Power transmission line soft fault positioning method and device, computer equipment, readable storage medium and program product

Abstract

The invention relates to a power transmission line soft fault positioning method and device, computer equipment, a computer readable storage medium and a computer program product. The method comprises the following steps: respectively performing pilot frequency estimation on a power transmission line based on co-prime sampling frequency in a fault-free state and a fault state of the power transmission line to obtain a basic scattering matrix corresponding to the fault-free state and a fault scattering matrix corresponding to the fault state of the power transmission line; obtaining a differential scattering matrix of the power transmission line according to the difference between the basic scattering matrix and the fault scattering matrix; carrying out eigenvalue decomposition on a time reversal operator of the differential scattering matrix to obtain a space energy spectrum and a pseudo spectrum of each to-be-measured position in the power transmission line; and determining the fault position of the power transmission line according to the space energy spectrum and the pseudo spectrum of each to-be-detected position. By adopting the method, the calculation complexity of power transmission line soft fault positioning can be reduced.

Description

Technical Field

[0001] The present application relates to the technical field of power protection, and particularly to a method and device for soft fault location of a transmission line, a computer device, a computer-readable storage medium, and a computer program product. Background Art

[0002] As a key facility for power transmission and signal transmission, transmission lines are widely used in various fields such as power systems, industrial production, aerospace, and transportation. In the actual use of transmission lines, once hard faults such as short circuits or open circuits occur, serious accidents such as fires are likely to be caused, resulting in huge losses. Therefore, maintaining the good state of transmission lines is of great significance for the safe and stable operation of the system.

[0003] Among them, hard faults of transmission lines often originate from soft faults. Therefore, detecting and locating soft faults of transmission lines is beneficial to preventing accidents. However, the soft fault location methods in related technologies have the problem of high computational complexity. Summary of the Invention

[0004] Based on this, it is necessary to provide a method and device for soft fault location of a transmission line, a computer device, a computer-readable storage medium, and a computer program product for the above technical problems.

[0005] In a first aspect, the present application provides a method for soft fault location of a transmission line, including:

[0006] Performing pilot estimation on the transmission line based on relatively prime sampling frequencies in a fault-free state and a fault state of the transmission line, respectively, to obtain a basic scattering matrix corresponding to the fault-free state of the transmission line and a fault scattering matrix corresponding to the fault state;

[0007] Obtaining a differential scattering matrix of the transmission line according to the difference between the basic scattering matrix and the fault scattering matrix;

[0008] Performing eigenvalue decomposition on the time reversal operator of the differential scattering matrix to obtain a spatial energy spectrum and a pseudo-spectrum of each position to be measured in the transmission line;

[0009] Determining the fault position of the transmission line according to the spatial energy spectrum and the pseudo-spectrum of each position to be measured.

[0010] In one embodiment, before performing pilot estimation on the transmission line based on relatively prime sampling frequencies in a fault-free state and a fault state of the transmission line, it includes: determining a plurality of sampling frequency sets according to the sampling frequency range of the detection port of the transmission line; where the sampling frequency intervals of each sampling frequency set are relatively prime; and obtaining the relatively prime sampling frequencies according to each sampling frequency set.

[0011] In one embodiment, the basic scattering matrix includes basic sub-matrices corresponding to each of the sampling frequency sets; the fault scattering matrix includes fault sub-matrices corresponding to each of the sampling frequency sets; obtaining the differential scattering matrix of the transmission line according to the difference between the basic scattering matrix and the fault scattering matrix includes: for each of the sampling frequency sets, obtaining the differential sub-matrix corresponding to the sampling frequency set according to the difference between the basic sub-matrix and the fault sub-matrix corresponding to the sampling frequency set; combining the differential sub-matrices of each of the sampling frequency sets to obtain the differential scattering matrix.

[0012] In one embodiment, performing eigenvalue decomposition on the time reversal operator of the differential scattering matrix to obtain the spatial energy spectrum and the pseudo-spectrum of each position to be measured in the transmission line includes: performing eigenvalue decomposition on the time reversal operator of the differential scattering matrix to obtain the eigenvalues of the time reversal operator and the eigenvectors corresponding to each of the eigenvalues; constructing a noise subspace according to each of the eigenvalues and the eigenvectors corresponding to each of the eigenvalues; constructing the spatial energy spectrum and the pseudo-spectrum of each of the positions to be measured in the noise subspace of the transmission line according to the cable parameters of the transmission line and the noise subspace.

[0013] In one embodiment, constructing the noise subspace according to each of the eigenvalues and the eigenvectors corresponding to each of the eigenvalues includes: screening out target eigenvalues that satisfy the non-significant condition among each of the eigenvalues; constructing the noise subspace according to the eigenvectors corresponding to each of the target eigenvalues.

[0014] In one embodiment, the ratio of the sum of the target eigenvalues to the sum of each of the eigenvalues is not greater than a preset value, and each of the target eigenvalues is less than each of the non-target eigenvalues among the eigenvalues.

[0015] In a second aspect, the present application also provides a soft fault location device for a transmission line, including:

[0016] A first acquisition module, configured to perform pilot estimation on the transmission line based on mutually prime sampling frequencies in a fault-free state and a fault state of the transmission line, respectively, to obtain the basic scattering matrix corresponding to the fault-free state of the transmission line and the fault scattering matrix corresponding to the fault state;

[0017] A second acquisition module, configured to obtain the differential scattering matrix of the transmission line according to the difference between the basic scattering matrix and the fault scattering matrix;

[0018] A decomposition module, configured to perform eigenvalue decomposition on the time reversal operator of the differential scattering matrix to obtain the spatial energy spectrum and the pseudo-spectrum of each position to be measured in the transmission line;

[0019] A positioning module, configured to determine a fault location of the transmission line according to the spatial energy spectrum and the pseudo-spectrum of each of the positions to be measured.

[0020] In a third aspect, the present application further provides a computer device, including a memory and a processor. The memory stores a computer program, and when the processor executes the computer program, the following steps are implemented:

[0021] Perform pilot estimation on the transmission line based on mutually prime sampling frequencies in a fault-free state and a fault state of the transmission line, respectively, to obtain a basic scattering matrix corresponding to the fault-free state of the transmission line and a fault scattering matrix corresponding to the fault state;

[0022] Obtain a differential scattering matrix of the transmission line according to the difference between the basic scattering matrix and the fault scattering matrix;

[0023] Perform eigenvalue decomposition on the time reversal operator of the differential scattering matrix to obtain a spatial energy spectrum and a pseudo-spectrum of each position to be measured in the transmission line;

[0024] Determine a fault location of the transmission line according to the spatial energy spectrum and the pseudo-spectrum of each of the positions to be measured.

[0025] In a fourth aspect, the present application further provides a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the following steps are implemented:

[0026] Perform pilot estimation on the transmission line based on mutually prime sampling frequencies in a fault-free state and a fault state of the transmission line, respectively, to obtain a basic scattering matrix corresponding to the fault-free state of the transmission line and a fault scattering matrix corresponding to the fault state;

[0027] Obtain a differential scattering matrix of the transmission line according to the difference between the basic scattering matrix and the fault scattering matrix;

[0028] Perform eigenvalue decomposition on the time reversal operator of the differential scattering matrix to obtain a spatial energy spectrum and a pseudo-spectrum of each position to be measured in the transmission line;

[0029] Determine a fault location of the transmission line according to the spatial energy spectrum and the pseudo-spectrum of each of the positions to be measured.

[0030] In a fifth aspect, the present application further provides a computer program product, including a computer program. When the computer program is executed by a processor, the following steps are implemented:

[0031] Pilot estimation is performed on the power transmission line based on co-prime sampling frequencies respectively in the fault-free state and the fault state of the power transmission line, to obtain the basic scattering matrix corresponding to the fault-free state of the power transmission line and the fault scattering matrix corresponding to the fault state;

[0032] According to the difference between the basic scattering matrix and the fault scattering matrix, the differential scattering matrix of the power transmission line is obtained;

[0033] Eigenvalue decomposition is performed on the time reversal operator of the differential scattering matrix, to obtain the spatial energy spectrum and the pseudo-spectrum of each position to be measured in the power transmission line;

[0034] According to the spatial energy spectrum and the pseudo-spectrum of each position to be measured, the fault position of the power transmission line is determined.

[0035] The above power transmission line soft fault location method, device, computer device, computer-readable storage medium and computer program product first perform pilot estimation on the power transmission line based on co-prime sampling frequencies respectively in the fault-free state and the fault state of the power transmission line, to obtain the basic scattering matrix corresponding to the fault-free state of the power transmission line and the fault scattering matrix corresponding to the fault state, then according to the difference between the basic scattering matrix and the fault scattering matrix, obtain the differential scattering matrix of the power transmission line, and then perform eigenvalue decomposition on the time reversal operator of the differential scattering matrix, to obtain the spatial energy spectrum and the pseudo-spectrum of each position to be measured in the power transmission line, and finally according to the spatial energy spectrum and the pseudo-spectrum of each position to be measured, determine the fault position of the power transmission line. In this solution, by using co-prime sampling frequencies for sparse sampling, the number of sampling points can be significantly reduced, which is beneficial to reducing the overall computational complexity and improving the computational efficiency, thereby being able to overcome the high computational complexity problem brought by non-sparse uniform sampling in the related art. Moreover, compared with the method of using sparse uniform frequencies for sampling in the related art, this solution uses co-prime sampling frequencies for sparse sampling, and can also eliminate the influence brought by artifacts, and more accurately realize the location of soft faults in the power transmission line. Description of the Drawings

[0036] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the related art, the following will briefly introduce the drawings required to be used in the description of the embodiments of the present application or the related art. Obviously, the drawings in the following description are only some embodiments of the present application. For those of ordinary skill in the art, without creative efforts, other related drawings can also be obtained based on these drawings.

[0037] Figure 1 It is a schematic flowchart of the power transmission line soft fault location method in an embodiment;

[0038] Figure 2 It is a schematic flowchart of obtaining the spatial energy spectrum and the pseudo-spectrum in an embodiment;

[0039] Figure 3 It is a schematic flow chart of a method for soft fault location of a power transmission line in another embodiment;

[0040] Figure 4 It is a structural block diagram of a device for soft fault location of a power transmission line in an embodiment;

[0041] Figure 5 It is an internal structure diagram of a computer device in an embodiment. Detailed implementation manners

[0042] In order to make the objectives, technical solutions and advantages of the present application clearer, the present application will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0043] In one embodiment, as Figure 1 shown, a method for soft fault location of a power transmission line is provided. In this embodiment, it is exemplified that the method is applied to a server. It can be understood that the method can also be applied to a terminal, or to a system including a terminal and a server, and is implemented through the interaction between the terminal and the server. In this embodiment, the method includes the following steps:

[0044] Step S101, perform pilot estimation on the power transmission line based on relatively prime sampling frequencies in the fault-free state and the fault state of the power transmission line, respectively, to obtain a basic scattering matrix corresponding to the fault-free state of the power transmission line and a fault scattering matrix corresponding to the fault state.

[0045] Specifically, the soft faults of the power transmission line may include line aging, insulator breakage, cable breakdown, etc. Among them, the fault-free state of the power transmission line may be the state in which the power transmission line operates normally. By performing pilot estimation on the power transmission line at the first time when the power transmission line operates normally, the basic scattering matrix of the power transmission line in the fault-free state can be obtained. Among them, the fault state of the power transmission line may be the operating state of the power transmission line at the second time after a preset time interval from the first time. By performing pilot estimation on the power transmission line at the second time, the fault scattering matrix of the power transmission line in the fault state can be obtained.

[0046] Among them, the pilot estimation of the transmission line can be performed by using the communication terminals deployed on the transmission line. Exemplarily, the communication terminals deployed on the transmission line may include, but are not limited to, broadband power line communication (BPLC) devices such as smart meters and smart switches. Exemplarily, one of the communication terminals can be alternately used as the sending port, and the remaining communication terminals can be used as the probing ports. The sending port sends pilot signals to each probing port, and the probing ports sample according to a specific sampling frequency, and then the channel frequency response of the transmission line between the sending port and the probing ports is obtained through pilot estimation. At the same time, the propagation delay of the transmission line between the sending port and the probing ports can be obtained through the Network Time Protocol (NTP) between the sending port and the probing ports. Then, the propagation delay can be used to perform delay compensation on the channel frequency response, so as to obtain the scattering parameters between the sending port and the probing ports. Subsequently, the scattering matrices corresponding to each sending port and each probing port can be constructed by using the scattering parameters between them. Among them, the scattering matrix obtained by using the result of pilot estimation at the first time is the basic scattering matrix, and the scattering matrix obtained by using the result of pilot estimation at the second time is the fault scattering matrix.

[0047] Among them, the pilot estimations performed at the first time and the second time can be based on mutually prime sampling frequencies. Optionally, the mutually prime sampling frequencies may include multiple sampling frequencies, and every two of the sampling frequencies are mutually prime. Optionally, the mutually prime sampling frequencies may also include multiple groups of sampling frequencies, and each group of sampling frequencies can be selected from the sampling frequency range of the probing ports according to mutually prime sampling frequency intervals.

[0048] Step S102, obtain the differential scattering matrix of the transmission line according to the difference between the basic scattering matrix and the fault scattering matrix.

[0049] Among them, assuming that the basic scattering matrix is , and the fault scattering matrix is , then the differential scattering matrix of the transmission line can be expressed as , where is the angular frequency of the pilot signal.

[0050] Step S103, perform eigenvalue decomposition on the time-reversal operator of the differential scattering matrix to obtain the spatial energy spectrum and the pseudo-spectrum of each position to be measured in the transmission line.

[0051] Among them, according to the differential scattering matrix , its corresponding time-reversal operator can be calculated. Exemplarily, the calculation method of the time-reversal operator can be: , where represents the Hermitian conjugate transpose.

[0052] Based on this time-reversal operator, its eigenvalue decomposition can be performed to obtain the corresponding eigenvalues and eigenvectors. It can be understood that for each frequency point of the pilot signal , after performing eigenvalue decomposition on its time-reversal operator, a real-valued diagonal matrix containing eigenvalues and an eigenvector matrix can be obtained. Exemplarily, the time-reversal operator can be eigenvalue-decomposed according to the following formula to obtain the corresponding eigenvalues and eigenvectors:

[0053]

[0054] In the formula, is the angular frequency of the pilot signal, is the time-reversal operator of the differential scattering matrix, represents the Hermitian conjugate transpose, is a real-valued diagonal matrix containing eigenvalues, is the eigenvector matrix.

[0055] Among them, based on the eigenvalues and eigenvectors of the time-reversal operator, the spatial energy spectrum and pseudo-spectrum of each position to be measured in the transmission line can be calculated. Exemplarily, the calculation formulas for the spatial energy spectrum and pseudo-spectrum can be:

[0056]

[0057]

[0058] In the formula, is the angular frequency of the pilot signal, is the position to be measured, is the eigenvector matrix the conjugate transpose of the i-th row eigenvector in, is the position to be measured in the transmission line corresponding to the pilot signal spatial energy spectrum, is the pseudo-spectrum of the position to be measured in the transmission line , is the position to be measured in the transmission line corresponding to the pilot signal Green's function.

[0059] Optionally, in specific calculations, according to the lengths of each branch of the transmission line network and the test step size , traverse each branch of the transmission line network and determine multiple positions to be measured from them. Then, according to the frequency of the pilot signal, calculate the angular frequency of the pilot signal , and calculating the phase constant in combination with the cable parameters of the transmission line (including resistance , inductance , reactance , capacitance ); and then calculating the spatial energy spectrum and the pseudo-spectrum corresponding to the pilot signal at each position to be measured according to these parameters. ; Then, according to the spatial energy spectrum and the pseudo-spectrum of each position to be measured, the fault position of the transmission line is determined.

[0060] Step S104, determining the fault position of the transmission line according to the spatial energy spectrum and the pseudo-spectrum of each position to be measured.

[0061] Among them, according to the spatial energy spectrum and the pseudo-spectrum of each position to be measured, the energy distribution at each position to be measured in the transmission line can be determined, so that the fault position where there is a soft fault in the transmission line can be determined according to the position to be measured where the energy is concentrated. Exemplarily, the fault position of the transmission line can be the position to be measured with the maximum energy, or the first few positions to be measured with the maximum energy.

[0062] In the above transmission line soft fault location method, first, pilot estimation is performed on the transmission line based on mutually prime sampling frequencies in the fault-free state and the fault state of the transmission line, and the basic scattering matrix corresponding to the fault-free state and the fault scattering matrix corresponding to the fault state of the transmission line are obtained. Then, according to the difference between the basic scattering matrix and the fault scattering matrix, the differential scattering matrix of the transmission line is obtained. Then, eigenvalue decomposition is performed on the time reversal operator of the differential scattering matrix to obtain the spatial energy spectrum and the pseudo-spectrum of each position to be measured in the transmission line. Finally, according to the spatial energy spectrum and the pseudo-spectrum of each position to be measured, the fault position of the transmission line is determined. In this solution, by using mutually prime sampling frequencies for sparse sampling, the number of sampling points can be significantly reduced, which is beneficial to reducing the overall computational complexity and improving the computational efficiency, thereby being able to overcome the high computational complexity problem brought by non-sparse uniform sampling in the related technology. Moreover, compared with the sampling method using sparse uniform frequencies in the related technology, this solution uses mutually prime sampling frequencies for sparse sampling, and can also eliminate the influence brought by artifacts, and more accurately realize the location of soft faults in the transmission line.

[0063] In an exemplary embodiment, before performing pilot estimation on the transmission line based on mutually prime sampling frequencies in the fault-free state and the fault state of the transmission line, it includes: determining a plurality of sampling frequency sets according to the sampling frequency range of the detection port of the transmission line; where the sampling frequency intervals of each sampling frequency set are mutually prime; and obtaining mutually prime sampling frequencies according to each sampling frequency set.

[0064] Specifically, before performing pilot estimation, the specific mutually prime sampling frequencies to be used can be determined first. Among them, a plurality of sampling frequency sets can be determined according to the sampling frequency range of the detection port, and these sampling frequency sets can be combined to obtain the mutually prime sampling frequencies for specific applications.

[0065] Exemplarily, according to the sampling frequency range of the detection port, the original frequency set f within this range for the detection port can be obtained, where the original frequency set f contains sampling frequencies, and these sampling frequencies are evenly distributed within the sampling frequency range of the detection port, with the frequency interval between each frequency being . Based on this, multiple groups of sampling frequencies can be respectively selected from the original frequency set f using relatively prime sampling frequency intervals to obtain multiple sampling frequency sets.

[0066] Exemplarily, taking the number of sampling frequency sets as 2 for illustration, the first sampling frequency set and the second sampling frequency set can be obtained through the following formula:

[0067]

[0068]

[0069] In the formula, is the sampling frequency interval of the first sampling frequency set, is the sampling frequency interval of the second sampling frequency set, and are relatively prime, is the number of sampling frequencies of the first sampling frequency set, is the number of sampling frequencies of the second sampling frequency set.

[0070] Among them, by combining the first sampling frequency set and the second sampling frequency set , a frequency set containing relatively prime sampling frequencies can be obtained.

[0071] It can be understood that the number of sampling frequency sets can also be greater than 2, as long as the sampling frequency intervals corresponding to every two sampling frequency sets are relatively prime.

[0072] In this embodiment, by determining multiple sampling frequency sets within the sampling frequency range of the detection port according to relatively prime sampling frequency intervals, sampling points can be selected according to relatively prime step lengths, thereby effectively improving the equivalent sampling rate, reducing aliasing, and improving the frequency resolution. Subsequently, the pilot overhead can be reduced, which is beneficial to ensuring the accuracy of soft fault location when sparse sampling is achieved.

[0073] In an exemplary embodiment, the basic scattering matrix includes basic sub-matrices corresponding to respective sets of sampling frequencies; the fault scattering matrix includes fault sub-matrices corresponding to respective sets of sampling frequencies; based on the differences between the basic scattering matrix and the fault scattering matrix, a differential scattering matrix of the power transmission line is obtained, including: for each set of sampling frequencies, a differential sub-matrix corresponding to the set of sampling frequencies is obtained according to the differences between the basic sub-matrix and the fault sub-matrix corresponding to the set of sampling frequencies; the differential sub-matrices of the respective sets of sampling frequencies are combined to obtain the differential scattering matrix.

[0074] Wherein, when pilot estimation is performed, the detection ports can sample respectively according to the respective sets of sampling frequencies, and perform pilot estimation based on the corresponding sampling results to obtain the scattering matrix of the power transmission line. Based on this, the basic sub-matrices corresponding to the respective sets of sampling frequencies of the power transmission line in the non-fault state can be constructed respectively, and the fault sub-matrices corresponding to the respective sets of sampling frequencies of the power transmission line in the fault state can be constructed respectively. Thus, the basic scattering matrix of the power transmission line can include multiple basic sub-matrices, and the fault scattering matrix can include multiple fault sub-matrices.

[0075] Exemplarily, still taking the number of sets of sampling frequencies as 2 for illustration, the first basic sub-matrix corresponding to the first set of sampling frequencies and the first fault sub-matrix can be constructed, and the second basic sub-matrix corresponding to the second set of sampling frequencies and the second fault sub-matrix can be constructed. Thus, the basic scattering matrix of the power transmission line can include the first basic sub-matrix and the second basic sub-matrix , and the fault scattering matrix of the power transmission line can include the first fault sub-matrix and the second fault sub-matrix . Wherein, is the angular frequency of the pilot signal.

[0076] Wherein, based on the basic sub-matrices and the fault sub-matrices corresponding to the respective sets of sampling frequencies, the differential sub-matrices corresponding to the respective sets of sampling frequencies can be obtained according to the differences between the basic sub-matrix and the fault sub-matrix corresponding to the same set of sampling frequencies, and then the differential sub-matrices are combined to obtain the differential scattering matrix of the power transmission line.

[0077] Exemplarily, still taking the number of sets of sampling frequencies as 2 for illustration, according to the first basic sub-matrix and the first fault sub-matrix , the first differential sub-matrix corresponding to the first set of sampling frequencies ; According to the second basis sub-matrix and the second fault sub-matrix , the second differential sub-matrix corresponding to the second sampling frequency set can be obtained . Subsequently, by combining the first differential sub-matrix and the second differential sub-matrix , the differential scattering matrix can be obtained.

[0078] In an exemplary embodiment, as Figure 2 shown, performing eigenvalue decomposition on the time reversal operator of the differential scattering matrix to obtain the spatial energy spectrum and the pseudo-spectrum of each position to be measured in the transmission line may include:

[0079] Step S201, performing eigenvalue decomposition on the time reversal operator of the differential scattering matrix to obtain the eigenvalues of the time reversal operator and the eigenvectors corresponding to each eigenvalue.

[0080] Among them, according to the differential scattering matrix , its corresponding time reversal operator can be calculated. Exemplarily, the calculation method of the time reversal operator may be: , where represents the Hermitian conjugate transpose.

[0081] Based on this time reversal operator, eigenvalue decomposition can be performed on it to obtain its corresponding eigenvalues and eigenvectors. It can be understood that for each frequency point of the pilot signal, after performing eigenvalue decomposition on its time reversal operator, a real-valued diagonal matrix containing eigenvalues and an eigenvector matrix can be obtained. Exemplarily, the time reversal operator can be eigenvalue decomposed according to the following formula to obtain its corresponding eigenvalues and eigenvectors:

[0082]

[0083] In the formula, is the angular frequency of the pilot signal, is the time reversal operator of the co-prime sparse scattering matrix, represents the Hermitian conjugate transpose, is a real-valued diagonal matrix containing eigenvalues, is the eigenvector matrix.

[0084] Step S202, constructing a noise subspace according to each eigenvalue and the eigenvector corresponding to each eigenvalue.

[0085] Among them, according to the time reversal operator The eigenvalues and the eigenvectors corresponding to the eigenvalues can be used to construct a noise subspace.

[0086] In an exemplary embodiment, constructing a noise subspace according to the eigenvalues and the eigenvectors corresponding to the eigenvalues may include: screening out target eigenvalues that meet a non-significant condition from the eigenvalues; constructing a noise subspace according to the eigenvectors corresponding to the target eigenvalues.

[0087] Specifically, after obtaining multiple eigenvalues of the time reversal operator the target eigenvalues corresponding to the noise signals can be screened out from the multiple eigenvalues according to a preset non-significant condition. Exemplarily, the non-significant condition may be that the value of the eigenvalue is less than a preset value, or the preset number of eigenvalues arranged at the forefront after sorting the eigenvalues from smallest to largest. Among them, after screening out the target eigenvalues, a noise subspace can be constructed according to the eigenvectors corresponding to the target eigenvalues.

[0088] In an exemplary embodiment, the ratio of the sum of the target eigenvalues to the sum of all eigenvalues is not greater than a preset value, and each target eigenvalue is less than each non-target eigenvalue among the eigenvalues.

[0089] Specifically, the non-significant condition for screening the target eigenvalues can be shown as the following formula:

[0090]

[0091] In the formula, represents an eigenvalue, is the sum of all eigenvalues ( ), N is the number of eigenvalues, that is, the number of detection ports of the transmission line, and P is a preset value (exemplarily 0.1). Among them, , , ……, are target eigenvalues, and the numerical magnitudes of , , ……, can be increasing in sequence.

[0092] Based on this, the target eigenvalues with a small proportion in the sum of eigenvalues can be screened out according to the above non-significant condition.

[0093] Step S203: Construct the spatial energy spectrum and the pseudo-spectrum of each position to be measured in the transmission line in the noise subspace according to the cable parameters of the transmission line and the noise subspace.

[0094] Among them, according to the cable parameters of the transmission line and the noise subspace, the spatial energy spectrum and the pseudo-spectrum of each position to be measured in the noise subspace can be constructed. Exemplarily, the calculation formulas of the spatial energy spectrum and the pseudo-spectrum can be:

[0095]

[0096]

[0097] In the formula, is the angular frequency of the pilot signal, is the position to be measured, is the eigenvector of the i-th row in the noise subspace The conjugate transpose of The location to be measured in the transmission line Corresponding to the pilot signal The spatial energy spectrum of The location to be measured in the transmission line The pseudo-score, The location to be measured in the transmission line Corresponding to the pilot signal The Green's function.

[0098] In this embodiment, by performing eigenvalue decomposition on the time reversal operator of the differential scattering matrix, constructing a noise subspace based on each eigenvalue and its corresponding eigenvector, and then calculating the spatial energy spectrum and pseudo-spectrum of each position to be measured in the noise subspace, the interference of noise on the energy distribution can be reduced, which is conducive to more accurate judgment of the energy focusing position in the subsequent process and improves the positioning accuracy of soft faults in the transmission line.

[0099] In one embodiment, Figure 3 As shown, a method for locating soft faults in a transmission line in a specific embodiment is provided, which specifically includes the following steps:

[0100] Step S1, obtaining a sampling frequency set according to the original frequency set f within the sampling frequency range of each detection port of the transmission line , And combined into a frequency set ; Among them, the frequency set Contains coprime sampling frequencies.

[0101] Step S2, based on the frequency set The coprime sampling frequencies included in the transmission line network enable each detection port to perform coprime sparse sampling on the pilot signal, and perform pilot estimation on the current communication channel based on the sampling results. Each of the communication terminals is set as a sending port in turn, and the other communication terminals are set as detection ports. The channel frequency response and propagation delay are obtained through pilot estimation, and the basic scattering matrix corresponding to the fault-free state is constructed. , the fault scattering matrix corresponding to the fault state , get the differential scattering matrix . Among them, the basic scattering matrix may include basic sub - matrices respectively corresponding to a set of sampling frequencies 、 。 、 The fault scattering matrix may include fault sub - matrices respectively corresponding to a set of sampling frequencies 、 。 、 。The differential scattering matrix can be obtained by combining differential sub - matrices respectively corresponding to a set of sampling frequencies 、 。 、 。

[0102] Step S3, calculate the time - reversal operator according to the differential scattering matrix 。

[0103] Step S4, perform eigenvalue decomposition on the time - reversal operator and sort the decomposed eigenvalues.

[0104] Step S5, screen the target eigenvalues according to the non - significant condition, and select the eigenvectors corresponding to the target eigenvalues to form the noise subspace 。

[0105] Step S6, traverse each branch of the transmission line network according to the lengths of each branch of the transmission line network and the test step size , and determine multiple positions to be measured from them; the angular frequency of the pilot signal can be calculated according to the frequency of the pilot signal, and the phase constant can be calculated in combination with the cable parameters of the transmission line (including resistance , inductance , reactance , capacitance ).

[0106] Step S7, calculate the spatial energy spectrum and the pseudo - spectrum , obtain the soft fault position according to the energy focusing point, and output it as the fault position 。

[0107] It should be understood that although the steps in the flowcharts involved in the above embodiments are shown in sequence according to the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless there is a clear indication in this article, the execution of these steps has no strict order limit, and these steps can be executed in other orders. Moreover, at least a part of the steps in the flowcharts involved in the above embodiments may include multiple steps or multiple stages. These steps or stages are not necessarily executed at the same time, but can be executed at different times. The execution order of these steps or stages is not necessarily sequential, but can be executed alternately or in turn with at least a part of other steps or steps or stages in other steps.

[0108] Based on the same inventive concept, an embodiment of the present application also provides a transmission line soft fault location device for implementing the transmission line soft fault location method described above. The solution provided by this device to solve the problem is similar to the solution described in the above method. Therefore, the specific limitations in one or more embodiments of the transmission line soft fault location device provided below can refer to the limitations on the transmission line soft fault location method in the above text, and will not be repeated here.

[0109] In an exemplary embodiment, as Figure 4 shown, a transmission line soft fault location device 400 is provided, including:

[0110] A first acquisition module 401, configured to perform pilot estimation on the transmission line based on relatively prime sampling frequencies in the fault-free state and the fault state of the transmission line, and obtain a basic scattering matrix corresponding to the fault-free state and a fault scattering matrix corresponding to the fault state of the transmission line;

[0111] A second acquisition module 402, configured to obtain a differential scattering matrix of the transmission line according to the difference between the basic scattering matrix and the fault scattering matrix;

[0112] A decomposition module 403, configured to perform eigenvalue decomposition on the time reversal operator of the differential scattering matrix to obtain the spatial energy spectrum and pseudo-spectrum of each position to be measured in the transmission line;

[0113] A location module 404, configured to determine the fault location of the transmission line according to the spatial energy spectrum and pseudo-spectrum of each position to be measured.

[0114] In an exemplary embodiment, the device further includes: a first frequency acquisition module, configured to determine a plurality of sampling frequency sets according to the sampling frequency range of the detection port of the transmission line; wherein the sampling frequency intervals of each of the sampling frequency sets are relatively prime; a second frequency acquisition module, configured to obtain the relatively prime sampling frequencies according to each of the sampling frequency sets.

[0115] In an exemplary embodiment, the basic scattering matrix includes basic sub-matrices corresponding to each of the sampling frequency sets; the fault scattering matrix includes fault sub-matrices corresponding to each of the sampling frequency sets; the second acquisition module 402 is further configured to: for each of the sampling frequency sets, obtain a differential sub-matrix corresponding to the sampling frequency set according to the difference between the basic sub-matrix and the fault sub-matrix corresponding to the sampling frequency set; combine the differential sub-matrices of each of the sampling frequency sets to obtain the differential scattering matrix.

[0116] In an exemplary embodiment, the decomposition module 403 is further configured to: perform eigenvalue decomposition on the time-reversal operator of the differential scattering matrix to obtain the eigenvalues of the time-reversal operator and the eigenvectors corresponding to each of the eigenvalues; construct a noise subspace according to each of the eigenvalues and the eigenvectors corresponding to each of the eigenvalues; construct a spatial energy spectrum and a pseudo-spectrum of each of the positions to be measured in the transmission line in the noise subspace according to the cable parameters of the transmission line and the noise subspace.

[0117] In an exemplary embodiment, the decomposition module 403 is further configured to: screen out target eigenvalues that meet the non-significant condition from each of the eigenvalues; construct the noise subspace according to the eigenvectors corresponding to each of the target eigenvalues.

[0118] In an exemplary embodiment, the ratio of the sum of the target eigenvalues to the sum of all eigenvalues is not greater than a preset value, and each target eigenvalue is less than each non-target eigenvalue among the eigenvalues.

[0119] Each module in the above transmission line soft fault location device can be implemented in whole or in part by software, hardware, and their combination. Each of the above modules can be embedded in the processor of the computer device in hardware form or be independent of it, or can be stored in the memory of the computer device in software form, so that the processor can call and execute the operations corresponding to each of the above modules.

[0120] In an exemplary embodiment, a computer device is provided. The computer device can be a server, and its internal structure diagram can be as Figure 5As shown in the figure. The computer device includes a processor, a memory, an input / output interface (Input / Output, abbreviated as I / O), and a communication interface. Among them, the processor, the memory, and the input / output interface are connected through a system bus, and the communication interface is connected to the system bus through the input / output interface. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program, and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The database of the computer device is used to store data such as relatively prime sampling frequencies. The input / output interface of the computer device is used to exchange information between the processor and external devices. The communication interface of the computer device is used to communicate with external terminals through a network connection. When the computer program is executed by the processor, it implements a method for locating soft faults in transmission lines.

[0121] Those skilled in the art can understand that Figure 5 the structure shown in the figure is only a block diagram of some structures related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than those shown in the figure, or combine some components, or have different component arrangements.

[0122] In one embodiment, a computer device is further provided, including a memory and a processor. A computer program is stored in the memory. When the processor executes the computer program, the steps in the above method embodiments are implemented.

[0123] In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by the processor, the steps in the above method embodiments are implemented.

[0124] In one embodiment, a computer program product is provided, including a computer program. When the computer program is executed by the processor, the steps in the above method embodiments are implemented.

[0125] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data for analysis, stored data, displayed data, etc.) involved in the present application are all information and data authorized by the user or fully authorized by all parties, and the collection, use, and processing of relevant data need to comply with relevant regulations.

[0126] Those of ordinary skill in the art can understand that all or part of the processes in the methods of the above embodiments can be completed by instructing relevant hardware through a computer program. The computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above methods. Among them, any reference to a memory, database, or other medium used in the embodiments provided in the present application can include at least one of non-volatile memory and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetoresistive random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM), etc. The databases involved in the embodiments provided in the present application can include at least one of relational databases and non-relational databases. Non-relational databases can include distributed databases based on blockchain, etc., without limitation. The processors involved in the embodiments provided in the present application can be general-purpose processors, central processing units, graphics processors, digital signal processors, programmable logic devices, data processing logics based on quantum computing, artificial intelligence (AI) processors, etc., without limitation.

[0127] The technical features of the above embodiments can be combined arbitrarily. For the sake of concise description, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, it should be considered to be within the scope recorded in the present application.

[0128] The above embodiments merely represent several implementation manners of the present application. The description thereof is relatively specific and detailed, but it should not be construed as a limitation to the patent scope of the present application. It should be noted that for those of ordinary skill in the art, without departing from the concept of the present application, several modifications and improvements can still be made, and these all fall within the protection scope of the present application. Therefore, the protection scope of the present application shall be subject to the appended claims.

Claims

1. A method for locating soft faults in a transmission line, characterized in that: The method comprises: Under the fault-free state and the fault state of the transmission line, respectively, pilot frequency estimation is performed on the transmission line based on the coprime sampling frequency to obtain a basic scattering matrix of the transmission line corresponding to the fault-free state and a fault scattering matrix corresponding to the fault state; Obtaining a differential scattering matrix of the transmission line according to a difference between the basic scattering matrix and the fault scattering matrix; Performing eigenvalue decomposition on the time reversal operator of the differential scattering matrix to obtain a spatial energy spectrum and a pseudo spectrum of each position to be measured in the transmission line; The fault location of the transmission line is determined according to the spatial energy spectrum and pseudo-spectrum of each of the locations to be measured.

2. The method according to claim 1, characterized in that Before performing pilot frequency estimation on the transmission line based on the coprime sampling frequency in the non-fault state and the fault state of the transmission line respectively, the method comprises: Determine a plurality of sampling frequency sets according to the sampling frequency range of the detection port of the transmission line; wherein the sampling frequency intervals of each sampling frequency set are mutually prime; According to each of the sampling frequency sets, the mutually prime sampling frequencies are obtained.

3. The method according to claim 2, characterized in that The basic scattering matrix includes a basic sub-matrix corresponding to each of the sampling frequency sets; the fault scattering matrix includes a fault sub-matrix corresponding to each of the sampling frequency sets; The step of obtaining a differential scattering matrix of the transmission line according to a difference between the basic scattering matrix and the fault scattering matrix comprises: For each of the sampling frequency sets, according to the difference between the basic sub-matrix and the fault sub-matrix corresponding to the sampling frequency set, a differential sub-matrix corresponding to the sampling frequency set is obtained; The differential sub-matrices of each sampling frequency set are combined to obtain the differential scattering matrix.

4. The method according to claim 1, characterized in that: The step of performing eigenvalue decomposition on the time reversal operator of the differential scattering matrix to obtain a spatial energy spectrum and a pseudo spectrum of each position to be measured in the transmission line includes: Performing eigenvalue decomposition on the time reversal operator of the differential scattering matrix to obtain eigenvalues ​​of the time reversal operator and eigenvectors corresponding to each eigenvalue; Constructing a noise subspace according to each of the eigenvalues ​​and the eigenvectors corresponding to each of the eigenvalues; According to the cable parameters of the transmission line and the noise subspace, a spatial energy spectrum and a pseudo-spectrum of each of the locations to be measured in the transmission line in the noise subspace are constructed.

5. The method according to claim 4, characterized in that The constructing a noise subspace according to each of the eigenvalues ​​and the eigenvectors corresponding to each of the eigenvalues ​​comprises: Screening out a target eigenvalue that meets a non-significant condition from among the eigenvalues; The noise subspace is constructed according to the eigenvectors corresponding to the target eigenvalues.

6. The method according to claim 5, characterized in that The ratio of the sum of the target feature values ​​to the sum of each feature value is not greater than a preset value, and each target feature value is smaller than each non-target feature value in the feature values.

7. A transmission line soft fault location device, characterized in that: The device comprises: A first acquisition module is used to perform pilot frequency estimation on the transmission line based on coprime sampling frequencies in a non-fault state and a fault state of the transmission line, respectively, to obtain a basic scattering matrix of the transmission line corresponding to the non-fault state and a fault scattering matrix corresponding to the fault state; A second acquisition module, configured to obtain a differential scattering matrix of the transmission line according to a difference between the basic scattering matrix and the fault scattering matrix; A decomposition module, used for performing eigenvalue decomposition on the time reversal operator of the differential scattering matrix to obtain a spatial energy spectrum and a pseudo spectrum of each position to be measured in the transmission line; A positioning module is used to determine the fault location of the transmission line according to the spatial energy spectrum and pseudo-spectrum of each of the locations to be measured.

8. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 6 are implemented.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 6 are implemented.

10. A computer program product, comprising a computer program, characterized in that When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 6 are implemented.

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