A method and system for locating the breakpoint of a non-operating cable

Abstract

The present invention discloses a method and system for locating the break point of a non-operating cable, belonging to the field of cable monitoring and fault detection. The method includes: injecting a high-frequency pulse signal into the non-operating cable in a normal state to obtain the pulse signal of the non-operating cable in the normal state; injecting a high-frequency pulse signal into the non-operating cable at a preset time interval to obtain the pulse signal of the non-operating cable; performing differential processing on the pulse signal of the non-operating cable obtained each time and the pulse signal in the normal state, and judging the differential signal. When the condition of a fault existing is met, the differential signal is used as a fault signal; decomposing the fault signal to obtain the SGC component containing the cable break point information; calibrating the SGC component to obtain the arrival times of the two wave heads of the fault signal in this component for calculating the position and time of the cable break point. The method of the present invention can provide the relative position and time information between the break point of the non-operating cable and the substation.

Description

Technical Field

[0001] The present invention relates to a method and system for locating breakpoints of non-operating cables, and belongs to the field of cable monitoring and fault detection. Background Art

[0002] With the continuous expansion of power infrastructure, cables are laid for standby power transmission, and these cables are in a non-operating state or waiting to be enabled. However, due to the lack of actual load and current flow in these non-operating cables, there are no effective monitoring and detection means, making them vulnerable to theft. Traditional cable anti-theft monitoring methods usually rely on simple judgments on whether the cable has physical damage or breakage, but often cannot provide accurate breakpoint location information and cannot monitor abnormal events in real time when the cable is offline or not transmitting current.

[0003] In addition, most of the existing breakpoint detection methods focus on judging faults by changes in current or voltage when the cable is in a normal operating state; however, these methods are not applicable to the case of non-operating cables because there is no current flow in the cable in the non-operating state, and it is impossible to judge cable damage or theft through conventional current and voltage monitoring means; manual inspections also have problems such as poor timeliness and limited coverage, especially at night or in unattended situations, it is difficult to detect in time whether the cable has a breakpoint; due to the inability to obtain cable status data in real time, there are large blind spots in the anti-theft monitoring of non-operating cables by traditional methods.

[0004] In view of this, the present invention is specifically proposed. Summary of the Invention

[0005] The present invention provides a method and system for locating breakpoints of non-operating cables, which can monitor the cable status in real time when the cable is in a non-operating state, and effectively locate the position and time of the cable breakpoint (i.e., provide the relative position and time information between the cable breakpoint and the substation), thereby improving the anti-theft / fault monitoring ability of cables in the power system and reducing economic losses and project delays caused by cable faults.

[0006] The technical solution of the present invention is as follows:

[0007] According to the first aspect of the present invention, a method for locating breakpoints of non-operating cables is provided, including the following steps:

[0008] Step 1: Inject a high-frequency pulse signal into the non-operating cable in a normal state to obtain the pulse signal of the non-operating cable in a normal state;

[0009] Step 2: Inject a high-frequency pulse signal into the non-operating cable at a preset time interval to obtain the pulse signal of the non-operating cable;

[0010] Step 3: Perform differential processing on the pulse signal of the non-operating cable obtained each time and the pulse signal in the normal state, judge the differential signal, and when the condition of a fault existing is met, use the differential signal as the fault signal;

[0011] Step 4: Decompose the fault signal to obtain the component containing cable break point information;

[0012] Step 5: Calibrate the component to obtain the arrival times of the two wave heads of the fault signal in this component;

[0013] Step 6: Combine the calibrated arrival times of the wave heads to calculate the position and time of the cable break point.

[0014] Further, the acquisition of the signals in Steps 1 and 2 is specifically as follows: Install a low-voltage high-frequency signal generation module and a high-frequency reflected wave detection module at the substation incoming line; Inject high-frequency pulse signals into the non-operating cable by the low-voltage high-frequency signal generation module according to a preset time interval; Real-time acquire the pulse signal of the cable by the high-frequency reflected wave detection module.

[0015] Further, for the judgment of the differential signal, one of the following is adopted: Obtain the extreme points of the differential signal, judge the amplitude of the differential signal.

[0016] Further, the obtaining of the extreme points of the differential signal is specifically as follows: If the number of extreme points is greater than the first preset value, it is considered that the pulse signal of the non-operating cable obtained currently has a fault.

[0017] Further, the judgment of the amplitude of the differential signal is specifically as follows: If the maximum value of the amplitude of the differential signal is greater than the second preset value, it is considered that the pulse signal of the non-operating cable obtained currently has a fault.

[0018] Further, Step 4 is specifically as follows: Use the clustering symplectic geometry algorithm to decompose the fault signal to obtain the component containing cable break point information.

[0019] Further, the decomposition of the fault signal by using the clustering symplectic geometry algorithm includes the following steps:

[0020] Step 4.1: Reconstruct the fault signal to obtain a trajectory matrix;

[0021] Step 4.2: Construct a first Hamiltonian matrix through the trajectory matrix; According to the first Hamiltonian matrix, construct a second Hamiltonian matrix;

[0022] Step 4.3: Both the first Hamiltonian matrix and the second Hamiltonian matrix are Hamiltonian matrices, so as to construct a symplectic orthogonal matrix to obtain the eigenvectors of the covariance symmetric matrix; the covariance symmetric matrix is obtained from the autocorrelation analysis of the trajectory matrix.

[0023] Step 4.4: According to the eigenvectors of the covariance symmetric matrix and the trajectory matrix, calculate the transformation coefficient matrix, so as to construct a single set of trajectory matrices. ;

[0024] Step 4.5: Transform into a set of reconstructed signals with a length of ; perform diagonal averaging on the remaining single set of trajectory matrices in turn, so as to obtain sets of reconstructed signals for the decomposition of the output signal.

[0025] Step 4.6: Use the clustering algorithm to screen the reconstructed signals corresponding to the normal values for linear superposition, so as to obtain the h-th , and then remove from the fault signal, and record the residual signal as ;

[0026] Step 4.7: Calculate the RMSE between the residual signal and the fault signal.

[0027] Step 4.8: Set the iteration threshold : If , then construct the residual signal as a new trajectory matrix, and repeat Steps 4.2 - 4.7, with the iteration number h = h + 1 until is satisfied.

[0028] Further, the clustering algorithm is the DBSCAN clustering algorithm.

[0029] Further, Step 5 is specifically: for the component, apply the second-order transient extraction algorithm to calibrate the arrival times of the two wave heads of the fault signal in this component.

[0030] Further, Step 6 is specifically:

[0031] Step 6.1: Substitute the two wave head times and obtained by STET into the following formula:

[0032] ;

[0033] In the formula, is the distance of the cable break point from the substation, is the wave velocity of the fault signal; and is the arrival time of two waveheads of the fault signal;

[0034] Step 6.2: Using the obtained Substitute into to calculate the cable break point time .

[0035] According to the second aspect of the present invention, there is provided a break point positioning system for a non-operating cable, including the break point positioning method for a non-operating cable described in any one of the above.

[0036] According to the third aspect of the present invention, there is provided a processor, and the processor is used to perform operations, and the operations include performing the break point positioning method for a non-operating cable described in any one of the above.

[0037] The beneficial effects of the present invention are as follows: By adopting the high-frequency pulse signal injection and reflection wave detection technology, the problem of fault location of non-operating cables is effectively solved. When the cable is not in the operating state, the traditional current and voltage monitoring means cannot play a role, while the present invention can detect the cable state in real time and accurately locate the break point position through the combination of differential processing and the clustering symplectic geometry algorithm, avoiding the monitoring blind area caused by no current flow in the traditional method. Specifically, the present invention successfully calibrates the arrival time of the wavehead of the fault signal through the clustering symplectic geometry algorithm and the second-order transient extraction algorithm, and calculates the fault position and time of the cable through the improved single-end method, with high positioning accuracy. This method greatly improves the anti-theft and fault monitoring capabilities of non-operating cables in the power system, providing a strong guarantee for the safe operation of power infrastructure. Description of the Drawings

[0038] Figure 1 is the flowchart of the break point positioning method for a non-operating cable of the present invention;

[0039] Figure 2 is the signal waveform diagram detected by the high-frequency reflection wave detection module under normal conditions;

[0040] Figure 3 is the signal waveform diagram detected by the high-frequency reflection wave detection module when the break point is 2 km away from the substation;

[0041] Figure 4 is the waveform diagram of the differential fault signal when the break point is 2 km away from the substation;

[0042] Figure 5 is the diagram of each mode of the fault signal decomposed by the clustering symplectic geometry algorithm when the break point is 2 km away from the substation;

[0043] Figure 6 is the component diagram of the clustering symplectic geometry algorithm when the break point is 2 km away from the substation;

[0044] Figure 7 Wavefront extraction diagram of the second-order transient extraction algorithm when the breakpoint is 2 km away from the substation;

[0045] Figure 8 Wavefront extraction diagram of the second-order transient extraction algorithm when the breakpoint is 1 km away from the substation;

[0046] Figure 9 Wavefront extraction diagram of the second-order transient extraction algorithm when the breakpoint is 3 km away from the substation;

[0047] Figure 10 Wavefront extraction diagram of the second-order transient extraction algorithm when the breakpoint is 4 km away from the substation;

[0048] Figure 11 Wavefront extraction diagram of the second-order transient extraction algorithm when the breakpoint is 5 km away from the substation. Specific implementation manner

[0049] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention. It should be noted that, without conflict, the embodiments in the present application and the features in the embodiments may be arbitrarily combined with each other.

[0050] As Figures 1-11 shown, according to the first aspect of the embodiments of the present invention, a method for locating the breakpoint of a non-operating cable is provided, including the following steps:

[0051] Step 1: Inject a high-frequency pulse signal into the non-operating cable in a normal state to obtain the pulse signal of the non-operating cable in the normal state;

[0052] Step 2: Inject a high-frequency pulse signal into the non-operating cable at a preset time interval to obtain the pulse signal of the non-operating cable;

[0053] In specific applications, the following operations can be performed: Install a low-voltage high-frequency signal generation module and a high-frequency reflected wave detection module at the incoming line of the substation; Inject a high-frequency pulse signal into the non-operating cable at a preset time interval through the low-voltage high-frequency signal generation module; Obtain the pulse signal of the cable in real time through the high-frequency reflected wave detection module. Further, the low-voltage high-frequency signal generation module can generate a high-frequency pulse signal, the frequency of the generated pulse signal can be adjusted within the range of 5000 - 16000 Hz, the amplitude can be adjusted within the range of 12 - 48 V, and the pulse signal emission interval time of the pulse signal source is adjustable, and the interval time range is 0 - 10 minutes, so as to adapt to the detection needs of different types of cables;

[0054] Step 3: Perform differential processing on the pulse signal of the non-operating cable obtained each time and the pulse signal in the normal state, judge the differential signal, and when the condition of a fault existing is met, use the differential signal as the fault signal;

[0055] The judgment of the differential signal is specifically as follows:

[0056] Find the extreme points of the differential signal: If the number of extreme points is greater than the first preset value, it is considered that there is a fault in the pulse signal of the non-operating cable currently obtained. Exemplarily, the first preset value is taken as 10.

[0057] Alternatively, judge the amplitude of the differential signal: If the maximum value of the amplitude of the differential signal is greater than the second preset value, it is considered that there is a fault in the pulse signal of the non-operating cable currently obtained. Exemplarily, the second preset value is taken as 0.01 Vpu, where Vpu represents the amplitude of the high-frequency pulse signal emitted by the low-voltage high-frequency signal generation module.

[0058] Step 4: Decompose the fault signal using the clustering symplectic geometry algorithm to obtain a symplectic geometry component (SGC) containing cable break point information;

[0059] The decomposition of the fault signal using the clustering symplectic geometry algorithm includes the following steps:

[0060] Step 4.1: Reconstruct the fault signal to obtain a trajectory matrix ;

[0061] X = [ x 1 x 1 + γ ⋯ x 1 + ( d − 1 ) γ x 2 x 2 + γ ⋯ x 2 + ( d − 1 ) γ ⋮ ⋮ ⋮ x m x m + γ ⋯ x m + ( d − 1 ) γ ]

[0062] where n represents the length of the fault signal; ; is the embedding dimension; is the delay time; the delay time is determined by the C-C method, and the delay time is taken; the embedding dimension is determined by the power spectral density of the fault signal: Let be the sampling frequency, be the fault signal corresponding to the maximum peak of the power spectral density; if the normalized frequency is less than the given threshold , then the embedding dimension , otherwise the embedding dimension ;

[0063] Step 4.2: Through the trajectory matrix Construct the first Hamiltonian matrix , and the expression is as follows:

[0064] M = [ A 0 0 − A T ]

[0065] In the formula, is the covariance symmetric matrix, obtained from the autocorrelation analysis of the trajectory matrix ;

[0066] According to the definition of the Hamiltonian matrix, the squared Hamiltonian matrix still belongs to the Hamiltonian matrix, so the second Hamiltonian matrix ;

[0067] Step 4.3: , are both Hamiltonian matrices, so the symplectic orthogonal matrix is constructed, and the expression is as follows:

[0068] Q T FQ = [ B R 0 B T ]

[0069] In the formula, is the sub-matrix after matrix transformation; is the upper triangular matrix, and its eigenvalues are ; According to the characteristics of the Hamiltonian matrix, the eigenvalues of the covariance symmetric matrix are: , and the eigenvector corresponding to the eigenvalue is ;

[0070] Step 4.4: Calculate the transformation coefficient matrix based on the eigenvectors of the covariance symmetric matrix and the trajectory matrix , so as to construct a single set of trajectory matrices ; Reconstruct the trajectory matrix is composed of and can be denoted as ;

[0071] Since is a matrix, diagonal averaging is needed to convert it into a reconstructed signal with a length of ; Define the elements in as , where , , and let ;

[0072] Step 4.5: Convert into a set with a length of according to the following formula​ Reconstructed signal ; Perform diagonal averaging on the remaining single-group trajectory matrices in sequence, so as to obtain the group of reconstructed signals of the output signal decomposition;

[0073]

[0074] In the formula, , , ;

[0075] Step 4.6: There is a periodic similarity among the group of reconstructed signals obtained by diagonal averaging. Therefore, use the Density-Based Spatial Clustering of Applications with Noise (DBSCAN) algorithm to screen the reconstructed signals corresponding to normal values for linear superposition, so as to obtain the h-th , and then is removed from the fault signal , and the residual signal is denoted as ; ;

[0076]

[0077] In the formula, is the number of iterations (the initial value is taken as 1);

[0078] Among them, the specific steps of the DBSCAN clustering algorithm are as follows: First, select appropriate neighborhood values and density threshold as the input of the clustering algorithm. In the present invention, and take values of 0.05 and 4; then, use the DBSCAN clustering algorithm to complete the clustering of the reconstructed signals, and output the clustering results, core points, boundary points and outlier points; finally, perform anomaly judgment, take the largest category of the reconstructed signals as normal values, and the others as abnormal values, and obtain the reconstructed signals corresponding to normal values.

[0079] Step 4.7: Calculate the root mean square error (RMSE) between the residual signal and the fault signal . When is removed from the fault signal , the RMSE decreases accordingly, and the RMSE gradually decreases as the number of iterations increases; thus, the RMSE can be used as the iteration termination condition to constrain the over-decomposition problem;

[0080]

[0081] Step 4.8: Set the iteration threshold : If , then construct the residual signal as a new trajectory matrix, repeat Steps 4.2 - 4.7, and the iteration count h = h + 1 until is satisfied, thereby obtaining the final result.

[0082] Step 5: For the component, apply the second - order transient extraction algorithm (second - order transient extraction transform, STET) to calibrate the arrival times of the two wavefronts of the fault signal in this component; the specific steps are as follows:

[0083] Step 5.1: Take the component as the function to perform the short - time Fourier transform (Short - Time Fourier Transform, STFT) to obtain , and the calculation formula is:

[0084]

[0085] In the formula, is the sliding window, is the kernel function of the Fourier transform, is the angular frequency, represents the integration variable in the short - time Fourier transform.

[0086] Step 5.2: The impulsive components in are usually represented by the Dirac

[0087]

[0088] In the formula, is the amplitude of the impulsive component, is the moment when the impulse occurs. Combining , we can obtain:

[0089]

[0090] Ideally, the STFT transform result of the Dirac function should be concentrated at the impulse occurrence moment . The time - frequency analysis algorithm usually uses the time - frequency energy where the two - dimensional group delay rearrangement diverges as , and the calculation formula is as follows:

[0091]

[0092] In the formula: is the real part; is the derivative with respect to the frequency variable.

[0093] Combining the above formula with , we get:

[0094]

[0095] The above formula shows that the two-dimensional group delay of the impulse component STFT result focuses on the occurrence time ;

[0096] Step 5.3: According to this characteristic, the second-order transient extraction transform first constructs a second-order frequency change model, that is:

[0097]

[0098] In the formula, is the Fourier transform of the signal, and are the amplitude and phase in the frequency domain of the signal, and are the first-order derivative function and the second-order derivative function of the signal phase , is a symbol used to represent frequency change during the frequency analysis process, usually used together with other frequency variables to help analyze and understand the characteristics of the signal in the frequency domain.

[0099] Step 5.4: With the help of the window function , the STFT transform of the above formula is:

[0100]

[0101] In the formula, is the width of the window function.

[0102] The path to calculate the two-dimensional group delay , and the calculation formula is:

[0103]

[0104] In the formula, is the derivative with respect to the time variable.

[0105] Step 5.5: According to the two-dimensional group delay calculation method defined by the above formula, and considering the relevant constraints, the two-dimensional group delay of the second-order frequency change model can be expressed as follows:

[0106]

[0107] In the formula, is the derivative with respect to the frequency variable, is the derivative with respect to the time variable, is the derivative with respect to the time variable, is the derivative with respect to the frequency variable.

[0108] Step 5.6: Using the above formula, the second-order transient transform of can be obtained as:

[0109]

[0110] In the formula, indicates that the signal undergoes an instantaneous change at time , is the Dirac function, representing the impact or instantaneous signal of the signal at a specific time point.

[0111] Step 5.7: Select the time of the first two mutation values after the second-order transient transform as the arrival times of the two wavefronts of the fault signal and .

[0112] Step 6: Combine the calibrated arrival times of the wavefronts and use the improved single-end method to calculate the location and time of the cable break point.

[0113] Step 6.1: Substitute the two wavefront times and obtained by STET into the following formula to get:

[0114]

[0115] In the formula, is the distance of the cable break point from the substation, is the wave velocity of the fault signal; , respectively represent the positive-sequence inductance and capacitance;

[0116] Step 6.2: Use the obtained to substitute into to calculate the cable break point time .

[0117] Applying the above technical solution, by introducing the clustering symplectic geometry algorithm, the present invention can efficiently decompose fault signals, deeply mine their multiple features, and has significant advantages especially in the complex reflection wave scenarios generated by cable breakpoints. This algorithm decomposes the signal into multiple sub-signals and classifies them based on geometric characteristics, thereby accurately extracting the high-frequency components of the fault signal. At the same time, the second-order transient extraction algorithm is used to accurately calibrate the arrival time of the wavefront, which has higher sensitivity and timeliness compared with the traditional first-order method. By analyzing the second derivative characteristics of the signal, this algorithm can accurately identify the rapid change points in the waveform to ensure the accurate calibration of the arrival time of the reflection wave. The combination of the two technologies enables the present invention to have excellent positioning accuracy in cable fault location, thus providing a strong guarantee for the safe operation of the power system.

[0118] Now, the method of the present invention is applied to a simulation environment for verification, and the simulation is carried out as follows:

[0119] The first group of simulations:

[0120] The frequency of the high-frequency pulse signal emitted by the low-voltage high-frequency signal generation module is set to 5000 Hz, and the amplitude is set to 48 V; the breakpoint position is set to 2 km, and the breakpoint time is set to 0.005 s. The cable line parameters are shown in Table 1.

[0121] Table 1

[0122]

[0123] Figure 2 It is the signal waveform diagram detected by the high-frequency reflection wave detection module when it is normal. The figure shows that when the cable is in a normal state, the waveform of the reflection wave is stable and regular, and there are no abnormal waveforms. This figure is used as a reference waveform for subsequent comparison with abnormal signal waveforms.

[0124] Figure 3 It is the signal waveform diagram detected by the high-frequency reflection wave detection module when the breakpoint is 2 km away from the substation. The figure shows that when a breakpoint occurs in the cable, the waveform of the reflection wave has changed significantly. The abnormal change in the waveform can promptly indicate the breakpoint fault caused by cable damage or theft.

[0125] Figure 4 It is the waveform diagram of the differential fault signal when the breakpoint is 2 km away from the substation. The figure shows the waveform of the fault signal after differential processing of the pulse signal at the breakpoint and the pulse signal in the normal state. Through this waveform, the system can identify the abnormal state of the cable and calculate the specific location where the fault occurred.

[0126] Figure 5When the breakpoint is 2 km away from the substation, it is the modal diagram of the fault signal decomposed by the clustering symplectic geometric algorithm. The figure shows the modal signals obtained by decomposing the fault signal using the clustering symplectic geometric algorithm. By analyzing the obtained modal signals, the system can identify the specific location of the cable breakpoint, providing accurate data for further positioning calculations.

[0127] Figure 6 When the breakpoint is 2 km away from the substation, it is the component diagram of the clustering symplectic geometric algorithm. This figure shows the components extracted in the clustering symplectic geometric algorithm. This component diagram reveals the characteristics of the abnormal signals generated at the cable breakpoint for subsequent wavefront extraction and positioning calculations.

[0128] Figure 7 When the breakpoint is 2 km away from the substation, it is the wavefront extraction diagram of the second-order transient extraction algorithm. This figure shows how to accurately extract the wavefront from the reflected signal through the second-order transient extraction algorithm. The extracted wavefront information provides key data for subsequent positioning calculations, ensuring that the time and location of the cable breakpoint can be accurately determined. Two wavefront times can be obtained from the figure = 0.0050071 s and = 0.0050213 s. It is calculated that the distance of the cable breakpoint from the substation = 1995.46 m differs from the set 2 km by 4.56 m, with a relative error of 0.23%, meeting the 1% accuracy requirement; the cable breakpoint time = 0.0050001 s differs from the set 0.005 s by 0.000001 s, with a relative error of 0.002%.

[0129] The second group of simulations:

[0130] When the breakpoint position is set to 1 km and the breakpoint time is set to 0.005 s, the frequency of the high-frequency pulse signal emitted by the low-voltage high-frequency signal generation module is set to 5000 Hz, and the amplitude is set to 48 V. Figure 8 When the breakpoint is 1 km away from the substation, it is the wavefront extraction diagram of the second-order transient extraction algorithm. Two wavefront times can be obtained from the figure = 0.0050036 s and = 0.0050107 s. It is calculated that the distance of the cable breakpoint from the substation = 997.73 m differs from the set 1 km by 2.27 m, with a relative error of 0.23%, meeting the 1% accuracy requirement; the cable breakpoint time = 0.00500005 s differs from the set 0.005 s by 0.0000005 s, with a relative error of 0.001%.

[0131] The third group of simulations:

[0132] When the breakpoint position is set to 3 km and the breakpoint time is set to 0.005 s, the frequency of the high-frequency pulse signal emitted by the low-voltage high-frequency signal generation module is set to 5000 Hz, and the amplitude is set to 48 V. Figure 9 It is the wavefront extraction diagram of the second-order transient extraction algorithm when the breakpoint is 3 km away from the substation. Two wavefront times can be obtained from the figure = 0.0050107 s and = 0.0050032 s. It is calculated that the distance between the cable breakpoint and the substation = 2993.18 m differs from the set 3 km by 6.82 m, and the relative error is 0.23%, meeting the accuracy requirement of 1%; the cable breakpoint time = 0.00500005 s differs from the set 0.005 s by 0.0000005 s, and the relative error is 0.001%.

[0133] The fourth group of simulations:

[0134] When the breakpoint position is set to 4 km and the breakpoint time is set to 0.005 s, the frequency of the high-frequency pulse signal emitted by the low-voltage high-frequency signal generation module is set to 5000 Hz, and the amplitude is set to 48 V. Figure 10 It is the wavefront extraction diagram of the second-order transient extraction algorithm when the breakpoint is 1 km away from the substation. Two wavefront times can be obtained from the figure = 0.0050142 s and = 0.0050427 s. It is calculated that the distance between the cable breakpoint and the substation = 4004.96 m differs from the set 4 km by 4.96 m, and the relative error is 0.12%, meeting the accuracy requirement of 1%; the cable breakpoint time = 0.00499995 s differs from the set 0.005 s by 0.0000005 s, and the relative error is 0.001%.

[0135] The fifth group of simulations:

[0136] When the breakpoint position is set to 5 km and the breakpoint time is set to 0.005 s, the frequency of the high-frequency pulse signal emitted by the low-voltage high-frequency signal generation module is set to 5000 Hz, and the amplitude is set to 48 V. Figure 11 It is the wavefront extraction diagram of the second-order transient extraction algorithm when the breakpoint is 1 km away from the substation. Two wavefront times can be obtained from the figure = 0.0050178 s and = 0.0050534 s. It is calculated that the distance between the cable breakpoint and the substation = 5002.69 m differs from the set 5 km by 2.69 m, and the relative error is 0.12%, meeting the accuracy requirement of 1%; the cable breakpoint time = 0.005 s is the same as the set 0.005 s without error.

[0137] The sixth group of simulations:

[0138] To verify the superiority of the positioning method of the present invention, the method of the present invention is compared with two methods: symplectic geometry mode decomposition-second-order transient extraction transform (SGMD-STET) and variational mode decomposition - Teager energy operator (VMD - TEO). The results are shown in Table 2. It can be seen from the table that at 1 km, the absolute ranging errors of SGM-STET and VMD-TEO are 25.83 m and 30.38 m respectively, and the relative errors are 2.58% and 3.04% respectively, both exceeding 1%, which cannot meet the positioning requirements. The average relative error of the method of the present invention is 0.20%, which is much lower than 1.26% and 1.81% of SGM-STET and VMD-TEO, indicating that the positioning accuracy of the method of the present invention is much higher than these two methods of SGM-STET and VMD-TEO.

[0139] Table 2

[0140]

[0141] According to the second aspect of the embodiments of the present invention, a break point positioning system for a non-operating cable is provided, including the break point positioning method for a non-operating cable described in any one of the above. Specifically, it includes: a first module for performing step 1: injecting a high-frequency pulse signal into the non-operating cable in a normal state to obtain the pulse signal of the non-operating cable in the normal state; a second module for performing step 2: injecting a high-frequency pulse signal into the non-operating cable according to a preset time interval to obtain the pulse signal of the non-operating cable; a third module for performing step 3: performing differential processing on the pulse signal of the non-operating cable obtained each time and the pulse signal in the normal state, and judging the differential signal. In the case of satisfying the existence of a fault, the differential signal is used as a fault signal; a fourth module for performing step 4: decomposing the fault signal to obtain a component containing cable break point information; a fifth module for performing step 5: for Calibrate the component to obtain the arrival times of the two wavefronts of the fault signal in this component; The sixth module is used to execute step 6: Combine the calibrated arrival times of the wavefronts to calculate the position and time of the cable break point. For the parts not detailed in the above modules, reference can be made to other descriptions of this embodiment.

[0142] According to the third aspect of the embodiments of the present invention, a processor is provided, and the processor is used to execute operations, and the operations include executing the breakpoint positioning method of the non-operating cable described in any one of the above.

[0143] The specific embodiments of the present invention have been described in detail above in conjunction with the accompanying drawings. However, the present invention is not limited to the above embodiments. Within the scope of knowledge possessed by those of ordinary skill in the art, various changes can be made without departing from the gist of the present invention.

Claims

1. A method for locating the break point of a non-operating cable, characterized in that It includes the following steps: Step 1: Inject a high-frequency pulse signal into the non-operating cable in a normal state to obtain the pulse signal of the non-operating cable in the normal state; Step 2: Inject a high-frequency pulse signal into the non-operating cable at a preset time interval to obtain the pulse signal of the non-operating cable; Step 3: Perform differential processing on the pulse signal of the non-operating cable obtained each time and the pulse signal in the normal state, judge the differential signal, and when the condition of a fault existing is met, use the differential signal as the fault signal; Step 4: Decompose the fault signal to obtain the component that contains cable break point information; Step 5: Calibrate the component to obtain the arrival times of the two wavefronts of the fault signal in this component; Step 6: Combine the calibrated wavefront arrival time to calculate the position and time of the cable break point; The acquisition of the signals in Steps 1 and 2 is specifically as follows: Install a low-voltage high-frequency signal generation module and a high-frequency reflection wave detection module at the substation incoming line; Inject a high-frequency pulse signal into the non-operating cable by the low-voltage high-frequency signal generation module at a preset time interval; Real-time obtain the pulse signal of the cable through the high-frequency reflection wave detection module; Step 4 specifically includes: decomposing the fault signal by using the clustering symplectic geometry algorithm to obtain the component containing cable breakpoint information; The decomposition of the fault signal using the clustering symplectic geometry algorithm includes the following steps: Step 4.1: Reconstruct the fault signal to obtain a trajectory matrix; Step 4.2: Construct a first Hamiltonian matrix through the trajectory matrix; According to the first Hamiltonian matrix, construct a second Hamiltonian matrix; Step 4.3: Both the first Hamiltonian matrix and the second Hamiltonian matrix are Hamiltonian matrices, so as to construct a symplectic orthogonal matrix to obtain the eigenvectors of the covariance symmetric matrix; The covariance symmetric matrix is obtained from the autocorrelation analysis of the trajectory matrix; Step 4.4: Calculate the transformation coefficient matrix based on the eigenvectors of the covariance symmetric matrix and the trajectory matrix, thereby constructing a single set of trajectory matrices ; Step 4.5: Convert into a set of reconstructed signals with a length of ; perform diagonal averaging on the remaining single set of trajectory matrices in sequence, so as to obtain sets of reconstructed signals for the decomposition of the output signal; Step 4.6: Use the clustering algorithm to screen the reconstructed signals corresponding to the normal values for linear superposition, so as to obtain the h-th , and then is removed from the fault signal, and the residual signal is denoted as ; Step 4.7: Calculate the residual signal between ; Step 4.8: Set the iteration threshold : If , then construct the residual signal as the new trajectory matrix, repeat Steps 4.2 - 4.7, and increment the iteration count h = h + 1 until ; The specific content of step 5 is as follows: For the component, apply the second-order transient extraction algorithm to calibrate the arrival times of the two wavefronts of the fault signal in this component.

2. The breakpoint positioning method for a non-in-transit cable according to claim 1, characterized in that, The judgment of the differential signal adopts one of the following: Obtain the extreme points of the differential signal, judge the amplitude of the differential signal.

3. The breakpoint positioning method for non-in-transit cables according to claim 2, characterized in that, The obtaining of the extreme points of the differential signal is specifically as follows: If the number of extreme points is greater than the first preset value, it is considered that the pulse signal of the non-operating cable obtained currently has a fault.

4. The breakpoint positioning method for a non-in-transit cable according to claim 2, characterized in that The judgment of the amplitude of the differential signal is specifically as follows: If the maximum value of the amplitude of the differential signal is greater than the second preset value, it is considered that the pulse signal of the non-operating cable obtained currently has a fault.

5. The method for locating the break point of a non-in-transit cable according to claim 1, wherein The clustering algorithm is the DBSCAN clustering algorithm.

6. The breakpoint positioning method for the non-in-operation cable according to claim 1, wherein, Step 6 is specifically as follows: Step 6.1: Using the two wavefront times obtained by STET and Substitute into the following formula to obtain: ； Wherein, is the distance of the cable breakpoint from the substation, is the wave velocity of the fault signal; and are the arrival times of the two wavefronts of the fault signal; Step 6.2: Using the obtained substitute into to calculate the cable break point time .

7. A break point positioning system for a non-operating cable, characterized in that, It includes the method for locating the break point of the non-operating cable according to any one of claims 1-6.

8. A processor, characterized in that, The processor is used to execute operations, and the operations include executing the method for locating the break point of the non-operating cable according to any one of claims 1-6.

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