Line fault location method, device and medium

Abstract

This invention provides a method, apparatus, and medium for determining line fault location, relating to the field of line fault technology. The method includes: after a fault is confirmed to occur within the line's fault zone, freezing the equivalent propagation velocity and extracting data from both ends within a predetermined time period before and after the fault; constructing two-end fault components based on the pre-fault steady-state data; extracting differential and energy features from the two-end fault components respectively, normalizing them, and then weighted and fusing them to obtain composite wavefront detection features; setting an adaptive threshold based on the background statistics of the composite wavefront features before the fault, comparing the composite wavefront features with the adaptive threshold, and extracting the first arrival sampling points at both ends; performing subsampling interpolation correction on the first arrival sampling points to obtain the corrected first arrival times at both ends; calculating and outputting the fault distance based on the difference between the corrected first arrival times at both ends, the equivalent propagation velocity, and the total line length. This invention can reduce the impact of ideal wave velocity setting errors, sampling discretization errors, wavefront distortion, and measurement noise on the distance measurement results.

Description

Technical Field

[0001] This invention relates to the field of line fault technology, and in particular to a method, device and medium for measuring line faults. Background Technology

[0002] With the widespread application of new energy grid connection, flexible power transmission, power electronic loads, and multi-converter equipment in power systems, the disturbances experienced by transmission lines are no longer limited to the traditional power frequency and low-frequency transient range. Converter control, switching processes, harmonic oscillations, and interactions between multiple devices can all superimpose broadband components into the voltage and current signals at the line ends, causing phenomena such as wavefront distortion, frequency-dependent attenuation, end reflections, and multipath propagation in the fault transient waveform. Under these conditions, fault location depends not only on the time it takes for the fault wavefront to reach both ends of the line, but also on factors such as the selection of propagation speed, wavefront identification accuracy, sampling discretization, signal preprocessing, and measurement link delay.

[0003] Existing methods for locating transmission line faults mainly include impedance methods, traveling wave methods, transient quantity location methods, and data-driven location methods. Impedance methods typically calculate the measured impedance based on the voltage and current after the fault to estimate the fault distance. They have advantages such as simplicity and mature engineering applications. However, when the transition resistance is large, the fault current is weak, or the fault characteristics of transmission lines from renewable energy plants are complex, the location accuracy is easily affected by power supply characteristics, fault resistance, and control strategies. Traveling wave location methods calculate the fault distance using the time difference between the arrival of the initial transient wavefront at both ends of the line. They have advantages such as fast response speed and suitability for transient ranging. However, their location accuracy is highly dependent on the accurate identification of the first arriving wavefront and the appropriate setting of the propagation speed.

[0004] In practical engineering, fault transient wavefronts do not always exhibit ideal spikes. Line distribution parameters, frequency correlation characteristics, end reflections, measurement noise, sampling intervals, and signal preprocessing can all alter the wavefront morphology and detection arrival time. Especially in scenarios involving cables, flexible DC lines, high-voltage transmission lines, and new power systems with broadband disturbances, directly applying ideal theoretical wave velocities or single wavefront criteria for fault location may lead to increased ranging errors and decreased stability of the location results. Meanwhile, while some data-driven location methods can learn fault waveform characteristics using a large number of samples, their performance typically depends on the coverage of the training samples, and their physical interpretability and robustness to unseen conditions remain insufficient.

[0005] Therefore, there is an urgent need for a line fault location method to reduce the impact of ideal wave velocity setting error, wavefront distortion, measurement noise, and sampling discretization on the location results. Summary of the Invention

[0006] In view of this, the purpose of the present invention is to provide a method, device and medium for fault location of transmission lines, so as to reduce the influence of ideal wave velocity setting error, sampling discretization error, wavefront distortion and measurement noise on the location results, and improve the accuracy, stability and engineering interpretability of fault location of transmission lines under complex broadband disturbance conditions.

[0007] In a first aspect, embodiments of the present invention provide a method for locating line faults, including: Acquire voltage and current data simultaneously sampled at both ends of the line; A multi-input multi-output finite impulse response port propagation model is established between the two ends of the line using health operation data. The expression for the port propagation model is as follows:

[0008] in, The order of the finite impulse response model; For the first The port propagation coefficient matrix corresponding to each discrete delay; To account for modeling errors and measurement noise; The input vector consists of voltage and current. The output vector is composed of voltage and current; From the model coefficients, the main propagation channel is selected based on the impulse response energy of each channel. The coefficients are then normalized by energy, and the effective propagation delay is extracted. The energy of the main propagation channel is defined as follows:

[0009] in, For the first The total energy of each candidate propagation channel This indicates the channel number. The square of the magnitude of each discrete delay coefficient The model order is the finite impulse response model. The equivalent propagation speed is constructed based on the total length of the route and the effective propagation delay. The equivalent propagation speed is defined as follows:

[0010] in, The equivalent propagation velocity used for fault location; The total length of the line; This refers to the effective propagation delay extracted from the main propagation channel; Once a fault is confirmed to have occurred within the line area, the equivalent propagation speed is frozen and data from both ends within a predetermined time period before and after the fault is captured. Construct a two-ended fault component based on the pre-fault steady-state data; Differential features and energy features are extracted from the two-end fault components, and then normalized and weighted to obtain the composite wavefront detection features. An adaptive threshold is set based on the background statistics of the composite wavefront features before the fault. The composite wavefront features are compared with the adaptive threshold to extract the first-arrival sampling points at both ends. Subsampling interpolation correction is performed on the first arrival sampling point to obtain the corrected double-ended first arrival time; Based on the corrected difference in the first arrival times at both ends, the equivalent propagation speed, and the total line length, the fault distance is calculated and output. The expression for the fault distance is:

[0011] in, The corrected first arrival time is the time when the fault wavefront arrives at one end. To correct the first arrival time of the faulty wavefront at the other end, The actual time when the fault occurred. This is the equivalent propagation speed.

[0012] Optionally, the coefficient matrix of the multiple-input multiple-output finite impulse response port propagation model contains four propagation channels: the starting-end voltage to the ending-end voltage channel, the starting-end current to the ending-end voltage channel, the starting-end voltage to the ending-end current channel, and the starting-end current to the ending-end current channel.

[0013] Optionally, the main propagation channel is the propagation channel with the largest impulse response energy; the effective propagation delay is the delay time corresponding to when the cumulative propagation energy first reaches half of the total energy.

[0014] Optionally, an equivalent propagation speed can be constructed based on the total length of the line and the effective propagation delay, including: Establish port propagation models for both the forward and reverse directions; Calculate the equivalent propagation velocity in both directions; When the two ends of the line are symmetrical, the average speed in both directions is taken as the uniform speed; When the two ends of the line are asymmetrical, distance measurement is calculated using speeds in different directions.

[0015] Optional methods for constructing fault components include: Using the pre-fault steady-state data as a benchmark, the fault component is obtained by subtracting the real-time sampled value in the fault ranging data window from the corresponding steady-state background reference value.

[0016] Optionally, the differential features are obtained by performing a first-order difference operation on the two-terminal fault components; the energy features are obtained by performing a Teager energy operator transformation on the two-terminal fault components.

[0017] Optionally, the adaptive threshold is determined by the sum of the products of the average value of the composite wavefront detection features within the pre-fault background window and the margin coefficient and standard deviation.

[0018] Optionally, the threshold comparison judgment includes a continuous threshold confirmation condition, that is, when multiple consecutive sampling points starting from a certain sampling point meet the threshold condition, the point is confirmed as a valid first-reach sampling point; if there is no sampling point that meets the continuous threshold confirmation condition in the preset search window, the sampling point corresponding to the maximum value of the composite wavefront detection feature in the window is used as the candidate first-reach sampling point.

[0019] Secondly, embodiments of the present invention also provide a line fault location system, comprising: The acquisition unit collects voltage and current data synchronously from both ends of the acquisition line. The first building unit is used to establish a multi-input multiple-output finite impulse response port propagation model between the two ends of the line using health operation data. The expression of the port propagation model is:

[0020] in, The order of the finite impulse response model; For the first The port propagation coefficient matrix corresponding to each discrete delay; To account for modeling errors and measurement noise; The input vector consists of voltage and current. The output vector is composed of voltage and current; The first extraction unit is used to select the main propagation channel from the model coefficients based on the impulse response energy of each channel, normalize the energy of the coefficients, and extract the effective propagation delay. The energy of the main propagation channel is defined as:

[0021] in, For the first The total energy of each candidate propagation channel This indicates the channel number. The square of the magnitude of each discrete delay coefficient The model order is the finite impulse response model. The second construction unit is used to construct an equivalent propagation speed based on the total length of the line and the effective propagation delay, wherein the equivalent propagation speed is defined as:

[0022] in, The equivalent propagation velocity used for fault location; The total length of the line; This refers to the effective propagation delay extracted from the main propagation channel; The freezing unit is used to freeze the equivalent propagation speed and capture the double-ended data within a predetermined time period before and after the fault when the line confirms a fault in the area. The third building unit is the employee, who constructs a two-end fault component based on the pre-fault steady-state data. The second extraction unit is used to extract differential features and energy features from the dual-end fault components respectively, and then normalize and weightedly fuse them to obtain composite wavefront detection features. The third extraction unit is used to set an adaptive threshold based on the background statistical value of the composite wavefront features before the fault, compare the composite wavefront features with the adaptive threshold, and extract the first-arrival sampling point at both ends. The correction unit is used to perform subsampling interpolation correction on the first arrival sampling point to obtain the corrected double-ended first arrival time. The calculation and output unit is used to calculate and output the fault distance based on the corrected difference between the first arrival times at both ends, the equivalent propagation speed, and the total length of the line. The expression for the fault distance is:

[0023] in, The corrected first arrival time is the time when the fault wavefront arrives at one end. To correct the first arrival time of the faulty wavefront at the other end, The actual time when the fault occurred. This is the equivalent propagation speed.

[0024] Thirdly, embodiments of the present invention also provide a computer-readable storage medium storing computer instructions that cause a computer to perform the line fault location method as described in the first aspect or any embodiment of the first aspect.

[0025] The embodiments of the present invention bring the following beneficial effects: The line fault location method provided in this invention utilizes measurable voltage and current data at both ends of the line to establish a port propagation model under healthy conditions, and extracts the effective propagation delay from the main propagation channel to construct an equivalent propagation speed consistent with the actual detected link. Compared with the traditional traveling wave location method that directly uses the ideal theoretical wave speed, this invention can equivalently incorporate factors such as line dispersion, end reflection, multipath propagation, measurement link delay, and signal preprocessing deviation into the speed parameter, thereby reducing the impact of propagation speed setting errors on the location results.

[0026] Other features and advantages of the invention will be set forth in the description which follows, and will be apparent in part from the description, or may be learned by practicing the invention. The objects and other advantages of the invention are realized and obtained in accordance with the structures particularly pointed out in the description, claims and drawings.

[0027] To make the above-mentioned objects, features and advantages of the present invention more apparent and understandable, preferred embodiments are described below in detail with reference to the accompanying drawings. Attached Figure Description

[0028] To more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the specific embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0029] Figure 1 A flowchart of the line fault location method provided in an embodiment of the present invention; Figure 2 This is a structural block diagram of the line fault location system provided in the embodiments of this application. Detailed Implementation

[0030] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0031] Existing methods for locating transmission line faults mainly include impedance methods, traveling wave methods, transient quantity location methods, and data-driven location methods. Impedance methods typically calculate the measured impedance based on the voltage and current after the fault to estimate the fault distance. They have advantages such as simplicity and mature engineering applications. However, when the transition resistance is large, the fault current is weak, or the fault characteristics of transmission lines from renewable energy plants are complex, the location accuracy is easily affected by power supply characteristics, fault resistance, and control strategies. Traveling wave location methods calculate the fault distance using the time difference between the arrival of the initial transient wavefront at both ends of the line. They have advantages such as fast response speed and suitability for transient ranging. However, their location accuracy is highly dependent on the accurate identification of the first arriving wavefront and the appropriate setting of the propagation speed.

[0032] In practical engineering, fault transient wavefronts do not always exhibit ideal spikes. Line distribution parameters, frequency correlation characteristics, end reflections, measurement noise, sampling intervals, and signal preprocessing can all alter the wavefront morphology and detection arrival time. Especially in scenarios involving cables, flexible DC lines, high-voltage transmission lines, and new power systems with broadband disturbances, directly applying ideal theoretical wave velocities or single wavefront criteria for fault location may lead to increased ranging errors and decreased stability of the location results. Meanwhile, while some data-driven location methods can learn fault waveform characteristics using a large number of samples, their performance typically depends on the coverage of the training samples, and their physical interpretability and robustness to unseen conditions remain insufficient.

[0033] Therefore, there is an urgent need for a line fault location method to reduce the impact of ideal wave velocity setting error, wavefront distortion, measurement noise, and sampling discretization on the location results.

[0034] To facilitate understanding of this embodiment, a line fault location method disclosed in this embodiment of the invention will first be described in detail.

[0035] Figure 1 This is a flowchart of a line fault location method provided in an embodiment of the present invention. Figure 1 As shown, the method may include: S102: Acquire voltage and current data simultaneously sampled at both ends of the line.

[0036] In this embodiment, synchronous sampling devices are arranged at both ends of the protected transmission line, designated as the starting and ending ends. For ease of explanation, the starting end is denoted as end M, and the ending end as end N. The voltage and current at end M, the voltage and current at end N are collected. The synchronous sampling device can be an existing protection and control device, a traveling wave acquisition device, a synchronous phasor measurement device, or other electrical quantity acquisition units that meet the synchronous sampling requirements.

[0037] To ensure the accuracy of subsequent fault ranging, the sampling data from both the M and N ends should have a unified time reference. Specifically, this can be achieved through satellite time synchronization, network time synchronization, or a station-synchronized clock, ensuring that the sampling data from both ends have comparable time stamps. If there is a fixed time delay in the acquisition channels, communication links, or filtering processes at both ends, it should be calibrated or recorded before ranging to facilitate correction in the initial arrival time difference calculation.

[0038] The collected two-terminal voltage and current data can be expressed as:

[0039] in, and They represent the first Voltage and current at terminal M at each sampling time; and They represent the first The voltage and current at terminal N at each sampling time.

[0040] When the protection device or fault initiation module detects a fault disturbance in the line, it extracts the voltage and current data at both ends within a certain time window before and after the fault. This data serves as the basis for subsequent fault component construction, wavefront feature extraction, and first arrival time calculation. The time window should cover the steady-state background segment before the fault and the initial transient segment after the fault, so as to obtain background reference quantities and fault wavefront information simultaneously.

[0041] Step S102 serves to provide synchronous, complete, and comparable two-end measurement data for fault location. Subsequent steps will construct fault components based on this data, extract the arrival times of the fault wavefronts at the M and N ends, and calculate the fault distance by combining the effective propagation velocity determined by the main propagation channel of the multiple-input multiple-output finite impulse response (MIMO-FIR).

[0042] S104: Establish a multi-input multi-output finite impulse response port propagation model between the two ends of the line using health operation data.

[0043] After obtaining the synchronous voltage and current data at both ends of the line, a MIMO-FIR port propagation model between the two ends of the line is established using healthy operation data under fault-free conditions. This model describes the equivalent propagation relationship of voltage and current transients from one end to the other under healthy conditions, providing a foundation for subsequent extraction of the main propagation channel, effective propagation delay, and equivalent propagation speed.

[0044] The FIR coefficients in the model are not directly equivalent to physical parameters such as resistance, inductance, capacitance, and conductance per unit length of the line. Instead, they are finite-dimensional equivalent expressions of the observable propagation relationship at both ends of the line, which can comprehensively reflect factors such as propagation delay, frequency-related attenuation, end reflection, multipath propagation, and voltage-current coupling.

[0045] Specifically, the input vector is composed of the voltage and current at terminal M, and the output vector is composed of the voltage and current at terminal N:

[0046] Establish a MIMO-FIR port propagation model from M end to N end:

[0047] In the formula, The order of the FIR model; For the first Each discrete delay corresponds to Port propagation coefficient matrix; To model errors and measurement noise, the propagation coefficient matrix can be written as:

[0048] in, This represents the propagation path from the voltage at terminal M to the voltage at terminal N. This represents the propagation path from the current at terminal M to the voltage at terminal N. This represents the propagation path from the voltage at terminal M to the current at terminal N. This represents the propagation path of the current from terminal M to terminal N.

[0049] Similarly, a reverse port propagation model from N to M can also be established:

[0050] in, This represents the MIMO-FIR propagation coefficient matrix from end N to end M. For cases where the line parameters and the measurement links at both ends are approximately symmetrical, a unidirectional main propagation model can be preferentially used to extract the equivalent propagation velocity; for cases where there are significant differences in the measurement links or propagation characteristics at both ends, different methods can be used... and Extract the equivalent propagation velocity in both directions.

[0051] The healthy MIMO-FIR port propagation model obtained in step S104 is mainly used for the selection of the main propagation channel and the extraction of effective propagation delay in subsequent steps.

[0052] S106: From the model coefficients, select the main propagation channel based on the impulse response energy of each channel, normalize the coefficients by energy, and extract the effective propagation delay.

[0053] After establishing a MIMO-FIR port propagation model under healthy conditions, the main propagation path and its effective propagation delay related to fault location are further extracted from the model coefficients. The purpose of this step is to obtain time parameters that can represent the main propagation path of fault transient waves from the line health propagation model, providing a basis for subsequently constructing the equivalent propagation speed.

[0054] As can be seen from step S104, the coefficient matrix in the MIMO-FIR port propagation model is... It includes multiple propagation channels, including the propagation channel from the voltage at terminal M to the voltage at terminal N, the propagation channel from the current at terminal M to the voltage at terminal N, the propagation channel from the voltage at terminal M to the current at terminal N, and the propagation channel from the current at terminal M to the current at terminal N. Different channels reflect different propagation relationships of voltage and current transients between the two ends of the line. For fault location, the main propagation channel that can stably reflect the propagation of the fault transient wave from one end to the other should be selected first.

[0055] As a specific implementation method, the main propagation channel can be selected based on the impulse response energy of each propagation channel. Let the FIR coefficient sequence of a certain propagation channel be... ,in If a candidate propagation channel is represented, then the propagation energy of that channel can be defined as:

[0056] In the formula, For the first The total energy of each candidate propagation channel This indicates the channel number. The square of the magnitude of each discrete delay coefficient This represents the order of the FIR model. Generally, the higher the propagation energy, the more significant the contribution of that channel to the port response. Therefore, the propagation channel with the highest energy can be selected as the main propagation channel.

[0057] In the formula, This indicates the selected main propagation channel. In addition to adopting the principle of maximizing energy, voltage-voltage channels, current-current channels, or other channels can be pre-specified as the main propagation channel based on the actual protection device configuration, fault type, signal quality, or engineering experience.

[0058] After determining the main propagation channel, the FIR coefficients of this channel are subjected to energy normalization:

[0059] In the formula, Indicates the main propagation channel at the 1st The normalized energy percentage at each discrete delay. This quantity can be understood as the distribution of the propagation energy of the main propagation channel at different delay positions.

[0060] Based on the normalized energy distribution, the effective propagation delay of the main propagation channel can be extracted. As a preferred method, the energy centroid delay can be used:

[0061] In the formula, The energy centroid delay of the main propagation channel The sampling period is denoted as . This delay reflects the average arrival position of the main propagation channel energy on the time axis, and can, to a certain extent, comprehensively consider the effects of multipath propagation, reflection, and frequency-dependent attenuation.

[0062] As another implementation method, a delay can be used when the accumulated energy reaches a set proportion. For example, define... The discrete delay point at which the cumulative propagation energy first reaches 50%:

[0063] The corresponding E50 latency is:

[0064] In the formula, This represents the effective delay when the accumulated energy of the main propagation channel reaches 50%. Compared to single-peak delay, the E50 delay is less sensitive to local noise and single-point glitches, making it more suitable for propagation delay characterization under broadband disturbances and waveform distortion conditions.

[0065] In practical applications, the energy centroid delay can be considered based on fault location accuracy requirements, sampling rate, line length, and signal quality. E50 latency Choose one of the following as the effective propagation delay: peak delay or weighted average group delay within a specified frequency band, denoted as: The effective propagation delay used to construct the equivalent propagation speed subsequently. It should be noted that... This is not the theoretical propagation delay in an ideal lossless line, but rather an equivalent delay determined by the healthy MIMO-FIR port propagation model, the selected main propagation channel, the sampling period, and the actual detection link. This delay can reflect the effects of line dispersion, end reflections, multipath propagation, and the measurement link in an equivalent form in the subsequent ranging model.

[0066] By step S106, the main propagation channel can be obtained from the equivalent model of a healthy MIMO-FIR circuit. and its effective propagation delay .

[0067] S108: Construct the equivalent propagation speed based on the total length of the line and the effective propagation delay.

[0068] The main propagation channel was obtained in the previous step. and its effective propagation delay Next, an equivalent propagation velocity for fault location is constructed. The purpose of this step is to transform the time delay information extracted from the healthy MIMO-FIR port propagation model into the velocity parameter in the fault location formula, thereby avoiding the error caused by directly using the ideal theoretical wave velocity in traditional traveling wave ranging.

[0069] Let the total length of the protected line be The effective propagation delay corresponding to the main propagation channel is Then the equivalent propagation speed is defined as:

[0070] In the formula, The equivalent propagation velocity used for fault location; The total length of the protected line; This is the effective propagation delay extracted from the main propagation channel in the previous step.

[0071] It should be noted that, It is not simply equivalent to the ideal physical wave speed in the sense of the telegraph equation, nor is it a fixed constant determined solely by the insulation medium of the line and the electromagnetic propagation speed. It is the engineering equivalent speed obtained based on the healthy MIMO-FIR port propagation model. It reflects the comprehensive speed at which fault transient waves or broadband disturbance signals propagate from one end of the line to the other on the selected main propagation channel and are effectively identified by the measurement and detection link.

[0072] Unlike traditional traveling wave positioning methods that directly use theoretical wave velocities, the method constructed in this invention... This method can effectively incorporate factors such as line frequency-dependent propagation, dispersion, end reflection, multipath tail, measurement bandwidth limitations, sampling discretization, signal preprocessing, and first-reach criterion offset into the velocity parameter. Therefore, this velocity has the same physical caliber as subsequent first-reach wavefront detection methods, making it more suitable for fault location under broadband disturbances and actual measurement conditions.

[0073] When only a one-way health transmission model is used, a uniform equivalent transmission speed can be obtained from the main transmission channel from end M to end N. When establishing bidirectional health transmission models from M to N and from N to M simultaneously, the equivalent transmission velocities in both directions can be calculated separately:

[0074] In the formula, This represents the effective propagation delay extracted from the main propagation channel from end M to end N; This represents the effective propagation delay extracted from the main propagation channel from end N to end M; and These represent the equivalent propagation speeds in the two directions, respectively.

[0075] If the line structure, measurement link, and processing methods at both ends are approximately symmetrical, the equivalent propagation velocities in the two directions can be combined into a unified velocity, for example, by taking the average value:

[0076] If there are significant differences in the measurement link, filtering process, or port propagation characteristics at both ends of the line, equivalent propagation velocities in different directions can be used in subsequent ranging formulas to improve the positioning adaptability under asymmetric conditions.

[0077] Furthermore, in engineering applications, historical disturbance data, known location test fault data, or simulation calibration data can be used to... Perform calibration. If the calibration results indicate that there is a fixed time offset in the actual detection link, a time correction can be introduced into the subsequent two-end first-arrival time difference positioning formula to further reduce the ranging error.

[0078] Through step S108, an equivalent propagation speed consistent with that of the main propagation channel and the fault wavefront detection link can be obtained. This speed will serve as a key parameter in the subsequent dual-end first arrival time difference positioning formula, used to convert the arrival time difference of the fault wavefronts at the M and N ends into the fault distance.

[0079] S110: When a fault is confirmed to occur within the line area, the equivalent propagation speed is frozen and the data from both ends within a predetermined time period before and after the fault is captured.

[0080] To achieve equivalent propagation speed Subsequently, the protection device enters real-time monitoring mode. The protection device can be a secondary device installed in substations at both ends of the transmission line to monitor the power system's operating status in real time and automatically execute trip commands or issue alarm signals when a fault is detected. When a disturbance occurs on the protected line, the existing protection device, fault initiation module, or independent zone fault detection module first determines whether the disturbance belongs to a fault within the protected line's zone. The zone fault detection module can employ existing current differential protection, distance protection, or transient quantity protection methods, or it can employ a structural mismatch detection method based on the MIMO-FIR health propagation model.

[0081] It should be noted that the focus of this invention is not on repeatedly constructing fault criteria within and outside the fault zone, but rather on further calculating the fault distance using the equivalent propagation velocity determined by the MIMO-FIR main propagation channel and the first arrival times at both ends after an internal fault has been confirmed. Therefore, the internal fault confirmation result is only used as a condition for initiating the fault ranging process in this step.

[0082] Specifically, the fault detection signal within the area is: ,when When this occurs, it indicates that the detection module has confirmed a fault within the line's affected area; when... When the condition is met for the first time, it indicates that the fault within the area has not been confirmed. The sampling point that first meets the conditions for a fault within the area is denoted as:

[0083] In the formula, The starting sampling point for fault location is:

[0084] in, The sampling period.

[0085] when And after the ranging process is initiated, the protection device performs the following operations: 1) Record the fault location starting sampling point and startup time ; 2) The equivalent propagation speed obtained in the freezing step S108 To prevent data from continuing to affect speed parameters during the fault transient process; 3) Extract voltage and current data of terminals M and N from the cache within a certain time window before and after the fault; 4) Input the captured data into the subsequent fault component construction, composite wavefront feature extraction and first arrival time calculation stages.

[0086] The fault location data window can be represented as:

[0087] In the formula, The data window used for fault location; The number of sampling points retained before the fault starts, used to extract the steady-state background before the fault; This is the number of sampling points retained after the fault starts, used to cover the process of the initial transient wavefront of the fault reaching both ends.

[0088] Within this time window, extract the voltage and current sequences at terminals M and N:

[0089] These data will serve as input for subsequent fault component construction and first wave head detection.

[0090] If no fault is detected within the zone during real-time operation, i.e. If the fault location module does not start, the protection device will continue to monitor. If the detection result is an external fault or external disturbance, the fault location module will remain locked and will not output the fault distance result to avoid invalid distance measurement for faults outside the local line.

[0091] This step clearly distinguishes the fault location process from the fault detection process: the fault detection module is responsible for confirming whether a fault has occurred within the area, while the fault location module, after confirming a fault within the area, calculates the fault distance using frozen equivalent propagation velocity and two-end transient data. This avoids duplication of content between the distance measurement patent and the fault detection patent, and ensures that the distance measurement method has clear engineering start-up conditions.

[0092] S112: Construct a two-ended fault component based on the steady-state data before the fault.

[0093] In step S110, the fault location data window is determined. Then, fault components are constructed for the voltage and current signals at terminals M and N, respectively. The purpose of this step is to reduce the influence of the power frequency steady-state component, load current, and normal operating background on fault wavefront identification, so that the transient change generated at the initial moment of the fault becomes the main object of subsequent analysis.

[0094] Specifically, first at the moment of fault initiation Previously, a steady-state reference window was selected:

[0095] In the formula, This serves as the steady-state reference window before the fault. This represents the number of sampling points used to estimate background quantities before the fault is initiated.

[0096] Based on this steady-state reference window, calculate the background reference values ​​for the voltage and current at terminals M and N respectively: In the formula, , , and These represent the steady-state background reference values ​​for the voltage and current at terminal M, the voltage and current at terminal N, and the current at terminal N before the fault, respectively.

[0097] Then, the real-time sampled values ​​within the fault location data window are subtracted from the corresponding background reference values ​​to obtain the dual-end fault components:

[0098] in, , and These represent the voltage fault component and the current fault component at terminal M, respectively. and These represent the voltage fault component and the current fault component at the N-terminal, respectively.

[0099] As another implementation method, the fault component can also be constructed using a periodic differential method to further weaken the power frequency periodic component:

[0100] In the formula, It can represent the voltage or current signal at either end. This represents the number of sampling points corresponding to one power frequency cycle. This method is suitable for scenarios with strong power frequency components and high sampling frequencies, such as voltage or current measurement under steady-state operating conditions of power systems, transient signal analysis of transmission line faults, and harmonic detection of output signals from power electronic converters.

[0101] After obtaining the above fault components, the main fault component for wavefront detection can be selected based on the fault type, signal quality, and ranging requirements. For example, the voltage fault component can be selected as the main wavefront detection quantity, or the current fault component can be selected, or a weighted combination of the voltage fault component and the current fault component can be used.

[0102] In the formula, and These are the combined fault components at the M and N ends, respectively, used for subsequent wavehead detection. and These are the weighting coefficients for the voltage fault component and the current fault component, respectively. If only the voltage fault component is used, we can take... If only the current fault component is used, then... .

[0103] This step converts the original two-terminal voltage and current signals into fault component signals that highlight transient changes in fault conditions. This fault component can reduce the impact of steady-state background at power frequency, load changes, and slow-changing operating disturbances on the first wavefront identification, providing input for the construction of first-order differential features, Teager energy features, and composite wavefront detection features in the next step.

[0104] S114: Extract differential features and energy features from the dual-end fault components respectively, and obtain composite wavefront detection features by normalization and weighted fusion.

[0105] In step S112, the combined fault components of terminals M and N are obtained. and Subsequently, wavefront features are extracted from the fault components at both ends. The purpose of this step is to enhance the detectability of the initial transient wavefront of the fault, so that the subsequent adaptive threshold determination can more accurately obtain the first arrival time of the fault wavefront at both ends.

[0106] First, the combined fault components at the M and N terminals are processed using first-order differential processing:

[0107] In the formula, and These are the first-order differential characteristics of the fault components at the M and N ends, respectively. The first-order difference reflects the rate of change of the signal between adjacent sampling points. When the transient wavefront of the fault reaches a certain end, the fault component at that end usually undergoes a sudden change within a short period of time, thus the first-order differential characteristic will show a significant increase.

[0108] Then, the Teager energy characteristics are constructed for the combined fault components at the M and N ends:

[0109] In the formula, and The Teager energy characteristics are shown for the M and N terminals, respectively. Teager energy can be used to characterize local transient energy changes in a signal. When a fault wavefront arrives, the local energy of the signal undergoes concentrated changes; therefore, the Teager energy characteristic can enhance the transient wavefront response in weak wavefronts, high transition resistance faults, or noisy environments.

[0110] To avoid the fusion result being biased towards a single feature due to differences in the dimensions and amplitude ranges of different features, the first-order difference features and the Teager energy features can be normalized first. For example, for the M-end, it can be defined as follows:

[0111] For the N-terminal, it can be defined as follows:

[0112] In the formula, , Normalized difference features; , Normalized Teager energy characteristics; Small positive numbers are introduced to prevent the denominator from being zero.

[0113] Furthermore, the normalized first-order difference features and the Teager energy features are weighted and fused to obtain the composite wavefront detection features at the M and N ends:

[0114] In the formula, and These are the composite wavefront characteristics of the M and N ends, respectively; and These are the weight coefficients for the difference feature and the Teager energy feature, respectively, and they satisfy the following:

[0115] In practical applications, if the edge of the fault wavefront changes significantly, the voltage can be appropriately increased. Typically, the parameters are increased by 10% to 30% from the original values. If the fault wavefront is weak, the noise is strong, or the amplitude change is not obvious due to high transition resistance, the values ​​can be increased appropriately. Typically, the parameters are increased by 10% to 30% from the original parameters to enhance the contribution of local energy changes to the extraction of the first arrival time.

[0116] This step converts the original fault components at the M and N ends into composite wavefront detection features. and Compared with directly using the original voltage and current amplitudes or a single differential feature, the composite wavefront feature can simultaneously reflect the rapid edge changes and local energy concentration phenomena of the fault wavefront, thereby improving the identifiability of the fault first arrival wavefront under broadband disturbances, wavefront distortion, high transition resistance, and measurement noise conditions.

[0117] S116: Set an adaptive threshold based on the background statistics of the composite wavefront features before the fault, compare the composite wavefront features with the adaptive threshold, and extract the first arrival sampling point at both ends.

[0118] In step S114, the composite wavefront detection features of the M and N ends are obtained. and Subsequently, adaptive thresholding is applied to the feature sequences at both ends to extract the first arrival times of the fault transient wavefront at both ends. The purpose of this step is to obtain reliable arrival times from the transient waveforms at both ends, providing time parameters for subsequent fault ranging based on the first arrival time difference between the two ends.

[0119] First, at the moment of fault start-up Previously selected background window before the fault The mean and standard deviation of the composite wavefront characteristics at the M and N ends were statistically analyzed under a fault-free background:

[0120] In the formula, , These are the mean and standard deviation of the M-end composite wavefront characteristics within the background window before the fault, respectively. , These represent the mean and standard deviation of the N-terminal composite wavefront characteristics within the background window before the fault, respectively.

[0121] Then, adaptive thresholds for the M and N ends are set according to the background characteristics before the fault:

[0122] In the formula, and These are the adaptive wavefront detection thresholds for the M and N ends, respectively. and This is the threshold margin coefficient, used to adjust the sensitivity and noise immunity of wavefront detection. A larger threshold margin coefficient results in stronger noise immunity, but may reduce sensitivity to weak wavefronts; a smaller threshold margin coefficient results in higher detection sensitivity, but requires avoiding false triggering due to noise.

[0123] Furthermore, define the threshold discrimination functions at both ends:

[0124] In the formula, Indicates that the M-end is at the 1st Each sampling point detected a composite wavefront feature exceeding the threshold. Indicates that the N-terminus is at the 1st... The composite wavefront feature detected at each sampling point exceeded the threshold.

[0125] To avoid false triggering caused by single-point noise, sampling spikes, or short-term peaks, this invention further sets up continuous threshold confirmation conditions. If starting from a certain sampling point, in continuous... If the threshold crossing condition is met at all sampling points, then a stable fault initial wavefront is considered to have been detected at that end. The first sampling point at end M can be represented as:

[0126] The first sampling point at the N-end can be represented as:

[0127] In the formula, and These are the sampling point numbers corresponding to the first stable threshold crossing at the M and N ends, respectively. This represents the number of consecutive threshold-crossing confirmation points.

[0128] After obtaining the initial sampling points at both ends, the corresponding initial arrival time can be obtained:

[0129] In the formula, and These represent the first arrival times of the fault transient wavefront at terminals M and N, respectively. The sampling period.

[0130] In practical engineering, to limit the search range and prevent subsequent reflected waves or noise peaks from being mistaken for the first arrival wavefront, a fault initiation time can be used. Then set up the first wave head search window:

[0131] In the formula, For the first wave head search window, This is the length of the search window. (The above...) and You should confirm within this search window.

[0132] If no sampling point that meets the continuous threshold crossing condition appears within the search window, the sampling point corresponding to the maximum value of the composite wavefront characteristic within the window can be used as the alternative first arrival point to ensure that ranging results can still be given under conditions of high transition resistance or weak fault characteristics. This step allows us to obtain the first arrival time of the M-end from the composite wavefront detection features at both ends. First arrival time on N terminals Compared to fixed threshold or single peak search methods, adaptive thresholding can automatically adjust the detection threshold based on the background noise level before the fault, and continuous threshold-crossing confirmation can suppress false triggering by short-term noise, thereby improving the reliability of first-arrival time extraction under broadband disturbances, wavefront distortion, and weak fault characteristics. The next step will be to perform subsampling correction on the first-arrival time to further reduce sampling discretization error.

[0133] S118: Perform subsampling interpolation correction on the first arrival sampling point to obtain the corrected double-ended first arrival time.

[0134] In step S116, the first arrival times of the M and N terminals are determined by the first stable threshold crossing sampling points, thus obtaining the sampling point-level first arrival times. and However, in actual sampling, the moment when the fault wavefront actually arrives and crosses the detection threshold usually does not fall exactly on a single sampling point, but may be located between two adjacent sampling points. If the sampling point time is directly used as the first arrival time, it will introduce a problem due to the sampling period. The resulting time quantization error affects the accuracy of subsequent calculations of first arrival time difference and fault distance between the two ends.

[0135] Therefore, this step obtains the first sampling point in step S116. and Based on this, a subsampling correction method is further employed to refine the first arrival times at both ends. The purpose of this step is to reduce sampling discretization errors and improve the accuracy and stability of fault location results.

[0136] Taking the M-end as an example, let's assume... The first valid threshold-crossing sampling point at the M end determined in step S116, and the composite wavefront characteristics satisfy:

[0137] Then it can be assumed that the true threshold crossing time is located at the sampling point. and Between. The M-end subsampling correction coefficients can be obtained using linear interpolation:

[0138] In the formula, The threshold crossing point at point M represents the relative position between two adjacent sampling points, and its value is typically located in... ; The threshold is an adaptive threshold for the M-end; Small positive numbers are introduced to prevent the denominator from being zero.

[0139] Therefore, the first arrival time after M-terminal correction can be expressed as:

[0140] Similarly, for the N-end, if This is the first valid threshold-crossing sampling point, and it satisfies: The N-terminal subsampling correction factor is:

[0141] In the formula, The threshold crossing point at the N-end is the relative position between two adjacent sampling points, and its value is usually located in... ; An adaptive threshold for the N-end; Small positive numbers are introduced to prevent the denominator from being zero.

[0142] The first arrival time after N-end correction is:

[0143] In the formula, and These represent the first arrival times of the M and N terminals after subsampling correction, respectively. (Compared to directly using...) , compared to, and It can describe the true threshold crossing moment of the fault wavefront between adjacent sampling points more precisely.

[0144] As another implementation, when a stable threshold-crossing point is not obtained in step S16, and a characteristic peak point within the search window is used as a candidate first-reach point, subsampling correction can be performed using parabolic interpolation near the peak. (Using either end...) For example, among which Let the peak sampling point be The subsampling offset near the peak can be expressed as:

[0145] The corresponding corrected first arrival time is:

[0146] In the formula, The peak point is relative to the sampling point The subsampling offset. This method is suitable for cases where weak fault characteristics or threshold exceedances are not obvious, but the composite wavefront features have a clear main peak within the search window.

[0147] In practical applications, if the first threshold crossing point can be reliably obtained, linear interpolation correction based on threshold crossing is preferred; if a stable threshold crossing point cannot be obtained, parabolic interpolation correction based on local peak values ​​can be used. Both methods belong to subsampling refinement of the first arrival time, and their common purpose is to reduce the time quantization error caused by the finite sampling interval.

[0148] This step yields the corrected first arrival times for both ends. and .

[0149] S120: Calculate and output the fault distance based on the corrected difference in the first arrival times of both ends, the equivalent propagation speed, and the total length of the line.

[0150] In step S118, the first arrival time of the M terminal after subsampling correction is obtained. First arrival time on N terminals Then, combined with the equivalent propagation speed obtained in step S108 The purpose of this step is to calculate the location of the fault point on the line. This step aims to use the time difference between the arrival time of the fault transient wavefront at both ends of the line to eliminate the influence of the unknown fault occurrence time, thereby obtaining the distance from the fault point to the end of the line.

[0151] Let the total length of the protected line be The distance from the fault point to end M is The distance from the fault point to terminal N is The time of the fault is Under equivalent uniform propagation conditions, the fault wavefront propagates from the fault point to both ends M and N. The time when it reaches both ends and is identified by the detection link can be expressed as:

[0152] In the formula, The corrected first arrival time of the fault wavefront at the M end. The corrected first arrival time of the fault wavefront at the N-terminal. The actual time when the fault occurred. The equivalent propagation speed is consistent with the main propagation channel and wavefront detection link.

[0153] Due to the timing of the fault Since both ends are unknown, it is difficult to directly determine the fault location using only the arrival time of one end. Subtracting the two equations above eliminates the fault. The time difference between the first arrivals at both ends is obtained:

[0154] Therefore, the distance from the fault point to end M can be obtained:

[0155] Accordingly, the distance from the fault point to terminal N is:

[0156] From the above formula, it can be seen that when When the fault wavefront arrives at end M first, it indicates that the fault point is closer to end M; when When the fault waveform arrives at the N end first, it indicates that the fault point is closer to the N end; when At that time, the fault point was located near the midpoint of the line.

[0157] It should be noted that the method used in this step is... The equivalent propagation velocity constructed for step S108 is not the ideal theoretical wave velocity directly set in traditional traveling wave positioning. This velocity has already equivalently taken into account the main propagation channel, broadband propagation characteristics, sampling discretization, wavefront detection method, and the influence of the measurement link. Therefore, the fault distance calculated using it is more consistent with the actual detection process.

[0158] After calculating the fault distance Then, a reasonableness assessment can be conducted. If the following conditions are met:

[0159] If the ranging result is within the protected line area, it can be considered as a valid fault location output; if or If the error occurs, it indicates that there may be an anomaly in the extraction of the first arrival time, the synchronization time reference, or the equivalent propagation speed. A prompt indicating an abnormal ranging or the need for verification should be output.

[0160] Through this step, the present invention converts the first arrival time difference of the wavefronts of a two-terminal fault into the actual location of the fault point on the line, realizing two-terminal fault ranging based on the equivalent propagation velocity of MIMO-FIR. This calculation process does not require explicitly determining the fault occurrence time. It is suitable for fault location of transmission lines under dual-end synchronous measurement conditions.

[0161] In practical engineering, the system first synchronously collects voltage and current data at the M and N ends of the protected line, and ensures that the data at both ends have a unified time reference. Then, it uses the healthy operation data to establish a MIMO-FIR port propagation model, selects the main propagation channel and extracts the effective propagation delay, and then constructs an equivalent propagation speed consistent with the main propagation channel and the detection link.

[0162] Furthermore, once a protection device or fault detection module confirms a fault within the line's fault zone, this invention initiates the ranging process, extracting voltage and current data from both ends before and after the fault, and constructing fault components to weaken the influence of the power frequency steady-state background and load changes. Based on this, first-order differential features and Teager energy features are fused to form composite wavefront detection features, and the arrival times of the fault wavefronts at the M and N ends are extracted through adaptive thresholding and continuous threshold crossing judgment. To reduce the time quantization error caused by sampling discretization, this invention further performs subsampling correction on the arrival time to obtain a more refined double-ended corrected arrival time.

[0163] Through the above process, this invention transforms the fault location process from the traditional traveling wave location method of "ideal wave velocity + single wavefront criterion" to a location method of "effective propagation velocity + composite wavefront characteristics + first arrival time difference at both ends". The equivalent propagation velocity is determined by the healthy MIMO-FIR main propagation channel, which can comprehensively reflect the effects of broadband propagation, dispersion, end reflection, measurement link, and detection algorithm. The composite wavefront characteristics can improve the stability of first arrival time extraction under high transition resistance, weak fault characteristics, wavefront distortion, and noise backgrounds.

[0164] Therefore, the focus of this invention is not on repeatedly constructing fault detection criteria within and outside the fault zone, but rather on calculating the fault distance after confirming the fault within the zone, using the equivalent propagation velocity and the first arrival time at both ends provided by the MIMO-FIR line equivalent model. This method can reduce the impact of ideal wave velocity setting errors, sampling discretization errors, wavefront distortion, and measurement noise on the ranging results, and improve the accuracy, stability, and engineering interpretability of transmission line fault ranging under complex broadband disturbance conditions.

[0165] As an optional embodiment, the coefficient matrix of the multiple-input multiple-output finite impulse response port propagation model contains four propagation channels: the starting-end voltage to the ending-end voltage channel, the starting-end current to the ending-end voltage channel, the starting-end voltage to the ending-end current channel, and the starting-end current to the ending-end current channel.

[0166] As an optional embodiment, the main propagation channel is the propagation channel with the largest impulse response energy; the effective propagation delay is the delay time corresponding to the first time when the cumulative propagation energy reaches half of the total energy.

[0167] As an optional implementation, an equivalent propagation speed is constructed based on the total length of the line and the effective propagation delay, including: Establish port propagation models for both the forward and reverse directions; Calculate the equivalent propagation velocity in both directions; When the two ends of the line are symmetrical, the average speed in both directions is taken as the uniform speed; When the two ends of the line are asymmetrical, distance measurement is calculated using speeds in different directions.

[0168] As an optional embodiment, the fault components are constructed in the following ways: Using the pre-fault steady-state data as a benchmark, the fault component is obtained by subtracting the real-time sampled value in the fault ranging data window from the corresponding steady-state background reference value.

[0169] As an optional embodiment, the differential features are obtained by performing a first-order differential operation on the two-terminal fault components; the energy features are obtained by performing a Teager energy operator transformation on the two-terminal fault components.

[0170] As an optional embodiment, the adaptive threshold is determined by the sum of the product of the average value of the composite wavefront detection features within the pre-fault background window and the margin coefficient and standard deviation.

[0171] As an optional embodiment, the threshold comparison judgment includes a continuous threshold confirmation condition, that is, when multiple consecutive sampling points starting from a certain sampling point meet the threshold condition, the point is confirmed as a valid first-reach sampling point; if there is no sampling point that meets the continuous threshold confirmation condition in the preset search window, the sampling point corresponding to the maximum value of the composite wavefront detection feature in the window is used as the candidate first-reach sampling point.

[0172] Figure 2 This is a structural block diagram of the line fault location system provided in the embodiments of this application, such as... Figure 2 As shown, the system includes: Acquisition unit 201, the employee and the acquisition line synchronously sample voltage and current data; The first building unit 203 is used to establish a multi-input multiple-output finite impulse response port propagation model between the two ends of the line using health operation data. The expression of the port propagation model is:

[0173] in, The order of the finite impulse response model; For the first The port propagation coefficient matrix corresponding to each discrete delay; To account for modeling errors and measurement noise; The input vector consists of voltage and current. The output vector is composed of voltage and current; The first extraction unit 205 is used to select the main propagation channel from the model coefficients based on the impulse response energy of each channel, normalize the energy of the coefficients, and extract the effective propagation delay. The energy of the main propagation channel is defined as:

[0174] in, For the first The total energy of each candidate propagation channel This indicates the channel number. The square of the magnitude of each discrete delay coefficient The model order is the finite impulse response model. The second building unit 207 is used to construct the equivalent propagation speed based on the total length of the line and the effective propagation delay. The equivalent propagation speed is defined as:

[0175] in, The equivalent propagation velocity used for fault location; The total length of the line; This refers to the effective propagation delay extracted from the main propagation channel; The freezing unit 209 is used to freeze the equivalent propagation speed and capture the double-ended data within a predetermined time period before and after the fault is confirmed to have occurred in the line area. The third building unit 211, the employee constructs a two-end fault component based on the pre-fault steady-state data; The second extraction unit 213 is used to extract differential features and energy features from the dual-end fault components respectively, and then normalize and weightedly fuse them to obtain composite wavefront detection features. The third extraction unit 215 is used to set an adaptive threshold based on the background statistical value of the composite wavefront features before the fault, compare the composite wavefront features with the adaptive threshold, and extract the first-reach sampling point at both ends. Correction unit 217 is used to perform subsampling interpolation correction on the first arrival sampling point to obtain the corrected double-ended first arrival time; The calculation and output unit 219 is used to calculate and output the fault distance based on the corrected difference between the first arrival times at both ends, the equivalent propagation speed, and the total length of the line. The expression for the fault distance is:

[0176] in, The corrected first arrival time is the time when the fault wavefront arrives at one end. To correct the first arrival time of the faulty wavefront at the other end, The actual time when the fault occurred. This is the equivalent propagation speed.

[0177] The system provided in this application embodiment has the same implementation principle and technical effects as the aforementioned method embodiment. For the sake of brevity, any parts not mentioned in the system embodiment can be referred to the corresponding content in the aforementioned method embodiment.

[0178] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of this application. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions marked in the blocks may occur in a different order than those marked in the drawings. For example, two consecutive blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, can be implemented using a dedicated hardware-based system that performs the specified function or action, or using a combination of dedicated hardware and computer instructions.

[0179] It should be noted that similar labels and letters in the following figures indicate similar items. Therefore, once an item is defined in one figure, it does not need to be further defined and explained in subsequent figures.

[0180] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of this application. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions marked in the blocks may occur in a different order than those marked in the drawings. For example, two consecutive blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, can be implemented using a dedicated hardware-based system that performs the specified function or action, or using a combination of dedicated hardware and computer instructions.

[0181] This application provides a non-transitory computer-readable storage medium that stores computer instructions, which cause the computer to execute embodiments of this application. Figure 1 The method provided in the illustrated embodiment.

[0182] The aforementioned computer-readable storage medium may be any combination of one or more computer-readable media. A computer-readable medium may be a computer-readable signal medium or a computer-readable storage medium. A computer-readable storage medium may be, for example,—but not limited to—an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples of computer-readable storage media (a non-exhaustive list) include: an electrical connection having one or more wires, a portable computer disk, a hard disk, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM), or flash memory, optical fiber, portable compact disk read-only memory (CD-ROM), optical storage device, magnetic storage device, or any suitable combination thereof. In this document, a computer-readable storage medium may be any tangible medium that contains or stores a program that may be used by or in connection with an instruction execution system, apparatus, or device.

[0183] Computer-readable signal media may include data signals propagated in baseband or as part of a carrier wave, carrying computer-readable program code. Such propagated data signals may take various forms, including—but not limited to—electromagnetic signals, optical signals, or any suitable combination thereof. Computer-readable signal media may also be any computer-readable medium other than computer-readable storage media, capable of transmitting, propagating, or transmitting programs for use by or in connection with an instruction execution system, apparatus, or device.

[0184] The program code contained on a computer-readable medium may be transmitted using any suitable medium, including—but not limited to—wireless, wire, optical fiber, RF, etc., or any suitable combination thereof.

[0185] Computer program code for performing the operations of the embodiments of this application can be written in one or more programming languages ​​or a combination thereof, including object-oriented programming languages ​​such as Java, Smalltalk, and C++, and conventional procedural programming languages ​​such as the "C" language or similar programming languages. The program code can be executed entirely on the user's computer, partially on the user's computer, as a standalone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving remote computers, the remote computer can be connected to the user's computer via any type of network—including a Local Area Network (LAN) or a Wide Area Network (WAN), or it can be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0186] The foregoing has described specific embodiments of this application. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps described in the claims may be performed in a different order than that shown in the embodiments and may still achieve the desired result. Furthermore, the processes depicted in the drawings do not necessarily require the specific or sequential order shown to achieve the desired result. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0187] In the description of the embodiments of this application, the terms "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., refer to specific features, structures, materials, or characteristics described in connection with that embodiment or example, which are included in at least one embodiment or example of the embodiments of this application. In the embodiments of this application, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials, or characteristics described may be combined in a suitable manner in any one or more embodiments or examples. Furthermore, without contradiction, those skilled in the art can combine and integrate the different embodiments or examples described in the embodiments of this application, as well as the features of different embodiments or examples.

[0188] Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of indicated technical features. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one of that feature. In the description of embodiments of this application, "multiple" means at least two, such as two, three, etc., unless otherwise explicitly specified.

[0189] Any process or method description in the flowchart or otherwise herein can be understood as representing a module, segment, or portion of code comprising one or more executable instructions for implementing custom logic functions or processes, and the scope of preferred embodiments of this application includes additional implementations in which functions may be performed not in the order shown or discussed, including substantially simultaneously or in reverse order according to the functions involved, as should be understood by those skilled in the art to which embodiments of this application pertain.

[0190] Depending on the context, the word "if" as used here can be interpreted as "when," "when," "in response to determination," or "in response to detection." Similarly, depending on the context, the phrase "if determination" or "if detection (of the stated condition or event)" can be interpreted as "when determination," "in response to determination," "when detection (of the stated condition or event)," or "in response to detection (of the stated condition or event)."

[0191] It should be noted that the terminals involved in the embodiments of this application may include, but are not limited to, personal computers (PCs), personal digital assistants (PDAs), wireless handheld devices, tablet computers, mobile phones, MP3 players, MP4 players, etc.

[0192] In the embodiments provided in this application, it should be understood that the disclosed systems, apparatuses, and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the displayed or discussed mutual couplings, direct couplings, or communication connections may be through some interfaces; indirect couplings or communication connections between devices or units may be electrical, mechanical, or other forms.

[0193] Furthermore, the functional units in the various embodiments of this application can be integrated into a single processor, or each unit can exist physically separately, or two or more units can be integrated into a single unit. The integrated units described above can be implemented in hardware or in a combination of hardware and software functional units.

[0194] The integrated units implemented as software functional units described above can be stored in a computer-readable storage medium. These software functional units, stored in a storage medium, include several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) or processor to execute some steps of the methods described in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0195] The above description is only a preferred embodiment of the present application and is not intended to limit the present application. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present application should be included within the scope of protection of the present application.

Claims

1. A method for locating line faults, characterized in that, include: Acquire voltage and current data simultaneously sampled at both ends of the line; A multi-input multi-output finite impulse response (MIRR) port propagation model between the two ends of a line is established using health operation data. The expression for the port propagation model is as follows: in, The order of the finite impulse response model; For the first The port propagation coefficient matrix corresponding to each discrete delay; To account for modeling errors and measurement noise; The input vector consists of voltage and current. The output vector is composed of voltage and current; From the model coefficients, the main propagation channel is selected based on the impulse response energy of each channel. The coefficients are then normalized by energy, and the effective propagation delay is extracted. The energy of the main propagation channel is defined as follows: in, For the first The total energy of each candidate propagation channel This indicates the channel number. The square of the magnitude of each discrete delay coefficient The model order is the finite impulse response model. The equivalent propagation speed is constructed based on the total length of the line and the effective propagation delay. The equivalent propagation speed is defined as follows: in, The equivalent propagation velocity used for fault location; The total length of the line; This refers to the effective propagation delay extracted from the main propagation channel; Once the line confirms a fault within the affected area, the equivalent propagation speed is frozen and bi-end data within a predetermined time period before and after the fault is captured. Construct a two-ended fault component based on the pre-fault steady-state data; Differential features and energy features are extracted from the two-end fault components, and then normalized and weighted to obtain the composite wavefront detection features. An adaptive threshold is set based on the background statistics of the composite wavefront features before the fault. The composite wavefront features are compared with the adaptive threshold to extract the first-arrival sampling points at both ends. Subsampling interpolation correction is performed on the first arrival sampling point to obtain the corrected double-ended first arrival time; Based on the corrected difference in the first arrival times at both ends, the equivalent propagation speed, and the total line length, the fault distance is calculated and output. The expression for the fault distance is: in, The corrected first arrival time is the time when the fault wavefront arrives at one end. To correct the first arrival time of the faulty wavefront at the other end, The actual time when the fault occurred. This is the equivalent propagation speed.

2. The line fault location method according to claim 1, characterized in that: The coefficient matrix of the multi-input multi-output finite impulse response port propagation model contains four propagation channels: the starting voltage to the ending voltage channel, the starting current to the ending voltage channel, the starting voltage to the ending current channel, and the starting current to the ending current channel.

3. The line fault location method according to claim 1, characterized in that: The main propagation channel is the propagation channel with the largest impulse response energy; the effective propagation delay is the delay time corresponding to when the cumulative propagation energy first reaches half of the total energy.

4. The line fault location method according to claim 1, characterized in that: The step of constructing the equivalent propagation speed based on the total length of the line and the effective propagation delay includes: Establish port propagation models for both the forward and reverse directions; Calculate the equivalent propagation velocity in both directions; When the two ends of the line are symmetrical, the average speed in both directions is taken as the uniform speed; When the two ends of the line are asymmetrical, distance measurement is calculated using speeds in different directions.

5. The line fault location method according to claim 1, characterized in that: The fault components are constructed in the following ways: Using the pre-fault steady-state data as a benchmark, the fault component is obtained by subtracting the real-time sampled value in the fault ranging data window from the corresponding steady-state background reference value.

6. The line fault location method according to claim 1, characterized in that: The differential feature is obtained by performing a first-order difference operation on the two-terminal fault components; the energy feature is obtained by performing a Teager energy operator transformation on the two-terminal fault components.

7. The line fault location method according to claim 1, characterized in that: The adaptive threshold is determined by the sum of the product of the average value of the composite wavefront detection features within the background window before the fault and the margin coefficient and standard deviation.

8. The line fault location method according to claim 1, characterized in that: The threshold comparison judgment includes a continuous threshold confirmation condition, that is, when multiple consecutive sampling points starting from a certain sampling point meet the threshold condition, the point is confirmed as a valid first-reach sampling point; if there is no sampling point that meets the continuous threshold confirmation condition in the preset search window, the sampling point corresponding to the maximum value of the composite wavefront detection feature in the window is used as the candidate first-reach sampling point.

9. A line fault location system, characterized in that, include: The acquisition unit collects voltage and current data simultaneously from both ends of the acquisition line. The first building unit is used to establish a multi-input multiple-output finite impulse response port propagation model between the two ends of the line using health operation data. The expression of the port propagation model is: in, The order of the finite impulse response model; For the first The port propagation coefficient matrix corresponding to each discrete delay; To account for modeling errors and measurement noise; The input vector consists of voltage and current. The output vector is composed of voltage and current; The first extraction unit is used to select the main propagation channel from the model coefficients based on the impulse response energy of each channel, normalize the energy of the coefficients, and extract the effective propagation delay. The energy of the main propagation channel is defined as: in, For the first The total energy of each candidate propagation channel This indicates the channel number. The square of the magnitude of each discrete delay coefficient The model order is the finite impulse response model. The second construction unit is used to construct an equivalent propagation speed based on the total length of the line and the effective propagation delay, wherein the equivalent propagation speed is defined as: in, The equivalent propagation velocity used for fault location; The total length of the line; This refers to the effective propagation delay extracted from the main propagation channel; The freezing unit is used to freeze the equivalent propagation speed and capture the bi-end data within a predetermined time period before and after the fault when the line confirms a fault in the area. The third building unit is the employee, who constructs a two-end fault component based on the pre-fault steady-state data. The second extraction unit is used to extract differential features and energy features from the dual-end fault components respectively, and then normalize and weightedly fuse them to obtain composite wavefront detection features. The third extraction unit is used to set an adaptive threshold based on the background statistical value of the composite wavefront features before the fault, compare the composite wavefront features with the adaptive threshold, and extract the first-arrival sampling point at both ends. The correction unit is used to perform subsampling interpolation correction on the first arrival sampling point to obtain the corrected double-ended first arrival time. The calculation and output unit is used to calculate and output the fault distance based on the corrected difference between the first arrival times of the two ends, the equivalent propagation speed, and the total length of the line. The expression for the fault distance is: in, The corrected first arrival time is the time when the fault wavefront arrives at one end. To correct the first arrival time of the faulty wavefront at the other end, The actual time when the fault occurred. This is the equivalent propagation speed.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer instructions that cause the computer to perform the line fault location method as described in any one of claims 1 to 8.

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