the first-level cross-correlation converter:

[0082]

[0083]

[0084] in, ⊙ indicates related operations.

[0085] (4) Peak extraction is performed on the output of the k-level cross-correlator to obtain the time difference between the two channels of the same source ultrasound signal. The mathematical expression for peak extraction on the output of the k-level cross-correlator is as follows:

[0086]

[0087] In the formula: f is the estimated time difference of the ultrasonic signals from the same source partial discharge; s This refers to the device sampling rate.

[0088] Appendix Figure 1 Here is an implementation flowchart of one embodiment: acquire two channels of homogeneous ultrasound signals; set the order of two transverse adaptive filters and the number of stages of the cross-correlator; input the two channels of homogeneous signals into the two transverse adaptive filters; input the weight coefficients obtained from the two transverse adaptive filters into the k-stage cross-correlator; extract the peak value from the output of the cross-correlator to obtain the time difference between the homogeneous ultrasound signals.

[0089] Appendix Figure 5 a(t) and b(t) are normally distributed zero-mean stationary random sequences with a sampling frequency of 1kHz and pass through an ideal low-pass filter with a bandwidth of 100Hz. The time difference between a(t) and b(t) is 2.7ms.

[0090] Appendix Figure 6 The curves showing the time difference estimation of signals a(t) and b(t) after processing by the adaptive filter of this invention are shown. It can be seen that after multiple iterations, the time difference stabilizes at 2.71094ms, which is closer to the actual time difference of 2.7ms than the result of 3ms obtained under the resolution condition. This demonstrates that the algorithm is indeed effective.

[0091] This method discloses a super-resolution adaptive filter for estimating the time difference of ultrasonic signals. The main steps are: acquiring two channels of co-origin ultrasonic signals; setting the order of the transverse adaptive filter and the number of stages of the cross-correlator; inputting the two co-origin signals into the two transverse adaptive filters; inputting the weight coefficients obtained from the two transverse adaptive filters into a k-stage cross-correlator; and extracting the peak value from the output of the cross-correlator to obtain the time difference between the co-origin ultrasonic signals. This invention has advantages such as high time resolution, small time difference estimation deviation, and good noise resistance, and has high application value in the field of partial discharge localization in the condition diagnosis of power equipment (such as power transformers).

[0092] The basic principles of this application have been described above with reference to specific embodiments. However, it should be noted that the advantages, benefits, and effects mentioned in this application are merely examples and not limitations, and should not be considered as essential features of each embodiment of this application. Furthermore, the specific details disclosed above are for illustrative and facilitative purposes only, and are not limitations. These details do not limit the application to the necessity of employing the aforementioned specific details for implementation.

[0093] The above description has been given for purposes of illustration and description. Furthermore, this description is not intended to limit the embodiments of this application to the forms disclosed herein. Although numerous exemplary aspects and embodiments have been discussed above, those skilled in the art will recognize certain variations, modifications, alterations, additions, and sub-combinations thereof.

Claims

1. A method for estimating the time difference of ultrasonic signals from the same source partial discharge, characterized in that, It includes the following steps, Step 1: Acquire two channels of homogeneous ultrasound signals and Initialize the first transverse adaptive filter, the second transverse adaptive filter, and the cross-correlator. Set the order of the first transverse adaptive filter to 2M+1, the order of the second transverse adaptive filter to 2M+1, and the number of stages of the cross-correlator to k, where M and k are positive integers. Step 2: Combine the two channels of homogeneous ultrasound signals and The weight coefficients are obtained by inputting the first transverse adaptive filter and the second transverse adaptive filter. and ; Step 3: Input the weight coefficients of the first and second transverse adaptive filters into a k-stage cross-correlation circuit to obtain the output function. ; Step 4; Output function Peak extraction was performed to obtain two-channel homogeneous ultrasound signals. and Time difference ; The expression for the l-th level cross-correlator in the k-th level cross-correlator is as follows: ， ， in, , , This indicates the relevant operations.

2. The time difference estimation method for homogeneous partial discharge ultrasonic signals according to claim 1, characterized in that, The weight coefficients of the first transverse adaptive filter The initial value is a zero vector of length 2M+1, and the weight coefficients of the second transverse adaptive filter are... The initial value is a 0 vector of length 2M+1.

3. The time difference estimation method for homogeneous partial discharge ultrasonic signals according to claim 2, characterized in that, The weight coefficients of the first transverse adaptive filter The update algorithm is as follows: ， ， ， In the formula: For the filter output function, Let be the error function. It is a constant. .

4. The time difference estimation method for homogeneous partial discharge ultrasonic signals according to claim 2, characterized in that, The weight coefficients of the second transverse adaptive filter The update algorithm is as follows: ， ， ， In the formula: For the filter output function, Let be the error function. It is a constant. .

5. The time difference estimation method for homogeneous partial discharge ultrasonic signals according to claim 1, characterized in that, The mathematical expression for peak extraction from the output of a k-level cross-correlator is as follows: , In the formula: The time difference estimate of the ultrasonic signals of partial discharge from the same source; This refers to the device sampling rate.

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