Power distribution line fault location method and system based on traveling wave ranging

Abstract

This application relates to the field of power system technology and discloses a method and system for fault location in distribution lines based on traveling wave ranging. The method includes: injecting a zero-mode signal through a live pulse coupler; performing wave velocity layering analysis on the impedance nodes of the mixed line to obtain the propagation parameter matrix; generating an empty-mode echo using mode conversion at the fault asymmetry point; filtering for pure fault signals using a frequency domain fingerprinting algorithm; and obtaining three-dimensional fault coordinates based on inverse time-distance mapping processing. This application solves the problem of accurate fault location in mixed distribution lines under energized operation, improving fault location accuracy and power supply reliability.

Description

Technical Field

[0001] This application relates to the field of power system technology, and in particular to a method and system for locating faults in distribution lines based on traveling wave ranging. Background Technology

[0002] Existing fault location technologies for power distribution lines mainly include impedance methods, traveling wave methods, and intelligent algorithms. Among these, traveling wave-based fault location methods are widely used due to their high accuracy and fast response speed. Traditional traveling wave fault location technology detects the transient traveling wave signal generated when a fault occurs and calculates the fault distance using the propagation time and speed of the traveling wave in the line. This technology has mature applications in transmission lines. Existing active traveling wave injection technology can artificially generate traveling wave signals for fault location. By injecting specific pulse signals into the line and detecting the reflected waves, the fault location is determined. Compared to passively waiting for the fault to generate a traveling wave, this method is more proactive.

[0003] However, existing traveling wave fault location technologies have significant shortcomings when applied to mixed distribution lines. Mixed distribution lines consist of both overhead lines and cables, and the impedance differences between the different media cause complex reflections of traveling waves at the connection points. This results in the superposition of fault reflections and line structure reflections, making it difficult to accurately identify the effective reflections generated at the fault point. Existing active pulse injection schemes can only be implemented after the line is de-energized, severely impacting power supply continuity and failing to meet the uninterrupted power supply requirements of distribution systems. Furthermore, traditional methods lack effective multi-reflection source identification mechanisms, easily misinterpreting non-fault reflections as fault signals in complex mixed line environments, leading to decreased location accuracy.

[0004] Based on the limitations of existing technologies, fault location in hybrid power distribution lines faces deeper technical challenges: how to actively inject traveling wave signals and accurately identify fault reflected waves while the line is energized; how to establish a segmented propagation parameter model suitable for hybrid lines; and how to accurately extract fault characteristic signals from complex multi-source reflected waves. The root of these problems lies in the lack of a systematic solution for the unique propagation environment of hybrid power distribution lines, failing to simultaneously address the three key technical issues of energized injection, multi-source identification, and accurate ranging. Therefore, a complete fault location technology system for hybrid power distribution lines based on traveling wave ranging is needed. Summary of the Invention

[0005] This application provides a method and system for fault location of power distribution lines based on traveling wave ranging, which solves the problem of accurate fault location in the energized operation state of mixed power distribution lines, and improves fault location accuracy and power supply reliability.

[0006] In a first aspect, this application provides a method for fault location of distribution lines based on traveling wave ranging. The method includes: injecting zero-mode construction pulses into the distribution line using a live pulse coupler to obtain a live zero-mode traveling wave signal; performing wave velocity layering analysis on the mixed line impedance nodes based on the live zero-mode traveling wave signal to obtain a segmented zero-mode propagation parameter matrix; performing mode coupling conversion processing on the live zero-mode traveling wave signal through fault asymmetry points to obtain a fault-excited empty-mode echo; using a frequency domain waveform fingerprinting algorithm to perform reflection source screening processing on the fault-excited empty-mode echo to obtain a clean fault location empty-mode signal; and performing inverse time-distance mapping processing on the segmented zero-mode propagation parameter matrix based on the clean fault location empty-mode signal to obtain three-dimensional fault coordinates.

[0007] Optionally, the step of performing zero-mode pulse injection processing on the power distribution line using a charged pulse coupler to obtain a charged zero-mode traveling wave signal includes:

[0008] The GPS synchronization clock signal is input into a pulse generator for timing calibration to obtain a synchronization reference time scale.

[0009] Based on the aforementioned synchronization reference time, the amplitude of the 500kHz square wave pulse is modulated to obtain a 5kV standard injection pulse.

[0010] The 5kV standard injection pulse is processed by in-phase injection through a three-way coupling capacitor circuit to obtain a three-phase synchronous pulse signal.

[0011] The three-phase synchronous pulse signal is subjected to symmetrical component transformation to obtain the charged zero-mode traveling wave signal;

[0012] The zero-mode traveling wave signal is processed to initiate its propagation based on the zero-mode impedance matching principle, thus obtaining a zero-mode propagation start time marker.

[0013] Optionally, the step of performing wave velocity layered analytical processing on the hybrid line impedance nodes based on the charged zero-mode traveling wave signal to obtain a segmented zero-mode propagation parameter matrix includes:

[0014] Based on the line topology information, impedance abrupt change points are identified at the connection points of overhead lines and cables to obtain the coordinates of impedance nodes.

[0015] Based on the charged zero-mode traveling wave signal, wave impedance calculations are performed on different dielectric sections to obtain the zero-mode wave impedance values ​​of overhead line sections and cable sections.

[0016] Based on the zero-mode wave impedance values ​​of the overhead line segment and the cable segment, the reflection coefficients of the impedance node positions are calculated to obtain the forward reflection coefficient and the reverse reflection coefficient.

[0017] Based on the electromagnetic properties of the medium, the propagation speed of each line segment is calibrated to obtain the zero-mode propagation speed of the overhead line segment and the zero-mode propagation speed of the cable segment.

[0018] The zero-mode wave impedance value, forward reflection coefficient, reverse reflection coefficient, and zero-mode propagation velocity are combined and processed into a matrix to obtain the segmented zero-mode propagation parameter matrix.

[0019] Optionally, the step of performing mode coupling conversion processing on the charged zero-mode traveling wave signal through the fault asymmetry point to obtain the fault-excited empty-mode echo includes:

[0020] Based on the characteristics of single-wire grounding faults, the fault point is subjected to three-phase asymmetrical structure identification processing to obtain asymmetrical fault nodes.

[0021] The charged zero-mode traveling wave signal is propagated to the asymmetric fault node for mode conversion efficiency calculation to obtain the zero-mode-empty-mode coupling conversion coefficient.

[0022] The charged zero-mode traveling wave signal is subjected to mode decomposition processing based on the zero-mode to empty-mode coupling conversion coefficient to obtain the transmitted zero-mode component and the converted empty-mode component.

[0023] Based on the fault resistance characteristics, the converted empty mode component is subjected to reflection intensity modulation processing to obtain the fault-modulated empty mode signal.

[0024] The fault-modulated empty-mode signal is transmitted back along the line to obtain the fault-excited empty-mode echo.

[0025] Optionally, the step of using a frequency domain waveform fingerprinting algorithm to perform reflection source screening on the fault excitation empty-mode echo to obtain a clean fault location empty-mode signal includes:

[0026] The fault-excited empty-mode echo input wavelet transform is subjected to time-frequency domain decomposition to obtain a multi-scale spectral feature matrix.

[0027] Based on the multi-scale spectral feature matrix, frequency domain fingerprinting is performed on each reflected wave component to obtain the fingerprints of overhead line connection points, cable connection points, branch lines, and fault points.

[0028] Based on a preset reflection source feature library, pattern matching processing is performed on the fingerprints of overhead line connection points, cable connection points, branch lines, and fault points to obtain a reflection source type identifier vector.

[0029] Based on the reflection source type identifier vector, the fault excitation empty mode echo is classified and filtered to obtain the fault source empty mode component and the non-fault source empty mode component.

[0030] The fault source empty mode component is filtered and purified to obtain the pure fault location empty mode signal.

[0031] Optionally, the step of performing pattern matching processing on the overhead line connection point fingerprint, cable connection point fingerprint, branch line fingerprint, and fault point fingerprint according to a preset reflection source feature library to obtain a reflection source type identifier vector includes:

[0032] The fingerprint of the overhead line connection point is input into the correlation calculator and subjected to unipolar feature matching to obtain the similarity value of the overhead line connection point.

[0033] Based on the cable connection point fingerprint, waveform comparison processing is performed on the bipolar reflection features to obtain the cable connection point similarity value.

[0034] Based on the branch line fingerprint, the amplitude of the high impedance reflection feature is compared to obtain the branch line similarity value.

[0035] The fault point fingerprint is matched with a preset spectrum range in the frequency domain to obtain the fault point similarity value.

[0036] Based on the similarity values ​​of the overhead line connection points, cable connection points, branch lines, and fault points, vector combination processing is performed to obtain the reflection source type identifier vector.

[0037] Optionally, the step of performing inverse time-distance mapping processing on the segmented zero-mode propagation parameter matrix based on the pure fault location empty-mode signal to obtain three-dimensional fault coordinates includes:

[0038] The time difference between the pure fault location empty mode signal and the start time marker of the zero mode propagation is calculated to obtain the total empty mode return time.

[0039] Based on the total return time of the empty mode, the segmented zero-mode propagation parameter matrix is ​​decomposed into segmented propagation time components to obtain the propagation time components of each line segment.

[0040] Based on the propagation time components of each line segment, the zero-mode propagation velocity of the overhead line segment and the zero-mode propagation velocity of the cable segment are calculated by distance inversion to obtain the segment fault distance value.

[0041] The segmented fault distance values ​​are interpolated with the line geographic information database to obtain the plane coordinates and elevation coordinates of the fault points.

[0042] The three-dimensional fault coordinates are obtained by performing accuracy correction processing on the plane coordinates and altitude coordinates of the fault point based on the temperature compensation coefficient.

[0043] Secondly, this application provides a power line fault location system based on traveling wave ranging, the power line fault location system based on traveling wave ranging comprising:

[0044] The injection module is used to perform zero-mode pulse injection processing on the power distribution line through a charged pulse coupler to obtain a charged zero-mode traveling wave signal.

[0045] The analysis module is used to perform wave velocity layer analysis on the hybrid line impedance nodes based on the charged zero-mode traveling wave signal to obtain the segmented zero-mode propagation parameter matrix.

[0046] The conversion module is used to perform mode coupling conversion processing on the charged zero-mode traveling wave signal through the fault asymmetry point to obtain the fault-excited empty-mode echo;

[0047] The filtering module is used to perform reflection source filtering on the fault excitation empty mode echo using a frequency domain waveform fingerprinting algorithm to obtain a clean fault location empty mode signal.

[0048] The mapping module is used to perform inverse time-distance mapping processing on the segmented zero-mode propagation parameter matrix based on the pure fault location empty mode signal to obtain three-dimensional fault coordinates.

[0049] Thirdly, a power distribution line fault location device based on traveling wave ranging is provided, comprising: a memory and at least one processor, wherein the memory stores instructions; the at least one processor invokes the instructions in the memory to cause the power distribution line fault location device based on traveling wave ranging to execute the aforementioned power distribution line fault location method based on traveling wave ranging.

[0050] Fourthly, a computer-readable storage medium is provided, wherein instructions are stored therein, which, when executed on a computer, cause the computer to perform the above-described method for locating power line faults based on traveling wave ranging.

[0051] The technical solution provided in this application obtains a zero-mode traveling wave signal by performing zero-mode pulse injection processing on the power distribution line using a live pulse coupler. This overcomes the limitation of existing technologies that require power outages before active pulse injection, achieving active fault detection while ensuring power supply continuity. Based on the live zero-mode traveling wave signal, wave velocity layering analysis is performed on the impedance nodes of the mixed line to obtain a segmented zero-mode propagation parameter matrix. This effectively solves the ranging error problem caused by the difference in propagation characteristics of different medium sections in mixed power distribution lines, establishing an accurate segmented propagation model. The live zero-mode traveling wave signal is then processed through mode coupling conversion at the fault asymmetry point to obtain the fault excitation empty-mode echo, cleverly utilizing single-wire grounding. The asymmetric characteristics of the fault enable active conversion from zero-mode to empty-mode, generating a dedicated ranging signal with fault characteristics. A frequency domain waveform fingerprinting algorithm is used to identify the reflection source of the fault-excited empty-mode echo, obtaining a pure fault location empty-mode signal. This effectively solves the technical problem of interference from multiple reflection sources in mixed lines. Through intelligent identification algorithms, the fault reflection wave is accurately distinguished from the line structure reflection wave. Based on the pure fault location empty-mode signal, the segmented zero-mode propagation parameter matrix is ​​processed by inverse time-distance mapping to obtain the precise three-dimensional fault coordinates. The time-domain ranging information is organically combined with spatial geographic information to achieve accurate conversion from one-dimensional distance to three-dimensional coordinates, significantly improving the accuracy and practicality of fault location in mixed distribution lines.

[0052] The frequency domain waveform fingerprinting algorithm performs time-frequency domain decomposition processing through wavelet transform, which can simultaneously obtain the time and frequency characteristics of reflected waves. This overcomes the technical deficiency of traditional time-domain analysis methods, which cannot effectively distinguish different reflection sources in mixed lines. The algorithm's established reflection source feature library and pattern matching mechanism enable the system to automatically identify four different types of reflection sources: overhead line connection points, cable connection points, branch lines, and fault points. This solves the key technical problem of complex reflected wave sources in mixed distribution line environments. The reverse time-distance mapping processing algorithm considers the segmented propagation characteristics and temperature compensation factors of mixed lines, converting abstract propagation time into specific geographical coordinates, providing directly usable location information for on-site fault repair. Attached Figure Description

[0053] To more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings used in the description of the embodiments 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 based on these drawings without creative effort.

[0054] Figure 1 This is a schematic diagram of an embodiment of the power distribution line fault location method based on traveling wave ranging in this application.

[0055] Figure 2This is a schematic diagram of an embodiment of the power line fault location system based on traveling wave ranging in this application.

[0056] Figure 3 This is a schematic block diagram of the structure of the power line fault location device based on traveling wave ranging in an embodiment of the present invention. Detailed Implementation

[0057] This application provides a method and system for fault location in power distribution lines based on traveling wave ranging. The terms "first," "second," "third," "fourth," etc. (if present) in the specification, claims, and accompanying drawings of this application are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments described herein can be implemented in a sequence other than that illustrated or described herein. Furthermore, the terms "comprising" or "having" and any variations thereof are intended to cover a non-exclusive inclusion; for example, a process, method, system, product, or device that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or devices.

[0058] For ease of understanding, the specific process of the embodiments of this application is described below. Please refer to [link / reference]. Figure 1 One embodiment of the power distribution line fault location method based on traveling wave ranging in this application includes:

[0059] Step S101: Perform zero-mode pulse injection processing on the power distribution line through a charged pulse coupler to obtain a charged zero-mode traveling wave signal;

[0060] Step S102: Perform wave velocity layer analysis on the impedance nodes of the hybrid line based on the charged zero-mode traveling wave signal to obtain the segmented zero-mode propagation parameter matrix;

[0061] Step S103: The charged zero-mode traveling wave signal is processed by mode coupling conversion through the fault asymmetry point to obtain the fault excitation empty mode echo;

[0062] Step S104: Use the frequency domain waveform fingerprinting algorithm to filter the reflection source of the fault excitation empty mode echo to obtain a clean fault location empty mode signal;

[0063] Step S105: Based on the pure fault location empty mode signal, perform inverse time-distance mapping processing on the segmented zero-mode propagation parameter matrix to obtain the three-dimensional fault coordinates.

[0064] It is understood that the executing entity of this application can be a power distribution line fault location system based on traveling wave ranging, or it can be a terminal or a server; the specific implementation is not limited here. This application's embodiments use a server as an example for illustration.

[0065] Specifically, the charged pulse coupler uses a GPS synchronization clock signal input to the pulse generator for timing calibration. The GPS synchronization clock signal refers to the standard time reference signal provided by the Global Positioning System. The timing calibration process precisely synchronizes the pulse generator's internal clock with the GPS standard time, ensuring that the synchronization error of each phase pulse signal is controlled at the nanosecond level, thus obtaining a synchronization reference time scale. Based on the synchronization reference time scale, the amplitude of a 500kHz square wave pulse is modulated. A square wave pulse refers to a periodic electrical signal with a rectangular waveform. The 500kHz frequency is much higher than the 50Hz fundamental frequency of the power distribution system. The amplitude modulation process adjusts the amplitude of the square wave pulse to the 5kV voltage level, ensuring that the pulse signal can effectively propagate in the power distribution line, obtaining a 5kV standard injection pulse. The 5kV standard injection pulse is then injected in phase through a three-way coupling capacitor circuit. The coupling capacitor circuit includes coupling capacitors and current-limiting inductors. In-phase injection means that the three circuits simultaneously inject the same pulse signal into the A, B, and C phase lines, obtaining a three-phase synchronized pulse signal. A symmetrical component transformation is performed on the three-phase synchronous pulse signal. Symmetrical component transformation is a mathematical method that decomposes an asymmetrical three-phase signal into three symmetrical components: positive sequence, negative sequence, and zero sequence. Since the injected signal is in phase, the transformation mainly produces the zero-sequence component, resulting in a charged zero-mode traveling wave signal. The zero-mode wave impedance matching principle is used to initiate the propagation of the charged zero-mode traveling wave signal. Impedance matching refers to matching the signal source impedance with the characteristic impedance of the transmission line to reduce reflections. The propagation initiation process records the precise moment when the zero-mode signal begins to propagate in the line, obtaining a zero-mode propagation initiation time marker.

[0066] Line topology information is used to identify impedance abrupt change points at overhead line-cable connection points. Line topology information describes the physical connections and geometric structure of power distribution lines. Impedance abrupt change points refer to locations in the line where the wave impedance changes drastically. The identification process determines impedance discontinuities by analyzing the locations of changes in line material, obtaining the coordinates of impedance nodes. Live zero-mode traveling wave signals are used to calculate wave impedance for different dielectric segments. Different dielectric segments refer to overhead line segments and cable segments with different electromagnetic characteristics. The wave impedance calculation process calculates the characteristic impedance value of each segment based on the line's geometric parameters and dielectric characteristics. Overhead lines have higher zero-mode wave impedance values ​​due to their geometric structure and air dielectric characteristics, while cables have lower zero-mode wave impedance values ​​due to their coaxial structure and insulation dielectric characteristics. The zero-mode wave impedance values ​​of overhead line segments and cable segments are used to calculate the reflection coefficient based on the impedance node coordinates. The reflection coefficient is a parameter describing the degree of wave reflection at impedance mismatch points. The calculation uses the reflection coefficient formula to calculate the reflection intensity in different directions of propagation. The forward reflection coefficient represents the degree of reflection when propagating from the overhead line to the cable, and the reverse reflection coefficient represents the degree of reflection when propagating from the cable to the overhead line. The propagation speed of each line segment is calibrated based on the electromagnetic properties of the medium, including relative permittivity and relative permeability. The propagation speed calibration calculates the propagation speed of the zero-mode signal based on the propagation law of electromagnetic waves in different media. Overhead line segments have a higher zero-mode propagation speed due to air, while cable segments have a lower zero-mode propagation speed due to solid insulation. The zero-mode wave impedance value, forward reflection coefficient, reverse reflection coefficient, and zero-mode propagation speed are combined and matrix-constructed. This matrix construction process organizes the various propagation parameters into a two-dimensional array according to the line segment order, resulting in a segmented zero-mode propagation parameter matrix.

[0067] The single-line grounding fault characteristics are used to identify the three-phase asymmetrical structure at the fault point. A single-line grounding fault refers to a fault type in which one phase of a three-phase distribution line forms a short-circuit path with the ground. Three-phase asymmetrical structure refers to the unequal ground impedance of the three phase lines at the fault point. The identification process determines the asymmetrical fault node by detecting the degree of imbalance in the three-phase voltage and current. The mode conversion efficiency of the energized zero-mode traveling wave signal propagating to the asymmetrical fault node is calculated. Mode conversion refers to the phenomenon of mode coupling of electromagnetic waves at the asymmetrical boundary. The conversion efficiency calculation process calculates the proportion of zero-mode signal converted to other mode signals based on the degree of asymmetry and the fault impedance value at the fault point, obtaining the zero-mode-to-empty-mode coupling conversion coefficient. The zero-mode-to-empty-mode coupling conversion coefficient is used to perform mode decomposition processing on the energized zero-mode traveling wave signal. Mode decomposition processing decomposes the incident zero-mode signal into a continuing propagating transmitted zero-mode component and a converted empty-mode component according to the conversion coefficient. The empty-mode component is a propagation mode in a three-phase system with different propagation characteristics than the zero-mode. The fault resistance characteristics are used to modulate the reflection intensity of the converted air-mode component. The fault resistance characteristics refer to the influence of the grounding resistance at the fault point on signal reflection. The reflection intensity modulation process adjusts the reflection amplitude of the air-mode component according to the fault resistance value; the smaller the fault resistance, the stronger the reflection, resulting in a fault-modulated air-mode signal. This fault-modulated air-mode signal is then propagated back along the line. This propagation process refers to the signal's propagation from the fault point towards the signal source. The air-mode signal returns to the beginning of the line with its unique propagation speed and characteristics, resulting in a fault-excited air-mode echo.

[0068] The fault-excited empty-mode echo is input to a wavelet transform for time-frequency domain decomposition. Wavelet transform is a mathematical tool that can analyze signals simultaneously in the time and frequency domains. Time-frequency domain decomposition decomposes complex mixed signals into components of different times and frequencies, each component corresponding to different reflection source characteristics, resulting in a multi-scale spectral feature matrix. The multi-scale spectral feature matrix is ​​then used for frequency domain fingerprint extraction of each reflected wave component. Frequency domain fingerprints refer to the characteristic patterns of reflected waves generated by different reflection sources in the frequency domain. Fingerprint extraction identifies various reflection source types by analyzing the amplitude distribution, phase characteristics, and frequency range of the spectrum. Overhead line connection point fingerprints have unipolar spectral characteristics, cable connection point fingerprints have bipolar spectral characteristics, branch line fingerprints have high-frequency attenuation characteristics, and fault point fingerprints have a spectral distribution within a specific frequency range. A pre-established reflection source feature library is used for pattern matching processing of the fingerprints of overhead line connection points, cable connection points, branch lines, and fault points. The reflection source feature library is a pre-built database containing various frequency domain features of reflection sources. Pattern matching determines the reflection source type by calculating the similarity between the extracted fingerprint and the standard patterns in the feature library, resulting in a reflection source type identifier vector. The reflection source type identification vector is used to classify and filter fault-excited empty-mode echoes. Based on the identification results of each reflection source in the identification vector, the mixed empty-mode echo signal is separated into signal components from different sources. The fault-source empty-mode component corresponds to the reflection signal generated by the fault point, while the non-fault-source empty-mode component corresponds to the reflection signal generated by the line structure. The fault-source empty-mode component undergoes filtering and purification processing. Digital filtering technology is used to remove noise and interference components from the fault-source empty-mode component, retaining pure fault characteristic information to obtain a pure fault location empty-mode signal.

[0069] The time difference between the clean fault location empty-mode signal and the zero-mode propagation start time marker is calculated. This time difference calculation determines the round-trip propagation time by measuring the difference between the arrival time of the empty-mode echo signal at the detection point and the transmission time of the zero-mode signal. Since the empty-mode signal needs to propagate from the beginning of the line to the fault point and back, the time difference reflects the propagation time corresponding to twice the fault distance, thus obtaining the total empty-mode return time. The total empty-mode return time is then decomposed into segmented propagation time components based on the segmented structure of the hybrid line and the propagation speed of each segment. This segmented propagation time decomposition allocates the total propagation time to each line segment by solving a system of linear equations, thus obtaining the propagation time components for each line segment. The propagation time component of each line segment is used to perform distance inversion calculations on the zero-mode propagation velocity of overhead line segments and cable segments. This distance inversion calculation is the reverse process of multiplying propagation time by propagation velocity. By multiplying the propagation time component of each segment by its corresponding propagation velocity, the propagation distance of each segment is obtained. The sum of these distances determines the location of the fault point within the entire line, yielding the segmented fault distance value. The segmented fault distance value is then interpolated using a line geographic information database containing detailed coordinate information of the line path. The spatial coordinate interpolation process calculates the location of the fault point on the line path based on the fault distance, converting the one-dimensional distance information into two-dimensional planar coordinates and elevation information, resulting in the planar and elevation coordinates of the fault point. A temperature compensation coefficient is used to correct the accuracy of the fault point's planar and elevation coordinates. This temperature compensation coefficient reflects the influence of ambient temperature on signal propagation velocity. The accuracy correction process adjusts the propagation velocity based on the actual ambient temperature, thereby correcting the distance calculation results, ultimately obtaining the temperature-compensated three-dimensional accurate fault coordinates.

[0070] In one specific embodiment, the process of performing step S101 may specifically include the following steps:

[0071] The GPS synchronization clock signal is input into a pulse generator for timing calibration to obtain a synchronization reference time scale.

[0072] Amplitude modulation of a 500kHz square wave pulse is performed based on a synchronous reference time scale to obtain a 5kV standard injection pulse.

[0073] The 5kV standard injection pulse is processed into a three-phase synchronous pulse signal by injecting it in phase through a three-way coupling capacitor circuit.

[0074] A symmetrical component transformation process is performed on the three-phase synchronous pulse signal to obtain a charged zero-mode traveling wave signal.

[0075] Based on the zero-mode impedance matching principle, the propagation start-up process of the charged zero-mode traveling wave signal is performed to obtain the zero-mode propagation start-up time marker.

[0076] Specifically, the data processing of the GPS synchronization clock signal input pulse generator for timing calibration involves converting the satellite time reference signal into a digital time code recognizable by the local device. The GPS synchronization clock signal refers to the standard time reference signal provided by the Global Positioning System, which contains precise second pulse signals and time data. The pulse generator contains a phase-locked loop circuit and a clock divider. The timing calibration process compares the GPS second pulse with the clock signal generated by the local crystal oscillator, calculates the frequency deviation, and adjusts the division ratio of the local clock to keep the local clock frequency consistent with the GPS standard frequency. The calibration process continuously monitors the phase difference between the two clock signals. When the phase difference exceeds a set threshold, the phase of the local clock is automatically adjusted, ultimately obtaining a synchronization reference time scale that is completely synchronized with GPS time. The accuracy of this time scale reaches the nanosecond level and has global uniformity.

[0077] The data processing procedure for amplitude modulation of a 500kHz square wave pulse based on a synchronous reference time mark first uses the synchronous reference time mark as a trigger signal to start the square wave pulse generation circuit. A square wave pulse refers to a periodic electrical signal with a rectangular waveform. Its frequency is set to 500kHz to ensure sufficient frequency interval with the 50Hz fundamental frequency of the power distribution system. The amplitude modulation process uses a controllable gain amplifier to amplify the amplitude of the square wave pulse step by step from the standard output voltage of the signal generator to the 5kV high voltage level. The amplification process adopts a multi-stage amplification structure. The gain of each stage amplifier is dynamically adjusted according to the amplitude of the input signal. At the same time, the peak value and effective value of the output voltage are monitored. When the output voltage reaches the standard value of 5kV, the amplification stops and the voltage is kept stable, resulting in a standard injection pulse with an amplitude of 5kV and a frequency of 500kHz.

[0078] The data processing of injecting a 5kV standard injection pulse in phase through a three-channel coupling capacitor circuit involves signal power distribution and impedance matching calculations. The three coupling capacitor circuits are connected to the A, B, and C phases of the distribution line, respectively. Each circuit contains a coupling capacitor and a current-limiting inductor. The capacitance of the coupling capacitor and the inductance of the current-limiting inductor are designed according to the line impedance characteristics. The in-phase injection process uses a power divider to distribute the single 5kV standard injection pulse to the three output ports with equal amplitude. The output signal of each port has equal amplitude and zero phase difference. The signal is capacitively coupled to the distribution line through the coupling capacitor. The current-limiting inductor limits the peak value of the injected current to prevent impact on the line. The three circuits simultaneously inject the same pulse signal into the three-phase line. Since the three signals have equal amplitude and the same phase, a three-phase synchronous pulse signal in phase is formed in the line.

[0079] The data processing procedure for symmetrical component transformation of three-phase synchronous pulse signals uses the Clarke transform matrix to convert the three-phase signals into symmetrical components. Symmetrical component transformation is a mathematical method in power system analysis to decompose asymmetrical three-phase quantities into positive-sequence, negative-sequence, and zero-sequence symmetrical components. The Clarke transform matrix is ​​a 3x3 matrix, and its elements contain complex coefficients with a 120-degree phase relationship. The transformation process takes the synchronous pulse signals of phases A, B, and C as input vectors, and obtains the positive-sequence, negative-sequence, and zero-sequence components through matrix multiplication. Since the input three-phase signals have equal amplitudes and are in phase, the amplitudes of the positive-sequence and negative-sequence components are zero, and the amplitude of the zero-sequence component is equal to the amplitude of a single-phase signal. The zero-sequence component propagates in the distribution line in zero-mode form, and has different propagation characteristics from the positive-sequence and negative-sequence components. The resulting charged zero-mode traveling wave signal contains the complete injected pulse energy and has zero-mode propagation characteristics.

[0080] The data processing for propagation initiation of charged zero-mode traveling wave signals based on the zero-mode impedance matching principle involves impedance calculation and reflection coefficient optimization. Zero-mode impedance refers to the characteristic impedance encountered by a zero-mode signal in a transmission line, the value of which is determined by the geometry of the line and the characteristics of the medium. The impedance matching principle requires that the output impedance of the signal source be equal to the characteristic impedance of the transmission line to minimize signal reflection. The propagation initiation process first calculates the zero-mode characteristic impedance of the distribution line, and then adjusts the output impedance of the coupling circuit to match the line impedance. Impedance matching is achieved by adjusting the capacitance of the coupling capacitor and the inductance of the current-limiting inductor. When the output impedance matches the line impedance, the reflection coefficient is close to zero. At this time, the charged zero-mode traveling wave signal can be transmitted to the line with maximum power. The propagation initiation process also records the precise time when the zero-mode signal begins to propagate. This time is measured by a high-precision timer and associated with a GPS synchronization reference time scale to obtain the zero-mode propagation initiation time marker.

[0081] In one specific embodiment, the process of performing step S102 may specifically include the following steps:

[0082] Based on the line topology information, impedance abrupt change points are identified at the connection points of overhead lines and cables to obtain the coordinates of impedance nodes.

[0083] Based on the zero-mode traveling wave signal, the wave impedance of different dielectric sections is calculated to obtain the zero-mode wave impedance values ​​of overhead line sections and cable sections.

[0084] The reflection coefficients of the impedance node positions are calculated based on the zero-mode wave impedance values ​​of the overhead line segment and the cable segment to obtain the forward reflection coefficient and the reverse reflection coefficient.

[0085] Based on the electromagnetic properties of the medium, the propagation speed of each line segment is calibrated to obtain the zero-mode propagation speed of the overhead line segment and the zero-mode propagation speed of the cable segment.

[0086] The zero-mode wave impedance, forward reflection coefficient, reverse reflection coefficient, and zero-mode propagation velocity are combined and processed into a matrix to obtain a segmented zero-mode propagation parameter matrix.

[0087] Specifically, detailed topology data of the lines is retrieved from the power distribution management system. The line topology information includes basic data such as the physical structure of the lines, material distribution, and connection node locations. The topology data is stored in the form of database tables. Each record contains fields such as line segment number, start coordinates, end coordinates, and line type. Impedance abrupt change points refer to the locations in the line where the wave impedance changes drastically. They mainly occur at the connection points between overhead lines and cables. The identification process involves traversing the line type field in the topology database. When the type field of two adjacent line segments changes from overhead line to cable or from cable to overhead line, the location is marked as an impedance abrupt change point. The identification algorithm also extracts the GPS coordinate information of the location and arranges all the identified abrupt change point locations in order of distance from the line start point, resulting in an array of impedance node location coordinates containing latitude and longitude coordinates and distance information. The data processing of zero-mode traveling wave signals for different dielectric segments involves the calculation of transmission line parameters in electromagnetic field theory. Wave impedance refers to the ratio of the electric field to the magnetic field when an electromagnetic wave propagates in a transmission medium. Its value is determined by the geometry of the conductor and the electromagnetic properties of the surrounding medium. The calculation process first extracts the geometric parameters of each line segment from the topology database. The geometric parameters of overhead line segments include conductor radius, conductor spacing, and height above the ground. The geometric parameters of cable segments include conductor radius, insulation thickness, and shielding radius. The calculation process calculates the zero-mode wave impedance of each segment based on these geometric parameters and the relative permittivity of the medium. The zero-mode wave impedance calculation of overhead lines considers the mirror effect between the conductor and the ground, while the zero-mode wave impedance calculation of cables considers the field distribution characteristics of the coaxial structure. The calculation process uses numerical integration to solve the complex electromagnetic field distribution, and finally obtains the zero-mode wave impedance value corresponding to each overhead line segment and cable segment. These values ​​constitute the data set of zero-mode wave impedance values ​​for overhead line segments and cable segments.

[0088] The data processing procedure for calculating the reflection coefficients of impedance node positions based on the zero-mode impedance values ​​of overhead line segments and cable segments is based on the impedance mismatch reflection principle in transmission line theory. The reflection coefficient is a dimensionless parameter describing the intensity of electromagnetic wave reflection at impedance discontinuities; its value is equal to the ratio of the reflected wave amplitude to the incident wave amplitude. The calculation process calculates the reflection coefficients in two directions for each impedance node. The forward reflection coefficient corresponds to the reflection of the signal when it propagates from the overhead line segment to the cable segment, and is calculated as the difference between the cable segment impedance and the overhead line segment impedance, divided by the sum of the two. The reverse reflection coefficient corresponds to the reflection of the signal when it propagates from the cable segment to the overhead line segment, and is also calculated as the difference between the overhead line segment impedance and the cable segment impedance, divided by the sum of the two. The calculation process establishes a correlation between the position coordinates of each impedance node and its corresponding forward and reverse reflection coefficients, forming a data structure with node position as the index and reflection coefficient as the value. This data structure facilitates subsequent signal propagation analysis and reflected wave identification.

[0089] The data processing for calibrating the propagation speed of each line segment based on the electromagnetic properties of the medium is based on the propagation law of electromagnetic waves in different media. The propagation speed is closely related to the relative permittivity and relative permeability of the medium. The calibration process first obtains the electromagnetic property parameters of various media from the material database. The air medium around the overhead line has electromagnetic properties close to a vacuum, and its relative permittivity is close to 1. The solid insulation medium in the cable has a higher relative permittivity. The calibration process calculates the propagation speed of the zero-mode signal in different media based on these electromagnetic property parameters. The calculation process adopts the relationship that the propagation speed is equal to the speed of light divided by the square root of the equivalent permittivity of the medium. At the same time, the influence of the line geometry on the equivalent permittivity is considered. The equivalent permittivity of the overhead line is mainly determined by the air medium, while the equivalent permittivity of the cable is determined by the dielectric properties of the insulation material. The calibration process establishes a mapping relationship between the calculated propagation speed and the corresponding line segment, and obtains the zero-mode propagation speed data of the overhead line segment and the cable segment distributed by line segment.

[0090] The data processing procedure for constructing a matrix using a combination of zero-mode impedance, forward reflection coefficient, reverse reflection coefficient, and zero-mode propagation velocity organizes the various propagation parameters calculated above according to a unified data structure. The matrix construction process first determines the matrix dimension and indexing method. The number of rows in the matrix equals the total number of line segments, and the number of columns equals the number of parameter types. Each row corresponds to a line segment, and each column corresponds to a propagation parameter. The construction process fills the matrix elements according to the spatial order of the line segments. The first column is filled with the zero-mode impedance value of the segment, the second column with the forward reflection coefficient, the third column with the reverse reflection coefficient, and the fourth column with the zero-mode propagation velocity. For line segments without impedance abrupt changes, their reflection coefficient is set to zero. The construction process also adds the starting position and length information of the line segments as auxiliary parameters to the matrix, finally obtaining a segmented zero-mode propagation parameter matrix containing complete propagation characteristics. Each element of this matrix is ​​associated with specific physical quantities and location information.

[0091] In one specific embodiment, the process of executing step S103 may specifically include the following steps:

[0092] Based on the characteristics of single-wire grounding faults, the fault point is subjected to three-phase asymmetrical structure identification processing to obtain asymmetrical fault nodes.

[0093] The charged zero-mode traveling wave signal is propagated to the asymmetric fault node for mode conversion efficiency calculation, and the zero-mode to empty-mode coupling conversion coefficient is obtained.

[0094] The charged zero-mode traveling wave signal is subjected to mode decomposition based on the zero-mode to empty-mode coupling conversion coefficient to obtain the transmitted zero-mode component and the converted empty-mode component.

[0095] Based on the characteristics of fault resistance, the reflection intensity modulation processing of the converted empty mode component is performed to obtain the fault-modulated empty mode signal.

[0096] The fault-modulated empty-mode signal is transmitted back along the line to obtain the fault-excited empty-mode echo.

[0097] Specifically, the data processing procedure for identifying three-phase asymmetric structures at the fault point based on the characteristics of single-phase grounding faults is based on the electrical characteristic analysis of single-phase grounding faults in power distribution lines. A single-phase grounding fault refers to a fault type in a three-phase power distribution line where one phase conductor forms a conductive path with the ground. This type of fault leads to a decrease in the voltage to ground of the faulty phase while the voltage to ground of the other two phases increases. Three-phase asymmetric structure refers to the electrical state where the impedance to ground of the three phase conductors at the fault point is unequal. The identification process detects the degree of asymmetry by monitoring real-time data of three-phase voltage and current, and the processing algorithm calculates the imbalance of the three-phase voltage. The unbalance degree is equal to the difference between the maximum and minimum phase voltages divided by the average of the three-phase voltages. When the unbalance degree exceeds a set threshold, a single-phase ground fault is determined. At the same time, the fault phase is determined by analyzing the amplitude and phase relationship of the zero-sequence voltage and zero-sequence current. The zero-sequence voltage is the vector sum of the three-phase voltages, and the zero-sequence current is the vector sum of the three-phase currents. During normal operation, the zero-sequence quantity is close to zero. When a single-phase ground fault occurs, the zero-sequence quantity increases significantly. The identification process marks the location of the detected fault as an asymmetrical fault node. The location of this node is initially estimated by the relationship between the traveling wave propagation time and propagation distance.

[0098] The data processing for calculating the mode conversion efficiency of a charged zero-mode traveling wave signal propagating to an asymmetrical fault node involves the mode coupling mechanism in electromagnetic field theory. Mode conversion refers to the phenomenon where the propagation mode of an electromagnetic wave changes when it encounters an asymmetrical boundary during propagation. In a symmetrical three-phase system, the zero-mode signal propagates with a specific field distribution mode. When it encounters a single-phase ground fault, the asymmetry of the fault point disrupts the original field distribution, causing some zero-mode energy to be converted into other propagation modes. Mode conversion efficiency is a parameter describing the degree of energy conversion, and its value is related to the degree of asymmetry at the fault point and... The calculation process is related to the fault resistance value. First, an equivalent circuit model of the fault point is established. This model includes the grounding resistance of the fault phase and the ground capacitance of the non-fault phase. Then, the field distribution change of the incident zero-mode signal at the fault point is calculated according to the electromagnetic field boundary conditions. The calculation process uses modal analysis to decompose the changed field distribution into the superposition of various propagation modes. The zero-mode to empty-mode coupling conversion coefficient is equal to the ratio of the energy converted to the empty mode to the total energy of the incident zero mode. The value of this coefficient is between zero and one. The smaller the fault resistance, the higher the conversion efficiency. The greater the asymmetry of the fault point, the higher the conversion efficiency.

[0099] The data processing procedure for mode decomposition of charged zero-mode traveling wave signals using zero-mode-empty-mode coupling conversion coefficients decomposes the incident zero-mode signal into different output components according to the principle of energy conservation. The mode decomposition process calculates the amplitude of each component based on the conversion coefficients. The transmitted zero-mode component is the signal portion that continues to propagate in zero-mode form; its amplitude is equal to the incident zero-mode signal amplitude multiplied by one minus the conversion coefficient. The converted empty-mode component is the empty-mode signal portion generated by zero-mode conversion; its amplitude is equal to the incident zero-mode signal amplitude multiplied by the conversion coefficient. Empty mode is another propagation mode in a three-phase system, distinct from zero mode, with different field distribution characteristics and propagation properties. The decomposition process also considers the phase relationship of each component. The transmitted zero-mode component maintains the same phase as the incident signal, while the phase of the converted empty-mode component is determined based on the field distribution changes during the conversion process. The decomposition process stores the amplitude and phase information of these components in a data structure, forming a signal description containing complete mode information. This description records the mode conversion process and result of the signal at the fault point.

[0100] The data processing procedure for modulating the reflection intensity of the converted air-mode component based on the fault resistance characteristics is based on the influence mechanism of the grounding resistance at the fault point on signal reflection. The fault resistance is the equivalent resistance between the fault phase conductor and the ground, and its value determines the impedance characteristics and signal reflection intensity at the fault point. The reflection intensity modulation process calculates the reflection coefficient of the air-mode component at the fault point based on the fault resistance value. The reflection coefficient is equal to the difference between the fault point impedance and the air-mode characteristic impedance, divided by the sum of the two. When the fault resistance is zero, the reflection coefficient is close to negative one, indicating strong reflection. When the fault resistance is very large, the reflection coefficient is close to zero, indicating weak reflection. The modulation process multiplies the amplitude of the converted air-mode component by the reflection coefficient to obtain the amplitude of the reflected air-mode component. At the same time, it adjusts the phase of the reflected signal according to the phase change during the reflection process. The smaller the fault resistance, the stronger the reflected signal, and the larger the fault resistance, the weaker the reflected signal. The modulation process also considers the influence of the frequency characteristics of the fault resistance on different frequency components. The reflection intensity of high-frequency components is usually higher than that of low-frequency components. The modulation process applies these frequency-related modulation effects to the spectrum of the air-mode component to obtain the fault-modulated air-mode signal modulated by the fault resistance characteristics.

[0101] The data processing procedure for fault-modulated unmodulated signals during return transmission along the line simulates the signal propagation process from the fault point towards the signal source. The return transmission process calculates the propagation parameters of the signal on the return path based on the propagation characteristics of the unmodulated signal. The unmodulated signal has different propagation speed and attenuation characteristics than the zero-mode signal. The propagation speed is determined by the geometry and medium characteristics of the line, while the attenuation characteristics are related to the signal frequency and line loss. The return transmission process treats the fault-modulated unmodulated signal as a new signal source and calculates its propagation process along the line. The processing considers the propagation delay and amplitude variations of the signal in different line segments. When passing through impedance abrupt change points, additional reflections and transmissions occur. The feedback processing calculates the impact of these secondary reflections on the signal waveform, while also considering the attenuation effect of line loss on the signal amplitude. The attenuation degree is proportional to the propagation distance and signal frequency. The feedback processing also simulates the dispersion effect of the signal during propagation. The slight difference in the propagation speed of different frequency components leads to signal waveform distortion. The processing algorithm takes all these propagation effects into account and calculates the waveform characteristics when the fault-modulated empty-mode signal returns to the line starting point, obtaining the fault-excited empty-mode echo. This echo signal carries the location information and fault characteristic information of the fault point.

[0102] In one specific embodiment, the process of executing step S104 may specifically include the following steps:

[0103] The fault-excited empty-mode echo is input into a wavelet transform and decomposed in the time-frequency domain to obtain a multi-scale spectral feature matrix.

[0104] Based on the multi-scale spectral feature matrix, frequency domain fingerprinting is performed on each reflected wave component to obtain fingerprints of overhead line connection points, cable connection points, branch lines, and fault points.

[0105] Based on the preset reflection source feature library, pattern matching processing is performed on the fingerprints of overhead line connection points, cable connection points, branch lines, and fault points to obtain the reflection source type identifier vector.

[0106] Based on the reflection source type identifier vector, the fault excitation empty mode echo is classified and filtered to obtain the fault source empty mode component and the non-fault source empty mode component.

[0107] The fault source empty mode component is filtered and purified to obtain a pure fault location empty mode signal.

[0108] Specifically, the data processing procedure for time-frequency domain decomposition of the fault-excited empty-mode echo input wavelet transform is based on the multi-resolution analysis principle of wavelet transform. Wavelet transform is a mathematical tool capable of analyzing signals simultaneously in the time and frequency domains. Unlike Fourier transform, which only provides frequency domain information, wavelet transform can provide local characteristics of signals at different times and frequencies. The wavelet transform first selects a suitable mother wavelet function as the basis for analysis. The mother wavelet function generates a series of wavelet basis functions through time shifting and scaling. Each basis function corresponds to a specific time window and frequency range. The time-frequency domain decomposition... The solution process involves convolving the fault-excited empty-mode echo signal with each wavelet basis function. The convolution result represents the energy distribution of the signal at the corresponding time-frequency position. The processing adopts the discrete wavelet transform algorithm to discretize the continuous signal into digital sampling points, and then performs wavelet decomposition layer by layer. Each layer of decomposition divides the signal into high-frequency detail components and low-frequency approximate components. Multi-layer decomposition forms spectrum analysis results at different scales, and finally obtains a multi-scale spectrum feature matrix containing three-dimensional information of time, frequency and amplitude. The rows of this matrix correspond to time sampling points, the columns correspond to frequency components, and the matrix element values ​​represent the signal strength at that time-frequency point.

[0109] The data processing procedure for extracting frequency domain fingerprints of each reflected wave component from a multi-scale spectral feature matrix involves pattern recognition based on the frequency domain characteristics of different reflection sources. Frequency domain fingerprints refer to the characteristic patterns of reflected waves generated by different types of reflection sources in the frequency domain. Each reflection source leaves unique features in the spectrum due to its different physical structure and electrical characteristics. The fingerprint extraction process first segments the multi-scale spectral feature matrix into time-frequency regions, dividing the matrix into different time windows based on the arrival time of the reflected wave. Each window corresponds to a reflection source. Then, frequency domain feature parameters are extracted within each time window. The extraction process for fingerprints at overhead line connection points is analyzed. Unipolar reflection characteristics: This type of reflected wave is characterized by a concentrated main frequency component and fewer harmonic components in the spectrum. The extraction process of cable connection point fingerprints identifies its bipolar reflection characteristics: This type of reflected wave exhibits the coexistence of the main frequency and second harmonic in the spectrum. The extraction process of branch line fingerprints detects its high impedance reflection characteristics: This type of reflected wave has significant attenuation in the high frequency band. The extraction process of fault point fingerprints identifies its mode conversion characteristics: This type of reflected wave has concentrated energy within a specific frequency range. The fingerprint extraction process organizes these frequency domain feature parameters into feature vectors, each of which contains parameters such as center frequency, bandwidth, energy distribution, and phase characteristics.

[0110] The data processing of the pre-established reflection source feature library for pattern matching of fingerprints from overhead line connection points, cable connection points, branch lines, and fault points employs a pattern recognition algorithm to compare the similarity between the extracted fingerprints and standard patterns. The reflection source feature library is a pre-built database containing standard frequency domain features of various reflection sources. This library was established through extensive experimental and simulation data, with each reflection source type corresponding to a set of standard feature parameters. The pattern matching process uses correlation analysis to calculate the matching degree between the extracted fingerprints and the standard features. The matching algorithm first normalizes the extracted feature vectors and the standard vectors in the feature library to eliminate the influence of amplitude differences. Then, it calculates the Euclidean distance or cosine similarity between the two vectors; a smaller distance or a larger similarity indicates a higher degree of matching. The matching process compares each extracted fingerprint with four standard features, obtaining four matching scores. The type with the highest matching score is taken as the identification result of that fingerprint, and the matching confidence is recorded. When the highest matching score is lower than a set threshold, it is marked as an unknown type. The matching process organizes all identification results into a reflection source type identifier vector, where each element of the vector corresponds to a reflected wave component, and the element value represents the reflection source type of that component.

[0111] The data processing procedure for classifying and filtering fault-excited empty-mode echoes using reflection source type identifier vectors separates the mixed signal into signal components from different sources based on the identification results. The classification and filtering process first establishes a mapping relationship between time windows and reflection source types. The reflection source type corresponding to each time window is determined based on the reflection source type identifier vector. Then, time-domain filtering techniques are used to extract the signal components corresponding to the time windows from the original fault-excited empty-mode echoes. The filtering process uses rectangular or Gaussian window functions to segment the signal in the time domain. The position and width of the window function are determined based on the arrival time and duration of the reflected wave. The segmented signal components are classified according to the reflection source type. Signal components identified as fault point types are classified into fault source empty-mode components, while other types of signal components are classified into non-fault source empty-mode components. The filtering process also considers the mutual influence between signal components. When signals in adjacent time windows overlap, a weighted separation method is used, assigning weights based on the identification confidence of each component. Components with higher confidence receive greater weights. The final filtering process yields clearly separated fault source empty-mode components and non-fault source empty-mode components.

[0112] The data processing steps for filtering and purifying the fault source's empty-mode component employ digital filtering technology to remove noise and interference from the signal. The filtering and purification process first analyzes the spectral characteristics of the fault source's empty-mode component to determine the frequency range of the useful signal and the frequency distribution of the noise. Then, a suitable digital filter is designed for signal purification. The filter design considers the frequency band characteristics of the fault characteristic signal, using a bandpass filter to retain the signal components of the fault characteristic frequency band while suppressing noise interference outside the band. The filter's passband frequency is determined based on the center frequency of the fault point fingerprint, the passband width is set based on the fingerprint's bandwidth, and the stopband attenuation is determined based on noise suppression requirements. The purification process also employs adaptive filtering technology to dynamically adjust the filtering parameters, optimizing the filtering effect based on the real-time characteristics of the signal. The adaptive algorithm monitors the signal-to-noise ratio (SNR) of the filtered output, automatically adjusting the filter parameters when the SNR falls below the expected value. The purification process ultimately yields a clean fault location empty-mode signal with noise and interference removed. This signal retains the key characteristic information of the fault point while filtering out irrelevant interference components.

[0113] In one specific embodiment, the process of performing pattern matching processing on the overhead line connection point fingerprint, cable connection point fingerprint, branch line fingerprint, and fault point fingerprint according to a preset reflection source feature library can specifically include the following steps:

[0114] The fingerprint of the overhead line connection point is input into the correlation calculator for unipolar feature matching to obtain the similarity value of the overhead line connection point.

[0115] Based on the waveform comparison of bipolar reflection features using cable connection point fingerprints, the similarity values ​​of cable connection points are obtained.

[0116] The similarity value of the branch line is obtained by comparing the amplitude of the high impedance reflection characteristics based on the branch line fingerprint.

[0117] The fault point fingerprint is matched with the preset spectrum range in the frequency domain to obtain the fault point similarity value.

[0118] Vector combination processing is performed based on the similarity values ​​of overhead line connection points, cable connection points, branch lines, and fault points to obtain the reflection source type identifier vector.

[0119] Specifically, the data processing procedure for unipolar feature matching of the overhead line connection point fingerprint input correlation calculator is based on signal correlation analysis theory. The correlation calculator is a digital processing unit specifically used to calculate the correlation between two signal sequences. Unipolar feature refers to the waveform characteristic of the reflected wave generated at the overhead line connection point having a single polarity change. This characteristic originates from the unidirectional reflection caused by the impedance change at the connection between the overhead line and the cable. The unipolar feature matching process first aligns the fingerprint of the overhead line connection point with a pre-stored standard unipolar template in the time domain. The alignment process uses a cross-correlation function to find the optimal matching position between the two signals. The cross-correlation function calculates the correlation between the two signals. The correlation coefficients at different time offsets are used to determine the optimal alignment position when the correlation coefficient reaches its maximum value. After matching, the Pearson correlation coefficient between the aligned fingerprint signal and the standard template is calculated. This coefficient reflects the similarity between the two signal waveforms. The calculation of the correlation coefficient involves dividing the covariance of the corresponding sampling points of the two signals by the product of their respective standard deviations. The calculation result ranges from negative one to positive one. The closer the value is to positive one, the higher the similarity. The processing also considers the influence of signal amplitude. Normalization is used to eliminate the interference of amplitude differences on the correlation calculation. Finally, the similarity value of the overhead line connection points, which characterizes the matching degree of the overhead line connection points, is obtained.

[0120] The data processing procedure for waveform comparison of cable connection point fingerprints addresses the unique bipolar reflection phenomenon at cable connection points. Bipolar reflection refers to the alternating positive and negative reflected waveforms of signals at the cable connection point, caused by the coaxial structure of the cable and variations in dielectric properties. The waveform comparison process first detects the polarity of the cable connection point fingerprint. The detection algorithm identifies the location and amplitude of the polarity changes by analyzing the zero-crossing distribution of the signal. Then, waveform matching is performed with a standard bipolar template. The matching process employs a dynamic time warping algorithm to handle inconsistencies in signal length. The algorithm constructs a cost matrix to find the optimal correspondence between two signals. Each element of the cost matrix represents the distance cost between corresponding points of the two signals. The algorithm finds the path with the minimum cumulative cost from the upper left corner to the lower right corner of the matrix. This path corresponds to the best alignment of the two signals. The algorithm then compares and calculates the root mean square error of the aligned signals. The root mean square error is equal to the square root of the mean of the squares of the differences between the corresponding sampling points. The smaller the error, the higher the waveform similarity. The processing converts the error value into a similarity value. The conversion formula is one minus the normalized root mean square error to obtain the similarity value of the cable connection point.

[0121] The data processing procedure for amplitude comparison of high-impedance reflection characteristics in branch line fingerprints specifically analyzes the high-impedance reflection phenomenon at branch line connection points. High-impedance reflection refers to the strong reflection phenomenon caused by the open circuit or high-impedance load characteristics of branch lines. This reflection is characterized by a reflection coefficient close to positive one and a reflected wave amplitude close to the incident wave amplitude. Amplitude comparison processing first extracts the peak amplitude information of the branch line fingerprint. The peak detection algorithm determines the amplitude of the reflected wave by finding the local maximum value of the signal. The detection process considers the influence of noise and uses a threshold decision method to eliminate false peaks caused by noise. The threshold is set to a value equal to the root mean square value of the signal. A fixed multiple is used, and only peak values ​​exceeding a threshold are considered valid reflected wave peak values. The comparison process compares the detected peak values ​​with the peak values ​​of a standard high-impedance reflection template. The comparison algorithm calculates the relative error between the two peak values. The relative error is equal to the absolute value of the peak difference divided by the standard peak value. The smaller the error, the higher the matching degree. The processing also analyzes the distribution pattern of the peak values. High-impedance reflection usually manifests as a single significant peak value, while other types of reflection show multiple peak values ​​or a wide peak distribution. The distribution pattern matching evaluates the matching degree by calculating the concentration parameter of the peak values. Finally, the relative error and the distribution matching results are combined to calculate the similarity value of the branch line.

[0122] The data processing procedure for frequency domain matching of fault point fingerprints with a preset spectral range is based on the spectral characteristics of the mode-converted signal generated by the fault point. The preset spectral range is a characteristic frequency interval determined according to the zero-mode-to-empty-mode conversion mechanism of the fault point. This frequency range is usually concentrated in a specific frequency band and has obvious energy peaks. The frequency domain matching process first performs a fast Fourier transform on the fault point fingerprint to convert the time-domain signal into a frequency-domain representation. The transform process decomposes the discrete-time signal into sine and cosine components of different frequencies. Each frequency component contains amplitude and phase information. The processing algorithm extracts the power spectral density from the transform result. The power spectral density represents the energy distribution of the signal at various frequencies. Then, the power spectrum is compared with the preset spectral range for overlap analysis. The overlap calculation involves the ratio of the intersection area to the union area of ​​the two spectral regions. The larger the ratio, the higher the degree of matching. The matching process also calculates the center frequency offset of the spectrum. The center frequency is the centroid position of the power spectrum. The offset reflects the degree of difference between the actual spectrum and the standard spectrum. The processing comprehensively considers the two factors of overlap and center frequency offset, and calculates the comprehensive matching score through a weighted average method to obtain the fault point similarity value.

[0123] The data processing procedure for vector combination of similarity values ​​for overhead line connection points, cable connection points, branch lines, and fault points organizes various similarity values ​​into vector form according to specific rules. The vector combination process first normalizes each similarity value to eliminate differences in numerical ranges caused by different calculation methods, ensuring that each similarity value falls within the same numerical range. The normalization formula is the original value minus the minimum value, divided by the difference between the maximum and minimum values. The processed result ranges from zero to one. The combination process then constructs a four-dimensional vector. The first component of the vector corresponds to the similarity value of overhead line connection points, the second to cable connection points, the third to branch lines, and the fourth to fault points. The vector combination also includes type determination logic. The determination process determines the reflection source type by comparing the values ​​of the four components. The reflection source type corresponding to the component with the largest value is considered the most likely type, and this maximum value is recorded as a confidence index. When the difference between the maximum and the second largest value is less than a set threshold, it is marked as fuzzy identification and requires further analysis. The final combination process generates a reflection source type identifier vector containing type identification and confidence information.

[0124] In one specific embodiment, the process of executing step S105 may specifically include the following steps:

[0125] The time difference between the clean fault location empty mode signal and the start time mark of zero mode propagation is calculated to obtain the total empty mode return time.

[0126] Based on the total return time of the empty mode, the segmented zero-mode propagation parameter matrix is ​​decomposed into segmented propagation time components to obtain the propagation time components of each line segment.

[0127] Based on the propagation time components of each line segment, the distance inversion calculation is performed on the zero-mode propagation velocity of the overhead line segment and the zero-mode propagation velocity of the cable segment to obtain the segment fault distance value.

[0128] The segmented fault distance values ​​are interpolated with the line geographic information database to obtain the plane coordinates and elevation coordinates of the fault points.

[0129] Based on the temperature compensation coefficient, the plane coordinates and altitude coordinates of the fault point are corrected to obtain the three-dimensional fault coordinates.

[0130] Specifically, the data processing procedure for calculating the time difference between the pure fault location empty-mode signal and the zero-mode propagation start time marker is based on precise time measurement technology. The pure fault location empty-mode signal is a fault reflection signal that has been filtered and purified to remove interference components. This signal carries the timestamp information of the fault point. The zero-mode propagation start time marker is the precise time point at which the zero-mode signal begins to propagate in the line. This time is recorded by associating a high-precision timer with a GPS synchronization reference time marker. The time difference calculation process first detects the arrival time of the pure fault location empty-mode signal. The detection algorithm uses wavefront detection technology to identify the starting edge of the signal. Wavefront detection analyzes the signal... The abrupt change in amplitude determines the precise arrival time of the signal. The detection process sets dual criteria of amplitude threshold and slope threshold. When the signal amplitude exceeds the amplitude threshold and the rate of change of amplitude exceeds the slope threshold, it is determined that the signal has arrived. The calculation process subtracts the arrival time of the detected empty-mode signal from the pre-recorded zero-mode propagation start time mark. The result of the subtraction operation represents the total propagation time of the signal from transmission to reception. Since the empty-mode signal needs to propagate from the beginning of the line to the fault point and then back to the beginning, this time difference reflects the total time of the signal's round-trip propagation, thus obtaining the total empty-mode return time. This time includes the propagation delay of the signal in each line segment and the reflection delay at the fault point.

[0131] The data processing of segmented propagation time decomposition of the segmented zero-mode propagation parameter matrix involves solving complex linear equations. The segmented zero-mode propagation parameter matrix includes parameters such as propagation velocity, wave impedance, and reflection coefficient of each line segment. The segmented propagation time decomposition process establishes a mathematical model of propagation time based on the segmented structure of the hybrid line. This model expresses the total empty-mode return time as the sum of the round-trip propagation times of each line segment. The decomposition process first determines the signal propagation path based on the line topology. The propagation path starts from the beginning of the line, passes through each line segment sequentially to reach the fault point, and then returns to the beginning along the same path. The processing algorithm is performed for each line... A propagation time equation is established for each segment. The equation is in the form that the propagation time of the segment is equal to the length of the segment divided by the propagation speed of the segment. Since the location of the fault point is unknown, the fault distance needs to be introduced as a variable. The propagation time equations of all line segments are combined into a system of linear equations. The unknowns of the system of equations include the line segment where the fault is located and the specific location of the fault within that segment. The solution process uses an iterative algorithm to search for the fault location segment by segment. The algorithm assumes that the fault is located within a certain line segment and calculates the theoretical propagation time under this assumption. The theoretical time is compared with the total time of the measured empty mode return. When the difference between the two is the smallest, the corresponding assumption is the correct fault location, and the propagation time components of each line segment are obtained.

[0132] The data processing steps for distance inversion calculation of the propagation time components of each line segment, based on the zero-mode propagation velocities of overhead and cable segments, employ a linear relationship between propagation time and distance. Distance inversion calculation is the core algorithm of the time-based ranging method. Based on the physical relationship that distance equals velocity multiplied by time, the inversion calculation multiplies the propagation time component of each line segment by its corresponding propagation velocity to obtain the propagation distance of that segment. The calculation process distinguishes between the different propagation characteristics of overhead and cable segments: the propagation distance of an overhead segment equals the propagation time component multiplied by the zero-mode propagation velocity of the overhead segment, and the propagation distance of a cable segment equals the propagation time component multiplied by the zero-mode propagation velocity of the cable segment. The zero-mode propagation speed of the cable segment is also considered in the processing algorithm, which takes into account the differences in the propagation characteristics of the signal in different media. The air medium around the overhead line has a low dielectric constant, resulting in a high propagation speed, while the solid insulation medium in the cable has a high dielectric constant, resulting in a low propagation speed. The inversion calculation process accumulates the propagation distance of each segment according to the spatial order of the line. The accumulation process starts from the starting point of the line and adds the length of each segment in turn. When the accumulated distance reaches the segment where the fault is located, the distance to the fault point is equal to the accumulated value of the lengths of the previous segments plus the distance of the fault within that segment, thus obtaining the segmented fault distance value. This value represents the total distance from the fault point to the starting point of the line.

[0133] The data processing procedure, which involves spatial coordinate interpolation of segmented fault distance values ​​with the route geographic information database, converts one-dimensional distance information into three-dimensional geographic coordinates. The route geographic information database contains detailed GPS coordinate information of the route path, indexed by route mileage, and records the longitude, latitude, and altitude information of each key point. Spatial coordinate interpolation searches for two adjacent coordinate points in the database based on the segmented fault distance values. The search algorithm determines which two known coordinate points the fault point is located between by comparing the fault distance with the mileage data in the database. Linear interpolation calculates the precise coordinates of the fault point using a linear interpolation method. Linear interpolation assumes a linear relationship between the coordinate changes of two known points. The interpolation formula calculates the coordinate value based on the distance ratio between the fault point and the two known points. Longitude interpolation equals the longitude of the starting point plus the distance ratio multiplied by the longitude difference. Latitude and altitude interpolation use the same calculation method. The interpolation process also considers the influence of the Earth's curvature on large-distance interpolation. When the two known points are far apart, spherical interpolation replaces planar linear interpolation. Spherical interpolation calculates the interpolated coordinates between two points on a sphere based on the great circle arc length formula, obtaining the planar coordinates and altitude coordinates of the fault point.

[0134] The data processing procedure for accurate correction of the plane and elevation coordinates of the fault point using the temperature compensation coefficient considers the influence of ambient temperature on signal propagation speed. The temperature compensation coefficient is a correction parameter describing the relationship between propagation speed and temperature. This coefficient is determined based on the temperature characteristics of electromagnetic waves in different media. The accuracy correction process first acquires the ambient temperature data at the time of the fault. Temperature data is collected in real time by temperature sensors installed on power distribution equipment or obtained from meteorological departments regarding the temperature of the fault area. The correction process calculates the actual propagation speed correction value based on the temperature data. The correction formula is: actual propagation speed equals standard propagation speed multiplied by one plus temperature coefficient multiplied by temperature difference. Temperature difference equals actual temperature minus standard temperature. The standard temperature is usually set to 20 degrees Celsius. The correction process recalculates the fault distance using the corrected propagation speed. The recalculated distance is more accurate than the original calculated distance. The processing algorithm reflects the distance correction value in the coordinate calculation and corrects the coordinate position of the fault point by adjusting the interpolation parameters. The corrected coordinates are closer to the true location of the fault point, resulting in accurate three-dimensional fault coordinates after temperature compensation. These coordinates include corrected longitude, latitude, and elevation information.

[0135] The above describes the distribution line fault location method based on traveling wave ranging in the embodiments of this application. The following describes the distribution line fault location system based on traveling wave ranging in the embodiments of this application. Please refer to [link to relevant documentation]. Figure 2 One embodiment of the power distribution line fault location system based on traveling wave ranging in this application includes:

[0136] The injection module is used to perform zero-mode pulse injection processing on the power distribution line through a charged pulse coupler to obtain a charged zero-mode traveling wave signal.

[0137] The analysis module is used to perform wave velocity layer analysis on the hybrid line impedance nodes based on the charged zero-mode traveling wave signal to obtain the segmented zero-mode propagation parameter matrix.

[0138] The conversion module is used to perform mode coupling conversion processing on the charged zero-mode traveling wave signal through the fault asymmetry point to obtain the fault-excited empty-mode echo;

[0139] The filtering module is used to perform reflection source filtering on the fault excitation empty mode echo using a frequency domain waveform fingerprinting algorithm to obtain a clean fault location empty mode signal.

[0140] The mapping module is used to perform inverse time-distance mapping processing on the segmented zero-mode propagation parameter matrix based on the pure fault location empty mode signal to obtain three-dimensional fault coordinates.

[0141] above Figure 2The traveling wave ranging-based power distribution line fault location system in this embodiment of the invention is described in detail from the perspective of modular functional entities. The traveling wave ranging-based power distribution line fault location device in this embodiment of the invention is described in detail from the perspective of hardware processing.

[0142] Reference Figure 3 This invention also provides a power distribution line fault location device based on traveling wave ranging. This device can be a server, and its internal structure can be as follows: Figure 3 As shown, the traveling wave ranging-based power line fault location device includes a processor, memory, display screen, input device, network interface, and database connected via a system bus. The processor, designed as a computer, provides computational and control capabilities. The memory of the traveling wave ranging-based power line fault location device includes a non-volatile storage medium and internal memory. The non-volatile storage medium stores the operating system, computer programs, and database. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage medium. The database of the traveling wave ranging-based power line fault location device stores the data corresponding to this embodiment. The network interface of the traveling wave ranging-based power line fault location device is used for communication with external terminals via a network connection. When the computer program is executed by the processor, it implements the above-described method.

[0143] Those skilled in the art will understand that Figure 3 The structure shown is merely a block diagram of a portion of the structure related to the present invention and does not constitute a limitation on the fault location device for power distribution lines based on traveling wave ranging applied thereto.

[0144] The present invention also provides a computer-readable storage medium, which can be a non-volatile computer-readable storage medium or a volatile computer-readable storage medium, wherein the computer-readable storage medium stores instructions that, when the instructions are executed on a computer, cause the computer to perform the steps of the power distribution line fault location method based on traveling wave ranging.

[0145] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working processes of the systems and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here.

[0146] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a power distribution line fault location device based on traveling wave ranging (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present invention. 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.

[0147] The above embodiments are only used to illustrate the technical solutions of the present invention, and are not intended to limit it. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for fault location in power distribution lines based on traveling wave ranging, characterized in that, The method includes: A zero-mode traveling wave signal is obtained by performing zero-mode pulse injection processing on the power distribution line using a charged pulse coupler. Based on the charged zero-mode traveling wave signal, wave velocity layering analysis is performed on the impedance nodes of the hybrid line to obtain a segmented zero-mode propagation parameter matrix. This includes: identifying impedance abrupt change points at the overhead line-cable connection point based on line topology information to obtain the location coordinates of the impedance nodes; calculating wave impedance for different dielectric segments based on the charged zero-mode traveling wave signal to obtain the zero-mode wave impedance values ​​of the overhead line segment and the cable segment; solving for the reflection coefficients of the impedance node location coordinates based on the zero-mode wave impedance values ​​of the overhead line segment and the cable segment to obtain the forward reflection coefficient and the reverse reflection coefficient; calibrating the propagation speed of each line segment based on the electromagnetic properties of the dielectric to obtain the zero-mode propagation speed of the overhead line segment and the cable segment; and combining the zero-mode wave impedance values, forward reflection coefficient, reverse reflection coefficient, and zero-mode propagation speed to construct a matrix to obtain the segmented zero-mode propagation parameter matrix. The charged zero-mode traveling wave signal is processed by mode coupling conversion through the fault asymmetry point to obtain the fault-excited empty-mode echo. A frequency domain waveform fingerprinting algorithm is used to filter the reflection sources of the fault excitation empty mode echo to obtain a clean fault location empty mode signal. Based on the pure fault location empty mode signal, the segmented zero-mode propagation parameter matrix is ​​subjected to inverse time-distance mapping processing to obtain three-dimensional fault coordinates. This includes: calculating the time difference between the pure fault location empty mode signal and the zero-mode propagation start time marker to obtain the total empty mode return time; performing segmented propagation time decomposition processing on the segmented zero-mode propagation parameter matrix based on the total empty mode return time to obtain the propagation time components of each line segment; performing distance inversion calculation processing on the zero-mode propagation velocity of the overhead line segment and the zero-mode propagation velocity of the cable segment according to the propagation time components of each line segment to obtain the segmented fault distance value; performing spatial coordinate interpolation processing on the segmented fault distance value and the line geographic information database to obtain the plane coordinates and elevation coordinates of the fault point; and performing accuracy correction processing on the plane coordinates and elevation coordinates of the fault point based on the temperature compensation coefficient to obtain the three-dimensional fault coordinates.

2. The method for fault location of power distribution lines based on traveling wave ranging according to claim 1, characterized in that, The process of injecting zero-mode pulses into the power distribution line using a charged pulse coupler to obtain a charged zero-mode traveling wave signal includes: The GPS synchronization clock signal is input into a pulse generator for timing calibration to obtain a synchronization reference time scale. Based on the aforementioned synchronization reference time scale, the amplitude of the 500kHz square wave pulse is modulated to obtain a 5kV standard injection pulse. The 5kV standard injection pulse is processed by in-phase injection through a three-way coupling capacitor circuit to obtain a three-phase synchronous pulse signal. The three-phase synchronous pulse signal is subjected to symmetrical component transformation to obtain the charged zero-mode traveling wave signal; The zero-mode traveling wave signal is processed to initiate its propagation based on the zero-mode impedance matching principle, thus obtaining a zero-mode propagation initiation time marker.

3. The method for fault location of power distribution lines based on traveling wave ranging according to claim 1, characterized in that, The step of performing mode coupling conversion processing on the charged zero-mode traveling wave signal through the fault asymmetry point to obtain the fault-excited empty-mode echo includes: Based on the characteristics of single-wire grounding faults, the fault point is subjected to three-phase asymmetrical structure identification processing to obtain asymmetrical fault nodes. The charged zero-mode traveling wave signal is propagated to the asymmetric fault node for mode conversion efficiency calculation to obtain the zero-mode-empty-mode coupling conversion coefficient. The charged zero-mode traveling wave signal is subjected to mode decomposition processing based on the zero-mode to empty-mode coupling conversion coefficient to obtain the transmitted zero-mode component and the converted empty-mode component. Based on the fault resistance characteristics, the converted empty mode component is subjected to reflection intensity modulation processing to obtain the fault-modulated empty mode signal. The fault-modulated empty-mode signal is transmitted back along the line to obtain the fault-excited empty-mode echo.

4. The method for fault location of power distribution lines based on traveling wave ranging according to claim 1, characterized in that, The step of using a frequency domain waveform fingerprinting algorithm to filter the reflection sources of the fault-excited empty-mode echo to obtain a clean fault location empty-mode signal includes: The fault-excited empty-mode echo input wavelet transform is subjected to time-frequency domain decomposition to obtain a multi-scale spectral feature matrix. Based on the multi-scale spectral feature matrix, frequency domain fingerprinting is performed on each reflected wave component to obtain the fingerprints of overhead line connection points, cable connection points, branch lines, and fault points. Based on a preset reflection source feature library, pattern matching processing is performed on the fingerprints of overhead line connection points, cable connection points, branch lines, and fault points to obtain a reflection source type identifier vector. Based on the reflection source type identifier vector, the fault excitation empty mode echo is classified and filtered to obtain the fault source empty mode component and the non-fault source empty mode component. The fault source empty mode component is filtered and purified to obtain the pure fault location empty mode signal.

5. The method for fault location of power distribution lines based on traveling wave ranging according to claim 4, characterized in that, The process of performing pattern matching on the fingerprints of overhead line connection points, cable connection points, branch lines, and fault points based on a preset reflection source feature library yields a reflection source type identifier vector, including: The fingerprint of the overhead line connection point is input into the correlation calculator and subjected to unipolar feature matching to obtain the similarity value of the overhead line connection point. Based on the cable connection point fingerprint, waveform comparison processing is performed on the bipolar reflection features to obtain the cable connection point similarity value. Based on the branch line fingerprint, the amplitude of the high impedance reflection feature is compared to obtain the branch line similarity value. The fault point fingerprint is matched with a preset spectrum range in the frequency domain to obtain the fault point similarity value. Based on the similarity values ​​of the overhead line connection points, cable connection points, branch lines, and fault points, vector combination processing is performed to obtain the reflection source type identifier vector.

6. A power distribution line fault location system based on traveling wave ranging, characterized in that, For implementing the distribution line fault location method based on traveling wave ranging as described in any one of claims 1 to 5, the distribution line fault location system based on traveling wave ranging comprises: The injection module is used to perform zero-mode pulse injection processing on the power distribution line through a charged pulse coupler to obtain a charged zero-mode traveling wave signal. The analysis module is used to perform wave velocity layer analysis on the hybrid line impedance nodes based on the charged zero-mode traveling wave signal to obtain the segmented zero-mode propagation parameter matrix. The conversion module is used to perform mode coupling conversion processing on the charged zero-mode traveling wave signal through the fault asymmetry point to obtain the fault-excited empty-mode echo; The filtering module is used to perform reflection source filtering on the fault excitation empty mode echo using a frequency domain waveform fingerprinting algorithm to obtain a clean fault location empty mode signal. The mapping module is used to perform inverse time-distance mapping processing on the segmented zero-mode propagation parameter matrix based on the pure fault location empty mode signal to obtain three-dimensional fault coordinates.

7. A fault location device for power distribution lines based on traveling wave ranging, characterized in that, The method includes a memory and a processor, wherein the memory stores a computer program that can run on the processor, and the processor executes the computer program to implement the power distribution line fault location method based on traveling wave ranging as described in any one of claims 1 to 6.

8. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is run by the processor, it causes the processor to execute the power distribution line fault location method based on traveling wave ranging as described in any one of claims 1 to 6.

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