Voltage and current traveling wave combined fault positioning method, system, equipment and medium

Abstract

The invention provides a voltage and current traveling wave combined fault positioning method, system and device and a medium, and the method comprises the steps: carrying out the traveling wave data collection of a faulted power transmission line through a broadband current and voltage transformer, and obtaining a plurality of current traveling wave signals and a plurality of voltage traveling wave signals; performing multi-scale feature analysis and multi-channel correlation analysis on the multiple paths of current traveling wave signals and the multiple paths of voltage traveling wave signals to obtain a traveling wave head candidate point set; adopting a dynamic selection mechanism to screen out a traveling wave head confirmation point from the traveling wave head candidate point set; and analyzing the traveling wave head confirmation point by adopting a double-end distance measurement algorithm to obtain position information of a fault point in the faulted power transmission line. According to the invention, the fault point in the power transmission line with the fault can be accurately positioned.

Description

Technical Field

[0001] This invention relates to the field of power system fault detection, specifically to a fault location method, system, device, and medium that combines voltage and current traveling waves. Background Technology

[0002] In the operation of power systems, rapid and accurate location of transmission line faults is crucial for ensuring power supply reliability and reducing power outage losses. Among related technologies, ranging methods are commonly used to determine the location of fault points in transmission lines. However, traditional ranging methods, such as those based on power frequency electrical quantities, are significantly affected by factors such as fault resistance and changes in line parameters, making it difficult to meet the accuracy and speed requirements of modern power systems. In recent years, traveling wave ranging technology has emerged as a research hotspot because it is theoretically unaffected by line type, fault resistance, and the systems on either side, offering higher ranging accuracy and faster response speed.

[0003] Meanwhile, existing traveling wave ranging technology still has some shortcomings, such as: the traveling wave signal on the line during a fault has a short duration and high frequency, while the cutoff frequency of traditional instrument transformers is low and cannot meet the requirements, resulting in severe distortion of the acquired traveling wave signal; and the traveling wave is affected by factors such as line loss, refraction, reflection and noise interference during propagation, which increases the difficulty of wavefront identification and makes it easy to make misjudgments, thus making it difficult to accurately locate the fault point in the transmission line. Summary of the Invention

[0004] To address the problems of existing technologies, this invention proposes a fault location method, system, device, and medium that combines voltage, current, and traveling wave, aiming to accurately locate the fault point in a transmission line where a fault has occurred.

[0005] The objective of this invention is achieved through the following technical solution: On one hand, embodiments of the present invention provide a fault location method combining voltage and current traveling waves, the method comprising: Wideband current and voltage transformers are used to collect traveling wave data of the faulted transmission line, and obtain multiple current traveling wave signals and multiple voltage traveling wave signals. Multi-scale feature analysis and multi-channel correlation analysis are performed on the multi-channel current traveling wave signal and the multi-channel voltage traveling wave signal to obtain a set of candidate points for traveling wave fronts; A dynamic selection mechanism is used to screen travel wave head confirmation points from the set of travel wave head candidate points; A dual-end ranging algorithm is used to analyze the traveling wave front confirmation point to obtain the location information of the fault point in the transmission line where the fault occurred.

[0006] Optionally, the step of employing a dynamic selection mechanism to filter travel wavefront confirmation points from the travel wavefront candidate point set includes: In the candidate set of traveling wavefronts, a set of undetermined traveling wavefronts that meet the wavefront confirmation mechanism is selected; If, based on the timestamps carried by the undetermined points of the traveling wave wavefront, the corresponding midpoints of the traveling wave wavefronts with amplitudes greater than or equal to the initial threshold are sequentially selected from the set of undetermined points of the traveling wave wavefront, then the selection is stopped and the midpoints of the traveling wave wavefronts are confirmed as the confirmed points of the traveling wave wavefronts. Otherwise, based on the noise level of the set of undetermined traveling wave front points and the distribution of the undetermined traveling wave front points within the set, the initial threshold is updated to obtain an updated threshold. The updated threshold is then used to re-filter the set of undetermined traveling wave front points until the corresponding traveling wave front confirmation points with amplitudes greater than or equal to the updated threshold are selected in sequence.

[0007] Optionally, the process of determining the initial threshold includes: The mean and standard deviation of the wavefront amplitude of historical traveling wave signals in the transmission channel are obtained; wherein, the transmission channel is the channel for transmitting traveling wave signals in the transmission line; The median value is obtained by multiplying the standard deviation by the adjustable coefficient. The initial threshold is obtained by summing the mean and the median.

[0008] Optionally, updating the initial threshold based on the noise level of the set of undetermined traveling wavefront points and the distribution of the undetermined traveling wavefront points within the set, to obtain an updated threshold, includes: The standard deviation of the amplitude of the undetermined points of the traveling wave front within the set of undetermined points of the traveling wave front is calculated to obtain the standard evaluation deviation characterizing the noise level of the set of undetermined points of the traveling wave front; The density of the travel wavefront undetermined points in the set of undetermined travel wavefronts is measured to obtain a density parameter characterizing the distribution of the travel wavefront undetermined points in the set of undetermined travel wavefronts. The feature fusion value is obtained by fusing the standard evaluation difference and the density parameter using a specific weighting formula; The updated threshold is obtained by multiplying the feature fusion value by the initial threshold.

[0009] Optionally, the step of performing multi-scale feature analysis and multi-channel correlation analysis on the multi-channel current traveling wave signals and the multi-channel voltage traveling wave signals to obtain a candidate set of traveling wave fronts includes: The multi-channel current traveling wave signal and the multi-channel voltage traveling wave signal are respectively converted from analog to digital to obtain multi-channel current digital waveform data and multi-channel voltage digital waveform data; The timestamps of the multi-channel current digital waveform data and the multi-channel voltage digital waveform data are calibrated using the second pulse signal output by the Global Positioning System (GPS) to obtain time-aligned multi-channel current digital signals and multi-channel voltage digital signals. Multi-scale feature analysis and multi-channel correlation analysis are performed on the multi-channel current digital signal and the multi-channel voltage digital signal to obtain the candidate point set of the traveling wave front.

[0010] Optionally, the multi-scale feature analysis includes: wavelet transform, modulus maxima detection, feature selection, and morphological filtering; The process of performing multi-scale feature analysis and multi-channel correlation analysis on the multi-channel current digital signals and the multi-channel voltage digital signals to obtain the candidate set of traveling wavefronts includes: Wavelet transform and modulus maxima detection are performed on the multi-channel current digital signal and the multi-channel voltage digital signal respectively to obtain the current wavefront midpoint set and the voltage wavefront midpoint set. Using current feature thresholds, feature filtering is performed on the current wavefront midpoint set and the feature set of the multi-channel current digital signal, respectively, to obtain a current wavefront filtering set and a current feature filtering set. The current feature filtering set is then merged into the current wavefront filtering set to obtain the effective current wavefront point set. Using voltage feature thresholds, feature filtering is performed on the voltage wavefront midpoint set and the feature set of the multi-channel voltage digital signal, respectively, to obtain a voltage wavefront filtering set and a voltage feature filtering set. The voltage feature filtering set is then merged into the voltage wavefront filtering set to obtain the effective voltage wavefront point set. Morphological filtering is performed on the effective point set of the current wavefront and the effective point set of the voltage wavefront respectively to obtain the candidate point set of the current wavefront and the candidate point set of the voltage wavefront. Multi-channel correlation analysis is then performed on the candidate point set of the current wavefront and the candidate point set of the voltage wavefront to obtain the candidate point set of the traveling wavefront.

[0011] Optionally, the faulty transmission line includes: an A-end monitoring device and a B-end monitoring device. A dual-end ranging algorithm is used to analyze the traveling wave front confirmation point to obtain the location information of the fault point in the faulty transmission line, including: The time difference between the two ends is obtained by comparing the time when the traveling wave wavefront confirmation point is detected by the monitoring device at end A with the time when the traveling wave wavefront confirmation point is detected by the monitoring device at end B. The distance from the fault point to the monitoring device at end A is calculated by substituting the time difference between the two ends, the line length between the monitoring device at end A and the monitoring device at end B, the wave velocity, and the current temperature into the two-end traveling wave ranging formula. Based on the location information of the monitoring device at end A and the distance, the fault point is mapped to geographic coordinates to obtain the location information of the fault point.

[0012] On the other hand, embodiments of the present invention also provide a fault location system combining voltage and current traveling waves, the system comprising: The data acquisition module is used to acquire traveling wave data of the faulty transmission line using a wideband current and voltage transformer, and obtain multiple current traveling wave signals and multiple voltage traveling wave signals. The first analysis module is used to perform multi-scale feature analysis and multi-channel correlation analysis on the multi-channel current traveling wave signal and the multi-channel voltage traveling wave signal to obtain a set of candidate points for the traveling wave front; The filtering module is used to filter out travel wave head confirmation points from the travel wave head candidate point set using a dynamic selection mechanism; The second analysis module is used to analyze the traveling wave front confirmation point using a dual-end ranging algorithm to obtain the location information of the fault point in the transmission line where the fault occurred.

[0013] Optionally, the filtering module includes: The first screening unit is used to screen the set of undetermined traveling wavefront points that meet the wavefront confirmation mechanism from the set of candidate traveling wavefront points. The second filtering unit is used to stop filtering and confirm the midpoint of the traveling wave head as the confirmed point if, based on the timestamp carried by the traveling wave head undetermined point in the set of traveling wave head undetermined points, the corresponding traveling wave head midpoint with an amplitude greater than or equal to the initial threshold is selected in sequence. Otherwise, based on the noise level of the set of undetermined traveling wave front points and the distribution of the undetermined traveling wave front points within the set, the initial threshold is updated to obtain an updated threshold. The updated threshold is then used to re-filter the set of undetermined traveling wave front points until the corresponding traveling wave front confirmation points with amplitudes greater than or equal to the updated threshold are selected in sequence.

[0014] Optionally, the filtering module further includes: A determining unit is used to obtain the mean and standard deviation of the wavefront amplitude of historical traveling wave signals in the transmission channel; wherein, the transmission channel is the channel for transmitting traveling wave signals in the transmission line; an intermediate value is obtained by multiplying the standard deviation by the adjustable coefficient; and an initial threshold is obtained by summing the mean and the intermediate value.

[0015] Optionally, the second filtering unit is specifically used to calculate the standard deviation of the amplitude of the undetermined points of the traveling wave front within the set of undetermined traveling wave fronts to obtain a standard evaluation deviation characterizing the noise level of the set of undetermined traveling wave fronts; measure the density of the undetermined traveling wave fronts within the set of undetermined traveling wave fronts to obtain a density parameter characterizing the distribution of the undetermined traveling wave fronts within the set of undetermined traveling wave fronts; fuse the standard evaluation deviation and the density parameter using a specific weighting formula to obtain a feature fusion value; and obtain the updated threshold by multiplying the feature fusion value by the initial threshold.

[0016] Optional, the first analysis module includes: An analog-to-digital conversion unit is used to perform analog-to-digital conversion on the multi-channel current traveling wave signal and the multi-channel voltage traveling wave signal respectively to obtain multi-channel current digital waveform data and multi-channel voltage digital waveform data. The calibration unit is used to calibrate the timestamps of the multi-channel current digital waveform data and the multi-channel voltage digital waveform data using the second pulse signal output by the Global Positioning System (GPS), so as to obtain time-aligned multi-channel current digital signals and multi-channel voltage digital signals. The analysis unit is used to perform multi-scale feature analysis and multi-channel correlation analysis on the multi-channel current digital signal and the multi-channel voltage digital signal to obtain the candidate point set of the traveling wave front.

[0017] Optionally, the multi-scale feature analysis includes: wavelet transform, modulus maxima detection, feature filtering, and morphological filtering; the analysis unit is specifically used to sequentially perform wavelet transform and modulus maxima detection on the multi-channel current digital signals and the multi-channel voltage digital signals to obtain a set of current wavefront midpoints and a set of voltage wavefront midpoints; using a current feature threshold, feature filtering is performed on the feature sets of the current wavefront midpoints and the multi-channel current digital signals to obtain a current wavefront filter set and a current feature filter set, and the current feature filter set is merged into the current wavefront filter set to obtain the current... Effective wavefront point set; using voltage feature thresholds, feature filtering is performed on the voltage wavefront intermediate point set and the feature set of the multi-channel voltage digital signal to obtain a voltage wavefront filter set and a voltage feature filter set, and the voltage feature filter set is merged into the voltage wavefront filter set to obtain the effective wavefront point set; morphological filtering is performed on the effective wavefront point set and the effective wavefront point set of the voltage wavefront to obtain a current wavefront candidate point set and a voltage wavefront candidate point set, and multi-channel correlation analysis is performed on the current wavefront candidate point set and the voltage wavefront candidate point set to obtain the traveling wave wavefront candidate point set.

[0018] Optionally, the faulty transmission line includes: an A-end monitoring device and a B-end monitoring device. The second analysis module is specifically used to obtain the time difference between the time when the A-end monitoring device detects the traveling wave front confirmation point and the time when the B-end monitoring device detects the traveling wave front confirmation point, and then to calculate the distance from the fault point to the A-end monitoring device by substituting the time difference, the line length between the A-end monitoring device and the B-end monitoring device, the wave velocity, and the current temperature into the two-end traveling wave ranging formula; and finally, to perform geographic coordinate mapping on the fault point based on the location information of the A-end monitoring device and the distance, thereby obtaining the location information of the fault point.

[0019] In another aspect, embodiments of the present invention also provide an electronic device, comprising: at least one processor and a memory; the memory and the processor are connected via a bus; The memory is used to store one or more programs; When the one or more programs are executed by the at least one processor, the fault location method combining voltage and current traveling waves as described above is implemented.

[0020] Correspondingly, embodiments of the present invention also provide a readable storage medium having an executable program stored thereon, wherein when the executable program is executed, it implements the fault location method combining voltage and current traveling waves as described in any of the preceding claims.

[0021] Compared with the prior art, the beneficial effects of the present invention are as follows: This invention provides a fault location method, system, device, and medium that combines voltage and current traveling wave signals. In the execution of this method, firstly, multi-scale feature analysis and multi-channel correlation analysis are performed on the acquired multi-channel current traveling wave signals and multi-channel voltage traveling wave signals. This enables timely and effective identification of candidate traveling wave fronts, providing parameter support for subsequent accurate positioning of the traveling wave fronts. Secondly, filtering is performed based on a dynamically adjustable threshold, unlike traditional fixed threshold methods which are prone to missed or false detections. This ensures a balance between sensitivity and accuracy in traveling wave front identification, accurately identifying both weak and strong traveling waves. This allows for precise location of the fault point in the transmission line based on the accurately identified traveling wave front confirmation point.

[0022] It should be understood that the above general description and the following detailed description are exemplary and explanatory only, and are not intended to limit the technical solutions provided in the embodiments of the present invention. Attached Figure Description

[0023] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort, wherein: Figure 1 A schematic flowchart illustrating a fault location method combining voltage and current traveling waves provided in an embodiment of the present invention; Figure 2 This is a schematic diagram of a process for acquiring multiple current traveling wave signals and multiple voltage traveling wave signals, provided in an embodiment of the present invention. Figure 3 This is a schematic flowchart illustrating the data alignment of multiple current digital waveform data and multiple voltage digital waveform data according to an embodiment of the present invention. Figure 4 This is a schematic diagram of a process for obtaining a candidate set of traveling wavefronts according to an embodiment of the present invention; Figure 5 This is a schematic diagram of a process for selecting travel wave head confirmation points from a set of travel wave head candidate points, provided by an embodiment of the present invention. Figure 6 This is a flowchart illustrating the process of determining the location information of a fault point using a dual-end ranging algorithm, as provided in an embodiment of the present invention. Figure 7 This is a schematic diagram of the functional framework of the system in which the fault location method combining voltage and current traveling waves provided in the embodiments of the present invention is located; Figure 8 A flowchart illustrating the fault location method combining voltage and current traveling waves provided in this embodiment of the invention in the corresponding system. Figure 9 A schematic diagram of the composition of a fault location system combining voltage and current traveling waves provided in an embodiment of the present invention; Figure 10 This is a schematic diagram of the composition of an electronic device provided in an embodiment of the present invention. Detailed Implementation

[0024] The embodiments of the present invention will be described below with reference to the accompanying drawings and preferred embodiments. Those skilled in the art can easily understand other advantages and effects of the present invention from the content disclosed in this specification. The present invention can also be implemented or applied through other different specific embodiments, and various details in this specification can also be modified or changed based on different viewpoints and applications without departing from the spirit of the present invention. It should be understood that the preferred embodiments are only for illustrating the present invention and not for limiting the scope of protection of the present invention.

[0025] In the following description, references are made to “some embodiments,” which describe a subset of all possible embodiments. However, it is understood that “some embodiments” may be the same subset or different subsets of all possible embodiments and may be combined with each other without conflict.

[0026] In the following description, the terms "first, second, third" are used merely to distinguish similar objects and do not represent a specific ordering of objects. It is understood that "first, second, third" may be interchanged in a specific order or sequence where permitted, so that the embodiments of the invention described herein can be implemented in an order other than that illustrated or described herein.

[0027] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which embodiments of the invention pertain. The terminology used herein is for descriptive purposes only and is not intended to limit the scope of the invention.

[0028] Example 1: This invention provides a fault location method combining voltage and current traveling waves, such as... Figure 1 As shown, the method includes the following steps: Step 101: Using wideband current and voltage transformers, travel wave data is collected from the faulty transmission line to obtain multiple current travel wave signals and multiple voltage travel wave signals.

[0029] In some embodiments of the present invention, the broadband current and voltage transformer can be a specially customized broadband current and voltage transformer with a corresponding frequency response range of 1Hz to 10MHz; in this way, the electrical purity of the acquired multi-channel current traveling wave signal and multi-channel voltage traveling wave signal in the signal transmission path can be ensured, so that the subsequent back-end precision processing circuit is protected from strong electric shock and stray electromagnetic interference.

[0030] The faulty transmission line can be an overhead transmission line and / or a cable line, and this invention does not limit it in any way.

[0031] In some embodiments of the present invention, firstly, traveling wave data of the faulted transmission line is acquired using a wideband current and voltage transformer to obtain initial current traveling wave signals and initial voltage traveling wave signals. Then, a bandpass filter composed of a low-noise, high-bandwidth operational amplifier (whose input voltage noise density unit can be as low as 1nV / √Hz) is selected to filter the obtained initial current and initial voltage traveling wave signals to obtain multiple current and voltage traveling wave signals. This ensures that even weak traveling wave initiation signals at the millivolt or even microvolt level can be accurately amplified, allowing a bandwidth of up to 10MHz to fully preserve the high-frequency components in the multiple current and voltage traveling wave signals. This enables subsequent analysis to obtain rich signal details and accurately reconstruct the original waveform of the faulted traveling wave.

[0032] In some embodiments of the present invention, reference is made to Figure 2 As shown, for the faulty transmission line 201, a broadband instrument transformer group 202 (i.e., the broadband current and voltage transformers shown above) can be deployed on it, which can be split into current transformers and voltage transformers. In this way, traveling wave data can be collected from the faulty transmission line 201 by means of the split current transformers and voltage transformers respectively, thereby obtaining the initial current traveling wave signal (IA / IB / IC / I0) and the initial voltage traveling wave signal (UA / UB / UC / U0) shown in 203, where I0 is the zero-sequence current and U0 is the zero-sequence voltage; at the same time, the signal frequency range corresponding to the initial current traveling wave signal and the initial voltage traveling wave signal is 1Hz-10MHz, and the duration is in the microsecond range. Furthermore, the initial current traveling wave signal (IA / IB / IC / I0) and the initial voltage traveling wave signal (UA / UB / UC / U0) acquired by 203 can be processed by the current channel processing and voltage channel processing shown in 204, which are composed of bandpass filtering and differential circuits respectively, to obtain the multi-channel current traveling wave signal and multi-channel voltage traveling wave signal stored in the data buffer of the core microcontroller unit (MCU) shown in 205.

[0033] It should be noted that digital-to-analog conversion can also be performed on the multi-channel current traveling wave signal and multi-channel voltage traveling wave signal before storage, but this invention does not limit this.

[0034] Here, the multiple current traveling wave signals and the multiple voltage traveling wave signals can be stored in the corresponding buffer in the data format of 16-bit binary (0-16777215), and the present invention does not impose any limitations on this.

[0035] Step 102: Perform multi-scale feature analysis and multi-channel correlation analysis on the multi-channel current traveling wave signal and the multi-channel voltage traveling wave signal to obtain a set of candidate points for the traveling wave front.

[0036] In some embodiments of the present invention, the acquired multi-channel current traveling wave signals (indicated by I) can be processed. A I B I C (taking I0 as an example) and multiple voltage traveling wave signals (taking U as an example) A U B U C Taking U0 as an example, a comprehensive comparative analysis is conducted, namely, multi-scale feature analysis and multi-channel correlation analysis, so as to timely and effectively determine the candidate point set of the wave head, thereby providing strong parameter support for the subsequent accurate positioning of fault points in the transmission line.

[0037] In some embodiments of the present invention, multi-scale feature analysis can be performed on the multi-channel current traveling wave signal and the multi-channel voltage traveling wave signal to obtain the multi-channel intermediate current traveling wave signal and the multi-channel intermediate voltage traveling wave signal. Then, multi-channel correlation analysis can be performed on the multi-channel intermediate current traveling wave signal and the multi-channel intermediate voltage traveling wave signal to obtain the candidate point set of traveling wave wavefronts.

[0038] In some embodiments of the present invention, multi-scale feature analysis includes, but is not limited to, wavelet transform, modulus maxima detection, feature selection, and morphological filtering.

[0039] In some embodiments of the present invention, step 102 described above can be implemented by steps 1021 to 1023. Figure 1 (not shown in the image) Step 1021: Perform analog-to-digital conversion on the multi-channel current traveling wave signal and the multi-channel voltage traveling wave signal respectively to obtain multi-channel current digital waveform data and multi-channel voltage digital waveform data.

[0040] In some embodiments of the present invention, a 16-bit analog-to-digital converter (ADC) with a sampling rate of 5Msps can be used to perform analog-to-digital conversion on the acquired multi-channel current traveling wave signals and multi-channel voltage traveling wave signals to obtain multi-channel current digital waveform data and multi-channel voltage digital waveform data.

[0041] Step 1022: Using the second pulse signal output by the Global Positioning System (GPS), calibrate the timestamps of the multi-channel current digital waveform data and the multi-channel voltage digital waveform data to obtain time-aligned multi-channel current digital signals and multi-channel voltage digital signals.

[0042] In some embodiments of the present invention, the second pulse signal output by the Global Positioning System (GPS) is further used to calibrate the timestamps of the multi-channel current digital waveform data and the multi-channel voltage digital waveform data. Correspondingly, as shown below... Figure 3 As shown, the multi-channel current and voltage digital waveform data cached in the core MCU data buffer of 301 according to timestamp order can first be digitally filtered (execution 302). Then, the second pulse signal output by GPS (accuracy ≤50ns) is used to align the digitally filtered multi-channel current and voltage digital waveform data (execution 303) to calibrate the timestamps of each channel and eliminate the phase difference caused by sampling delay. The time offset between each channel can be calculated using existing algorithms, and corresponding phase compensation can be performed. Further, features (such as amplitude, slope, and energy) can be extracted from the obtained time-aligned multi-channel current and voltage digital signals (execution 304). Specifically, current features corresponding to the multi-channel current digital signals can be extracted, such as amplitude, rising edge slope, and energy integral; voltage features corresponding to the multi-channel voltage digital signals can be extracted, such as amplitude, falling edge slope, and harmonic content (which can be total harmonic distortion). The techniques used for feature extraction are all existing technologies and will not be elaborated here.

[0043] In this way, by performing time alignment and feature extraction on multi-channel current digital waveform data and multi-channel voltage digital waveform data, high-quality data support can be provided for subsequent wavefront identification.

[0044] Step 1023: Perform multi-scale feature analysis and multi-channel correlation analysis on the multi-channel current digital signal and the multi-channel voltage digital signal to obtain the candidate point set of the traveling wave front.

[0045] In some embodiments of the present invention, a wavefront recognition algorithm integrating wavelet transform, modulus maxima detection, morphological filtering, and multi-channel correlation analysis can be used to process multiple current digital signals and multiple voltage digital signals to obtain a set of traveling wavefront candidate points. The number of traveling wavefront candidate points included in the set can be determined according to actual needs, and the present invention does not impose any limitation on this.

[0046] In some embodiments of the present invention, such as Figure 4As shown, wavelet transform (402) is first applied to the multi-channel current digital signal and multi-channel voltage digital signal (401) respectively to decompose them into different scale spaces. Here, the multi-channel current digital signal and multi-channel voltage digital signal can be processed independently. Next, using the modulus maxima of the wavelet coefficients, feature filtering (403) is performed on the signals decomposed into different scale spaces. Then, morphological filtering (404) and multi-channel correlation analysis (405) are performed on the signal data obtained after feature filtering to determine the possible locations of the wavefronts, thus obtaining the traveling wavefront candidate point set (406). Here, by comparing and calculating the multi-channel current and voltage waveforms (multi-channel current digital signal and multi-channel voltage digital signal), the accuracy and reliability of wavefront identification can be effectively improved. Even in strong noise environments, traveling wavefront candidate points can be accurately identified for further screening.

[0047] It should be noted that wavelet transform is a mathematical tool used in signal and image processing, which can decompose a signal or image into multiple components of different frequencies. Furthermore, the wavelet coefficients obtained after wavelet transform can describe the characteristics of the signal or image at different frequencies and times.

[0048] In some embodiments of the present invention, when the multi-scale feature analysis includes wavelet transform, modulus maxima detection, feature selection, and morphological filtering, the above step 1023 can be implemented by the following steps A1 to A4: Step A1: Perform wavelet transform and modulus maxima detection on the multi-channel current digital signal and the multi-channel voltage digital signal respectively to obtain the current wavefront midpoint set and the voltage wavefront midpoint set.

[0049] In some embodiments of the present invention, firstly, wavelet transform is performed on the multiple current digital signals and the multiple voltage digital signals respectively to obtain a multi-level current wavelet coefficient set and a multi-level voltage wavelet coefficient set; then, modulus maxima detection is performed on the multi-level current wavelet coefficient set and the multi-level voltage wavelet coefficient set respectively to obtain a current wavefront midpoint set and a voltage wavefront midpoint set.

[0050] Here, wavelet transform is performed on multiple current digital signals. The corresponding current channels involve the wavelet basis db4 and the number of decomposition levels (taking 3 levels as an example, obtaining high-frequency components D1-D3, the frequency band is 1kHz-1MHz). The corresponding output is a multi-level set of current wavelet coefficients, i.e., current wavelet coefficients: 4 channels × 3 levels (D1-D3). Simultaneously, wavelet transform is performed on multiple voltage digital signals. The corresponding voltage channels involve the wavelet basis db6 and the number of decomposition levels (again, taking 3 levels as an example, obtaining high-frequency components D1-D3, the frequency band is 1kHz-1MHz). The corresponding output is a multi-level set of voltage wavelet coefficients, i.e., voltage wavelet coefficients: 4 channels × 3 levels (D1-D3). The specific wavelet transform descriptions here are existing techniques and will not be elaborated further.

[0051] Here, the obtained current wavelet coefficients and voltage wavelet coefficients can be subjected to modulus maxima detection to achieve the output of: current wavefront midpoint set (which may include: timestamp, channel number and wavelet coefficient amplitude) and voltage wavefront midpoint set (timestamp, channel number and wavelet coefficient amplitude), etc.

[0052] Step A2: Using current feature thresholds, feature filtering is performed on the current wavefront midpoint set and the feature set of the multi-channel current digital signal to obtain the current wavefront filtering set and the current feature filtering set. The current feature filtering set is then merged into the current wavefront filtering set to obtain the effective current wavefront point set.

[0053] Step A3: Using voltage feature thresholds, feature filtering is performed on the voltage wavefront intermediate point set and the feature set of the multi-channel voltage digital signal to obtain a voltage wavefront filtering set and a voltage feature filtering set. The voltage feature filtering set is then merged into the voltage wavefront filtering set to obtain the effective voltage wavefront point set.

[0054] In some embodiments of the present invention, the feature set of the multi-channel current digital signals may include, but is not limited to, the amplitude characteristics, rising edge slope, and energy integral of the multi-channel current digital signals; correspondingly, the feature set of the multi-channel voltage digital signals includes, but is not limited to, the amplitude characteristics, falling edge slope, and harmonic content of the multi-channel voltage digital signals. Correspondingly, the current feature thresholds include, but are not limited to, the current amplitude threshold, the current rising edge slope threshold, and the current energy integral threshold; the voltage feature thresholds include, but are not limited to, the voltage amplitude threshold, the voltage falling edge slope threshold, and the voltage harmonic content threshold. Here, the corresponding thresholds may include upper and lower limits. For example, the current amplitude threshold includes, but is not limited to, an upper current amplitude threshold and a lower current amplitude threshold.

[0055] In some embodiments of the present invention, the current characteristic threshold and voltage characteristic threshold can be determined based on historical operating data of the transmission line. For example, for a specific transmission line, the lower limit threshold for current amplitude is set to 1.5 times the minimum amplitude during normal operation, and the upper limit threshold is set to 3 times the maximum amplitude during normal operation; the lower limit threshold for current rise rate slope is set to 0.8 times the maximum rate of change of slope during normal operation; and the lower limit threshold for current energy integral is set to 2 times the average energy integral during normal operation. Here, voltage amplitude, fall rate slope, and other characteristics are also set with corresponding thresholds using the same method.

[0056] It should be noted that the feature sets of the multi-channel current digital signal and the multi-channel voltage digital signal can be obtained by feature extraction after obtaining the time-aligned multi-channel current digital signal and multi-channel voltage digital signal above.

[0057] In some embodiments of the present invention, the following description takes as examples the use of current characteristic thresholds to perform feature filtering on the set of intermediate points of current wavefronts to obtain a current wavefront selection set, and the use of voltage characteristic thresholds to perform feature filtering on the set of intermediate points of voltage wavefronts to obtain a voltage wavefront selection set: In the process of filtering each current wavefront midpoint from the current wavefront midpoint set using a current characteristic threshold, the first step is to check whether its amplitude, rise edge slope, and energy integral meet the set current characteristic threshold. If the amplitude I of the current wavefront midpoint... d If the current amplitude is greater than or equal to the lower threshold and less than or equal to the upper threshold, the rising edge slope (slopeI) is greater than or equal to the lower threshold, and the energy integral (EI) is greater than or equal to the lower threshold, then the midpoint of the current wavefront is initially retained; otherwise, it is marked for exclusion. Similarly, using voltage characteristic thresholds, for each midpoint in the voltage wavefront midpoint set, its amplitude, falling edge slope, and voltage harmonic content are judged to meet the requirements of the set voltage characteristic thresholds. When the amplitude U of the midpoint of the voltage wavefront... d Within the upper and lower threshold ranges of voltage amplitude, and when the slope U of the falling edge is greater than or equal to the lower threshold of voltage falling edge slope and the voltage harmonic content is less than or equal to the voltage harmonic content threshold, the midpoint of the voltage wavefront is initially retained; otherwise, it is marked as to be excluded.

[0058] Next, for the midpoints of the initially retained current and voltage wavefronts, their corresponding amplitude correlations can be calculated, that is, the ratio R=I between the current amplitude at the initially retained current wavefront midpoint and the voltage amplitude at the initially retained voltage wavefront midpoint can be calculated. d / U dThe ratio R is then compared with the range of amplitude ratios during normal operation in historical data (e.g., Rmin-Rmax). If Rmin < R < Rmax, the correlation score of the midpoint pair formed by the midpoints of the initially retained current and voltage wavefronts can be increased; if it exceeds the range, the correlation score is appropriately reduced according to the degree of exceedance.

[0059] Then, for the initially retained midpoints of the current and voltage wavefronts, analyze the changing trends of the slopes along the current rise and voltage fall. When the current rises and the voltage falls, and the slope changes satisfy a certain proportional relationship (e.g., slopeI / slopeU is within the empirical proportional range Kmin to Kmax), increase the correlation score of the midpoint pair formed by the initially retained midpoints of the current and voltage wavefronts; if not, decrease the correlation score according to the degree of deviation.

[0060] Finally, a comprehensive evaluation value is calculated for each pair of points formed by the midpoints of the current and voltage wavefronts, or the midpoints of the current and voltage wavefronts. Firstly, a weighted summation method can be used to assign weights to amplitude, slope, energy, and correlation: , , , (Here, the weights are determined using methods such as the analytic hierarchy process (AHP) based on the importance of each feature to fault diagnosis, and...) Correspondingly, the amplitude evaluation score and amplitude weight can be determined according to the following formula (1). Slope evaluation score, slope weight Energy assessment score, energy weight Relevance assessment score and relevance weight Calculations are performed to obtain a comprehensive evaluation value. : Formula (1); The amplitude assessment score is quantified based on the deviation of the current and voltage amplitudes from the threshold values; similarly, the slope, energy, and correlation assessment scores are calculated. Simultaneously, a threshold value for the comprehensive assessment is set. Only the comprehensive evaluation value Greater than or equal to Only the midpoint or a pair of midpoints of the wavefront are ultimately determined as valid current wavefront screening points or valid voltage wavefront screening points, thus forming the current wavefront screening set and voltage wavefront screening set respectively; otherwise, points smaller than [the specified value] are considered valid. The corresponding intermediate points are discarded.

[0061] In some embodiments of the present invention, the effective set of current wavefronts after comprehensive feature analysis and screening includes: a current feature screening set and a current wavefront screening set, which may further include the following information: timestamp, channel number, wavelet coefficient amplitude, and screened current features; correspondingly, the effective set of voltage wavefronts after comprehensive feature analysis and screening includes: a voltage feature screening set and a voltage wavefront screening set, which may further include the following information: timestamp, channel number, wavelet coefficient amplitude, and screened voltage features.

[0062] Step A4: Perform morphological filtering on the effective point set of the current wavefront and the effective point set of the voltage wavefront respectively to obtain the candidate point set of the current wavefront and the candidate point set of the voltage wavefront, and perform multi-channel correlation analysis on the candidate point set of the current wavefront and the candidate point set of the voltage wavefront to obtain the candidate point set of the traveling wavefront.

[0063] In some embodiments of the present invention, firstly, morphological filtering (including but not limited to: erosion operation to eliminate isolated noise points, expansion operation to merge neighboring candidate points) is performed on the effective point set of the current wavefront and the effective point set of the voltage wavefront, respectively, to obtain the candidate point set of the current wavefront and the candidate point set of the voltage wavefront; then, multi-channel correlation analysis is performed on the candidate point set of the current wavefront and the candidate point set of the voltage wavefront, wherein the correlation rules involved in the multi-channel correlation analysis include but are not limited to: the time difference between the current wavefront and the corresponding phase voltage wavefront is ≤5μs, and the zero-sequence wavefront (I0 / U0) has a higher priority than the phase wavefront, to obtain the candidate point set of the traveling wavefront.

[0064] It should be noted that the traveling wave wavehead candidate point set may include: timestamp, channel number, association flag, etc. of the traveling wave wavehead candidate point; correspondingly, the performance indicators of the traveling wave wavehead candidate points in this set may include: wavehead recognition rate ≥ 99.5% (when signal-to-noise ratio ≥ 10dB), false alarm rate ≤ 0.1% (based on morphological filtering), and processing time ≤ 15μs (single channel).

[0065] In this way, by extracting high-frequency features of traveling waves through wavelet transform and other operations, and combining morphological filtering and multi-channel correlation analysis, noise can be effectively suppressed and the candidate point set of traveling wave head can be accurately identified, thus providing reliable candidate points for subsequent dynamic threshold adjustment.

[0066] Step 103: Using a dynamic selection mechanism, select travel wave head confirmation points from the travel wave head candidate point set.

[0067] In some embodiments of the present invention, a set of undetermined traveling wavefront points that meet the wavefront confirmation mechanism can be selected from the set of candidate traveling wavefront points, and then a traveling wavefront confirmation point can be selected from the set of undetermined traveling wavefront points based on a dynamic selection mechanism.

[0068] In some embodiments of the present invention, step 103 above can be implemented by the following steps 1031 to 1033. Figure 1 (not shown in the image) Step 1031: In the set of candidate traveling wavefronts, select a set of undetermined traveling wavefronts that meet the wavefront confirmation mechanism.

[0069] In some embodiments of the present invention, the wavefront confirmation mechanism includes, but is not limited to: multi-channel correlation mechanism (e.g., the time difference between the current wavefront and the corresponding phase voltage wavefront is within a specified range) and time consistency mechanism (e.g., the wavefront appearance time conforms to the traveling wave propagation law).

[0070] In some embodiments of the present invention, a set of undetermined traveling wavefront points that simultaneously satisfy the multi-channel correlation mechanism and the time consistency mechanism can be selected from the traveling wavefront candidate point set.

[0071] Step 1032: If, based on the timestamps carried by the undetermined points of the traveling wave front, the corresponding midpoints of the traveling wave fronts with amplitudes greater than or equal to the initial threshold are sequentially selected from the set of undetermined traveling wave fronts, then the selection is stopped and the midpoints of the traveling wave fronts are confirmed as the confirmed points of the traveling wave fronts.

[0072] Step 1033: Otherwise, based on the noise level of the traveling wave front undetermined point set and the distribution of the traveling wave front undetermined points in the traveling wave front undetermined point set, the initial threshold is updated to obtain the updated threshold, and the updated threshold is used to re-filter the traveling wave front undetermined point set until the corresponding traveling wave front confirmation point with an amplitude greater than or equal to the updated threshold is selected in sequence.

[0073] In some embodiments of the present invention, the initial threshold may be determined based on historical statistical data. For example, the sum of the mean and standard deviation of the channel wavefront amplitude of the transmission line over a period of time may be used as the initial threshold.

[0074] In some embodiments of the present invention, the process of determining the initial threshold can be implemented by the following steps B1 to B3: Step B1: Obtain the mean and standard deviation of the wavefront amplitude of the historical traveling wave signal in the transmission channel.

[0075] The transmission channel is a channel for transmitting traveling wave signals in the power transmission line.

[0076] Step B2: Obtain the intermediate value by multiplying the standard deviation by the adjustable coefficient.

[0077] Step B3: Obtain the initial threshold based on the sum of the mean and the median.

[0078] In some embodiments of the present invention, the average value of the wavefront amplitude of historical traveling wave signals in the channel of the traveling wave signal in the transmission line can be obtained. and standard deviation Therefore, the mean can be obtained through the following formula (2). and standard deviation The initial threshold T is obtained through calculation. init : Formula (2); Where k is an adjustable coefficient, which is usually taken as any value between 1 and 3, and can be dynamically adjusted according to the actual situation.

[0079] refer to Figure 5 As shown, firstly, in the candidate point set 501 of the traveling wave head (i.e., corresponding to...) Figure 4 From the candidate point set 406 of the traveling wave front shown, candidate points that satisfy the wave front confirmation mechanism 502 are selected to obtain the set of undetermined traveling wave front points 503; then, according to the timestamp carried by the undetermined traveling wave front points in the set of undetermined traveling wave front points 503, the amplitude of the undetermined traveling wave front points in the set of undetermined traveling wave front points 503 is compared with the initial threshold T of 504. init If, by comparison, a corresponding amplitude greater than or equal to the initial threshold T of 504 can be selected from the undetermined point set 503 of the traveling wavefront,... init If the midpoint of the traveling wave front is not found, the screening process in the set of undetermined traveling wave front points stops, and this midpoint is directly designated as the confirmed traveling wave front point, i.e., 505. If the screening of undetermined traveling wave front points in set 503 is completed without finding the midpoint, then the initial threshold T of 504 can be adjusted based on the noise level and distribution of the undetermined traveling wave front point set involved in 506. init Adjustments or updates are made to obtain updated thresholds. Then, using these updated thresholds, the set of undetermined points 503 of the traveling wave front is re-filtered until the corresponding traveling wave front confirmation points 505 with amplitudes greater than or equal to the updated thresholds are sequentially selected.

[0080] It should be noted that the final selected traveling wave front confirmation point may also include its corresponding timestamp, channel number, and amplitude, etc., and this invention does not impose any limitations on this.

[0081] In some embodiments of the present invention, the initial threshold can be updated based on the noise level of the traveling wave front undetermined point set and the distribution of the traveling wave front undetermined points within the traveling wave front undetermined point set, to obtain the updated threshold. The specific execution logic can be referred to in steps C1 to C4: Step C1: Calculate the standard deviation of the amplitude of the undetermined points of the traveling wave front within the set of undetermined points of the traveling wave front to obtain the standard evaluation deviation characterizing the noise level of the set of undetermined points of the traveling wave front.

[0082] Step C2: Measure the density of the travel wavefront undetermined points in the set of travel wavefront undetermined points to obtain a density parameter characterizing the distribution of the travel wavefront undetermined points in the set of travel wavefront undetermined points.

[0083] Step C3: By using a specific weighting formula, the standard evaluation difference and the density parameter are fused to obtain the feature fusion value.

[0084] Step C4: Obtain the updated threshold by multiplying the feature fusion value by the initial threshold.

[0085] In some embodiments of the present invention, firstly, the standard deviation of the amplitude of the undetermined points of the traveling wave front within the set of undetermined traveling wave fronts is calculated to obtain the standard evaluation deviation characterizing the noise level of the set of undetermined traveling wave fronts; secondly, the density of the undetermined traveling wave fronts within the set of undetermined traveling wave fronts is measured to obtain the density parameter characterizing the distribution of the undetermined traveling wave fronts within the set of undetermined traveling wave fronts; then, different weights, namely weight 1 and weight 2, are assigned to the standard evaluation deviation characterizing the noise level of the set of undetermined traveling wave fronts and the density parameter characterizing the distribution of the undetermined traveling wave fronts within the set of undetermined traveling wave fronts, respectively, and the sum of weight 1 and weight 2 is 1. The product of weight 1 and the standard evaluation deviation, and the product of the density parameter and weight 2 are fused to obtain a feature fusion value; finally, the updated threshold is obtained by multiplying the feature fusion value by the initial threshold.

[0086] In some embodiments of the present invention, the initial threshold can be dynamically adjusted according to the following situations: if the current noise level of the traveling wave front undetermined points in the traveling wave front undetermined point set is high, the initial threshold can be appropriately reduced; if the distribution of the traveling wave front undetermined points in the traveling wave front undetermined point set is relatively dense, the initial threshold can be appropriately increased.

[0087] It should be noted that after obtaining the updated threshold, it is possible to further analyze the changing trend of the undetermined points of the traveling wave wavefront in the time series within the set of undetermined points of the traveling wave wavefront. For example, if multiple undetermined points of the traveling wave wavefront do not meet the screening conditions of the initial threshold and show a certain regularity, the initial threshold can be adjusted accordingly.

[0088] In some embodiments of the present invention, a dynamic threshold adjustment and wavefront confirmation mechanism can effectively eliminate false wavefronts in the candidate point set of traveling wavefronts, thereby improving the accuracy of wavefront identification and providing reliable wavefront information, i.e., traveling wavefront confirmation points, for subsequent fault location and analysis. Here, the initial threshold for wavefront identification is dynamically generated based on real-time operating conditions. Unlike traditional fixed thresholds, which are prone to missed or false detections, this strategy is always adaptable to different environments, ensuring a balance between sensitivity and accuracy in wavefront identification. It can accurately identify wavefront information regardless of whether it is a weak traveling wave or a strong impact traveling wave.

[0089] Step 104: Using a dual-end ranging algorithm, analyze the traveling wave front confirmation point to obtain the location information of the fault point in the transmission line where the fault occurred.

[0090] In some embodiments of the present invention, the dual-end ranging algorithm involves installing traveling wave ranging devices at both ends of the line (transmission line) and calculating the location of the fault point on the transmission line by detecting the time difference between the arrival of the first traveling wave front at both ends.

[0091] In some embodiments of the present invention, the faulty transmission line includes: an A-end monitoring device and a B-end monitoring device, and the above step 104 can be implemented by the following steps 1041 to 1043. Figure 1 (not shown in the image) Step 1041: Obtain the time difference between the two ends based on the time difference between the time when the traveling wave wavefront confirmation point is detected by the monitoring device at end A and the time when the traveling wave wavefront confirmation point is detected by the monitoring device at end B.

[0092] Step 1042: Substitute the time difference between the two ends, the line length between the monitoring device at end A and the monitoring device at end B, the wave velocity, and the current temperature into the two-end traveling wave ranging formula to calculate the distance from the fault point to the monitoring device at end A.

[0093] Step 1043: Based on the location information of the monitoring device at end A and the distance, perform geographic coordinate mapping on the fault point to obtain the location information of the fault point.

[0094] In some embodiments of the present invention, reference is made to Figure 6 As shown, before obtaining the time difference between the two ends, the determined traveling wavefront confirmation point 601 (i.e., the corresponding point) can be first determined. Figure 5The traveling wave wavefront confirmation point 505 (shown) is timestamped using GPS (602). This synchronizes the second pulse signal from the GPS module to calibrate the timestamp of the traveling wave wavefront confirmation point 601 to nanosecond accuracy. Furthermore, the corresponding time can be converted to local time. Then, data communication is performed using two-end devices, monitoring device A and monitoring device B (execution 603). The time difference between the two ends (604) is calculated based on the difference between the time detected by monitoring device A and the time detected by monitoring device B at the traveling wave wavefront confirmation point 601. Finally, the distance is calculated using a distance formula with temperature compensation. That is, 605. Here, the distance from the fault point to the monitoring device at end A can be calculated according to the following formula (3). : Formula (3); in, The length of the line between monitoring device A and monitoring device B. At the speed of light, , The current temperature (°C) For the time difference between the two ends, This refers to the traveling wave propagation speed (km / s) after taking temperature into account.

[0095] Following the description above, after obtaining the distance... Next, geographic coordinate mapping 606 can be performed, based on distance. Using the coordinate information of the monitoring device at end A, the geographical coordinates of the fault point are determined, thus realizing the output of the fault point location as shown in 607.

[0096] In this way, by calculating the time difference between the two ends, compensating for wave velocity and temperature, and mapping geographical coordinates, high-precision location of the fault point can be achieved, providing intuitive fault location information for power dispatching.

[0097] Referring to the foregoing, the functional framework of the system in which the fault location method combining voltage and current traveling waves provided in this embodiment of the invention is located can be referred to... Figure 7 As shown, the system comprises three main functional parts, which are as follows: 701. Multi-channel acquisition module: It adopts a specially customized wideband current and voltage transformer for signal isolation acquisition, and acquires four channels of current waveform data (IA, IB, IC, I0) and four channels of voltage waveform data (UA, UB, UC, U0) respectively. Then, it uses an operational amplifier to design a bandpass filter and a differential acquisition circuit for signal filtering and acquisition.

[0098] 702. Core MCU: Employs a 400MHz microcontroller for data processing, featuring two core algorithms: wavefront recognition and dynamic threshold adaptive adjustment. This enables precise identification of the traveling wave's wavefront. It also incorporates a high-precision GPS module for positioning and timing, achieving nanosecond-level accuracy. Combining wavefront recognition and dynamic threshold adaptive adjustment algorithms, it accurately transmits data to the system platform via a 4G module or the Global System for Mobile Communications (GSM).

[0099] 703. System Platform: By integrating the distribution characteristics of equipment throughout the entire line, the system determines the time difference between the traveling wave fault point and the two nearest measurement points. Then, combining this with the propagation speed of the traveling wave in the transmission line, the distance from the fault point to the measurement point is calculated, achieving precise location. Simultaneously, this system can also be used to effectively integrate and coordinate the traveling wave ranging device with other power system equipment, thereby improving system integration and compatibility, facilitating data sharing and comprehensive utilization, and providing technical support for intelligent management of power systems.

[0100] The corresponding references are available. Figure 8 As shown, firstly, the acquisition unit sends the acquired four current signals and four voltage signals to the core MCU, which then executes... Figure 8 As shown in steps 801 and 802; secondly, using the second pulse signal output by the GPS module, the timestamps of the four current signals and four voltage signals stored in the core MCU are aligned and calibrated, i.e., this is achieved by executing steps 803 and 804; then, the core MCU performs multi-scale feature analysis, multi-channel correlation analysis, and relevant dynamic threshold selection on the time-aligned timestamps of the four current signals and four voltage signals to accurately determine the wavefront information, and synchronously sends the determined wavefront information and the timestamps carried in the wavefront information, along with the latitude and longitude information sent by the GPS module, to the system platform so that the system platform can accurately locate the fault point, i.e., executing steps 805 and 806; finally, the system platform can further utilize the geographic information system to determine the location information of the fault point based on the wavefront information and latitude and longitude coordinates, i.e., executing step 807, and can further send the obtained location information of the fault point to the scheduler for updating, so as to realize the visualization of the location information of the fault point, i.e., executing step 808.

[0101] In other words, the fault location method combining voltage and current traveling waves provided in this embodiment of the invention can use a high-precision GPS module for positioning and timing, achieving centimeter-level positioning accuracy and nanosecond-level timing accuracy. Combined with a wavefront recognition algorithm, the wavefront confirmation point of the traveling wave is accurately uploaded to the system platform. The platform can then calculate the location of the fault point by detecting and analyzing the time difference between the arrival of the traveling wave at both ends of the line, combined with the line length and wave speed, thereby achieving high-precision fault location.

[0102] Here, the platform can be a highly integrated IoT system. Leveraging the principle of traveling wave propagation, a high-precision GPS timing system in the hardware circuit, and an intelligent algorithm for wavefront recognition, it establishes a two-end ranging algorithm that considers the distribution characteristics of line parameters. This algorithm first determines the time difference between the traveling wave fault point and the two nearest measurement points based on the acquired traveling wave signal. Then, combining this with the propagation speed of the traveling wave in the transmission line, it calculates the distance from the fault point to the measurement point, thus achieving precise location. Furthermore, the construction of this highly integrated IoT system enables the effective integration and collaborative operation of the traveling wave ranging device with other power system equipment, improving the system's integration and compatibility, facilitating data sharing and comprehensive utilization, and thus providing technical support for the intelligent management of power systems.

[0103] As those skilled in the art should know, existing traveling wave ranging technology still has some shortcomings, such as: Traveling wave signal acquisition is difficult: During a fault, the traveling wave signal on the line has a short duration and high frequency, requiring a current transformer with a high sampling frequency and wide bandwidth for accurate measurement. However, traditional current transformers have a low cutoff frequency, which cannot meet the requirements, resulting in severe distortion of the acquired traveling wave signal.

[0104] Inaccurate wavefront identification and large ranging deviation: During the propagation of traveling waves, factors such as line loss, refraction, reflection and noise interference will increase the difficulty of wavefront identification and make it easy to misjudge, thus affecting the ranging accuracy.

[0105] Low system integration: Most existing traveling wave ranging devices have limited functions and lack the ability to effectively integrate and work collaboratively with other power system equipment. This makes it impossible to achieve data sharing and comprehensive utilization, thus limiting the application scope of traveling wave ranging technology.

[0106] Therefore, in practical power system applications, traveling wave ranging equipment is installed at critical locations on distribution line towers to ensure comprehensive line coverage. The traveling wave ranging equipment is connected using anti-interference dedicated cables. The signal passes through a customized wideband current and voltage transformer, then through a bandpass filter designed with operational amplifiers and a differential acquisition circuit. Once a fault traveling wave signal is detected, wavefront identification, signal compensation, and data uploading to the platform are completed rapidly. The system platform immediately calculates and feeds back accurate fault location information to the power dispatch center in real time, providing accurate guidance for repair personnel, significantly shortening power outage time, and improving the operational efficiency and stability of the power system. Therefore, the voltage-current-traveling wave combined fault location method provided in this invention, through innovative design and multi-technology integration, effectively overcomes the shortcomings of existing technologies, providing an efficient and accurate solution for power system fault location, with broad application prospects and significant economic benefits.

[0107] The fault location method combining voltage and current traveling waves provided in this invention firstly performs multi-scale feature analysis and multi-channel correlation analysis on the acquired multi-channel current traveling wave signals and multi-channel voltage traveling wave signals. This enables timely and effective identification of candidate traveling wave front points, providing parameter support for subsequent accurate positioning of the traveling wave fronts. Secondly, based on a dynamically adjustable threshold for screening, unlike traditional fixed threshold methods which are prone to missed or false detections, this method ensures a balance between sensitivity and accuracy in traveling wave front identification. It can accurately identify wave fronts, regardless of whether the traveling wave is weak or a strong impulse, thereby achieving precise location of the fault point in the transmission line based on the accurately identified traveling wave front confirmation point.

[0108] Example 2: Based on the same inventive concept, embodiments of the present invention also provide a fault location system combining voltage and current traveling waves, such as... Figure 9 As shown, the system 900 includes: The data acquisition module 901 is used to acquire traveling wave data of the faulted transmission line using a wideband current and voltage transformer, and obtain multiple current traveling wave signals and multiple voltage traveling wave signals. The first analysis module 902 is used to perform multi-scale feature analysis and multi-channel correlation analysis on the multi-channel current traveling wave signal and the multi-channel voltage traveling wave signal to obtain a set of candidate points for traveling wave fronts; The filtering module 903 is used to filter out travel wave head confirmation points from the travel wave head candidate point set using a dynamic selection mechanism; The second analysis module 904 is used to analyze the traveling wave front confirmation point using a dual-end ranging algorithm to obtain the location information of the fault point in the transmission line where the fault occurred.

[0109] Optionally, the filtering module 903 includes: The first screening unit is used to screen the set of undetermined traveling wavefront points that meet the wavefront confirmation mechanism from the set of candidate traveling wavefront points. The second filtering unit is used to stop filtering and confirm the midpoint of the traveling wave head as the confirmed point if, based on the timestamp carried by the traveling wave head undetermined point in the set of traveling wave head undetermined points, the corresponding traveling wave head midpoint with an amplitude greater than or equal to the initial threshold is selected in sequence. Otherwise, based on the noise level of the set of undetermined traveling wave front points and the distribution of the undetermined traveling wave front points within the set, the initial threshold is updated to obtain an updated threshold. The updated threshold is then used to re-filter the set of undetermined traveling wave front points until the corresponding traveling wave front confirmation points with amplitudes greater than or equal to the updated threshold are selected in sequence.

[0110] Optionally, the filtering module 903 further includes: A determining unit is used to obtain the mean and standard deviation of the wavefront amplitude of historical traveling wave signals in the transmission channel; wherein, the transmission channel is the channel for transmitting traveling wave signals in the transmission line; an intermediate value is obtained by multiplying the standard deviation by the adjustable coefficient; and an initial threshold is obtained by summing the mean and the intermediate value.

[0111] Optionally, the second filtering unit is specifically used to calculate the standard deviation of the amplitude of the undetermined points of the traveling wave front within the set of undetermined traveling wave fronts to obtain a standard evaluation deviation characterizing the noise level of the set of undetermined traveling wave fronts; measure the density of the undetermined traveling wave fronts within the set of undetermined traveling wave fronts to obtain a density parameter characterizing the distribution of the undetermined traveling wave fronts within the set of undetermined traveling wave fronts; fuse the standard evaluation deviation and the density parameter using a specific weighting formula to obtain a feature fusion value; and obtain the updated threshold by multiplying the feature fusion value by the initial threshold.

[0112] Optionally, the first analysis module 902 includes: An analog-to-digital conversion unit is used to perform analog-to-digital conversion on the multi-channel current traveling wave signal and the multi-channel voltage traveling wave signal respectively to obtain multi-channel current digital waveform data and multi-channel voltage digital waveform data. The calibration unit is used to calibrate the timestamps of the multi-channel current digital waveform data and the multi-channel voltage digital waveform data using the second pulse signal output by the Global Positioning System (GPS), so as to obtain time-aligned multi-channel current digital signals and multi-channel voltage digital signals. The analysis unit is used to perform multi-scale feature analysis and multi-channel correlation analysis on the multi-channel current digital signal and the multi-channel voltage digital signal to obtain the candidate point set of the traveling wave front.

[0113] Optionally, the multi-scale feature analysis includes: wavelet transform, modulus maxima detection, feature filtering, and morphological filtering; the analysis unit is specifically used to sequentially perform wavelet transform and modulus maxima detection on the multi-channel current digital signals and the multi-channel voltage digital signals to obtain a set of current wavefront midpoints and a set of voltage wavefront midpoints; using a current feature threshold, feature filtering is performed on the feature sets of the current wavefront midpoints and the multi-channel current digital signals to obtain a current wavefront filter set and a current feature filter set, and the current feature filter set is merged into the current wavefront filter set to obtain the current... Effective wavefront point set; using voltage feature thresholds, feature filtering is performed on the voltage wavefront intermediate point set and the feature set of the multi-channel voltage digital signal to obtain a voltage wavefront filter set and a voltage feature filter set, and the voltage feature filter set is merged into the voltage wavefront filter set to obtain the effective wavefront point set; morphological filtering is performed on the effective wavefront point set and the effective wavefront point set of the voltage wavefront to obtain a current wavefront candidate point set and a voltage wavefront candidate point set, and multi-channel correlation analysis is performed on the current wavefront candidate point set and the voltage wavefront candidate point set to obtain the traveling wave wavefront candidate point set.

[0114] Optionally, the faulty transmission line includes: an A-end monitoring device and a B-end monitoring device. The second analysis module 904 is specifically used to obtain the time difference between the time when the A-end monitoring device detects the traveling wave front confirmation point and the time when the B-end monitoring device detects the traveling wave front confirmation point, and then to calculate the distance from the fault point to the A-end monitoring device by substituting the time difference, the line length between the A-end monitoring device and the B-end monitoring device, the wave velocity, and the current temperature into the two-end traveling wave ranging formula; and finally, to perform geographic coordinate mapping on the fault point based on the location information of the A-end monitoring device and the distance, thereby obtaining the location information of the fault point.

[0115] It should be noted that the description of this system is similar to that of the method embodiments described above, and has similar beneficial effects. For technical details not disclosed in the system embodiments of this invention, please refer to the description of the method embodiments of this invention for understanding.

[0116] Example 3: like Figure 10As shown, the present invention also provides an electronic device, which may be a computer device, a microcontroller device, a smart mobile device, etc. The electronic device 1000 in this embodiment may include a processor 1010, a memory 1020, a transceiver component 1030, etc. The memory 1020, the processor 1010, and the transceiver component 1030 are connected via a bus 1040; the memory 1020 can be used to store executable programs, and an exemplary executable program may include instructions; the processor 1010 is used to execute the instructions stored in the memory. The memory 1020 can also be used to store data, which can be accessed and / or modified when instructions are executed.

[0117] The processor may be a Central Processing Unit (CPU), or it may be other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. It is the computing and control core of the terminal, and it is suitable for implementing one or more instructions. Specifically, it is suitable for loading and executing one or more instructions in the storage medium to implement the corresponding method flow or corresponding function, so as to realize the steps of the fault location method combining voltage traveling wave and current traveling wave in the above embodiments.

[0118] Example 4 Based on the same inventive concept, this invention also provides a readable storage medium, specifically an electronic device readable storage medium (Memory). This readable storage medium is a memory device within an electronic device used to store programs and data. It is understood that the storage medium here can include both built-in storage media within the electronic device and extended storage media supported by the electronic device. The storage medium provides storage space, which stores the terminal's operating system. Furthermore, this storage space also stores one or more instructions suitable for loading and execution by a processor. These instructions can be one or more executable programs (including program code). It should be noted that the storage medium here can be high-speed RAM or non-volatile memory, such as at least one disk storage device. Loading and executing one or more instructions stored in the storage medium by the processor can implement the steps of the fault location method combining voltage and current traveling waves in the above embodiments.

[0119] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, systems, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0120] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0121] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0122] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0123] The above are merely embodiments of the present invention and are not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention are included within the scope of the claims of the present invention pending approval.

Claims

1. A fault location method combining voltage and current traveling waves, characterized in that, The method includes: Wideband current and voltage transformers are used to collect traveling wave data of the faulted transmission line, and obtain multiple current traveling wave signals and multiple voltage traveling wave signals. Multi-scale feature analysis and multi-channel correlation analysis are performed on the multi-channel current traveling wave signal and the multi-channel voltage traveling wave signal to obtain a set of candidate points for traveling wave fronts; A dynamic selection mechanism is used to screen travel wave head confirmation points from the set of travel wave head candidate points; A dual-end ranging algorithm is used to analyze the traveling wave front confirmation point to obtain the location information of the fault point in the transmission line where the fault occurred.

2. The method according to claim 1, characterized in that, The dynamic selection mechanism used to screen travel wavefront confirmation points from the candidate travel wavefront point set includes: In the candidate set of traveling wavefronts, a set of undetermined traveling wavefronts that meet the wavefront confirmation mechanism is selected; If, based on the timestamps carried by the undetermined points of the traveling wave wavefront, the corresponding midpoints of the traveling wave wavefronts with amplitudes greater than or equal to the initial threshold are sequentially selected from the set of undetermined points of the traveling wave wavefront, then the selection is stopped and the midpoints of the traveling wave wavefronts are confirmed as the confirmed points of the traveling wave wavefronts. Otherwise, based on the noise level of the traveling wave front undetermined point set and the distribution of the traveling wave front undetermined points within the traveling wave front undetermined point set, the initial threshold is updated to obtain an updated threshold. The updated threshold is then used to re-filter the traveling wave front undetermined point set until the corresponding traveling wave front confirmation point with an amplitude greater than or equal to the updated threshold is selected in sequence.

3. The method according to claim 2, characterized in that, The process of determining the initial threshold includes: The mean and standard deviation of the wavefront amplitude of historical traveling wave signals in the transmission channel are obtained; wherein, the transmission channel is the channel for transmitting traveling wave signals in the transmission line; The median value is obtained by multiplying the standard deviation by the adjustable coefficient. The initial threshold is obtained by summing the mean and the median.

4. The method according to claim 2 or 3, characterized in that, The step of updating the initial threshold based on the noise level of the set of undetermined traveling wavefront points and the distribution of the undetermined traveling wavefront points within the set, to obtain the updated threshold, includes: The standard deviation of the amplitude of the undetermined points of the traveling wave front within the set of undetermined points of the traveling wave front is calculated to obtain the standard evaluation deviation characterizing the noise level of the set of undetermined points of the traveling wave front; The density of the travel wavefront undetermined points in the set of undetermined travel wavefronts is measured to obtain a density parameter characterizing the distribution of the travel wavefront undetermined points in the set of undetermined travel wavefronts. The feature fusion value is obtained by fusing the standard evaluation difference and the density parameter using a specific weighting formula; The updated threshold is obtained by multiplying the feature fusion value by the initial threshold.

5. The method according to claim 1, characterized in that, The process involves performing multi-scale feature analysis and multi-channel correlation analysis on the multi-channel current traveling wave signals and the multi-channel voltage traveling wave signals to obtain a candidate set of traveling wave fronts, including: The multi-channel current traveling wave signal and the multi-channel voltage traveling wave signal are respectively converted from analog to digital to obtain multi-channel current digital waveform data and multi-channel voltage digital waveform data; The timestamps of the multi-channel current digital waveform data and the multi-channel voltage digital waveform data are calibrated using the second pulse signal output by the Global Positioning System (GPS) to obtain time-aligned multi-channel current digital signals and multi-channel voltage digital signals. Multi-scale feature analysis and multi-channel correlation analysis are performed on the multi-channel current digital signal and the multi-channel voltage digital signal to obtain the candidate point set of the traveling wave front.

6. The method according to claim 5, characterized in that, The multi-scale feature analysis includes: wavelet transform, modulus maxima detection, feature selection, and morphological filtering; The process of performing multi-scale feature analysis and multi-channel correlation analysis on the multi-channel current digital signals and the multi-channel voltage digital signals to obtain the candidate set of traveling wavefronts includes: Wavelet transform and modulus maxima detection are performed on the multi-channel current digital signal and the multi-channel voltage digital signal respectively to obtain the current wavefront midpoint set and the voltage wavefront midpoint set. Using current feature thresholds, feature filtering is performed on the current wavefront midpoint set and the feature set of the multi-channel current digital signal, respectively, to obtain a current wavefront filtering set and a current feature filtering set. The current feature filtering set is then merged into the current wavefront filtering set to obtain the effective current wavefront point set. Using voltage feature thresholds, feature filtering is performed on the voltage wavefront midpoint set and the feature set of the multi-channel voltage digital signal, respectively, to obtain a voltage wavefront filtering set and a voltage feature filtering set. The voltage feature filtering set is then merged into the voltage wavefront filtering set to obtain the effective voltage wavefront point set. Morphological filtering is performed on the effective point set of the current wavefront and the effective point set of the voltage wavefront respectively to obtain the candidate point set of the current wavefront and the candidate point set of the voltage wavefront. Multi-channel correlation analysis is then performed on the candidate point set of the current wavefront and the candidate point set of the voltage wavefront to obtain the candidate point set of the traveling wavefront.

7. The method according to claim 1, characterized in that, The faulty transmission line includes: an A-end monitoring device and a B-end monitoring device. A dual-end ranging algorithm is used to analyze the traveling wave front confirmation point to obtain the location information of the fault point in the faulty transmission line, including: The time difference between the two ends is obtained by comparing the time when the traveling wave wavefront confirmation point is detected by the monitoring device at end A with the time when the traveling wave wavefront confirmation point is detected by the monitoring device at end B. The distance from the fault point to the monitoring device at end A is calculated by substituting the time difference between the two ends, the line length between the monitoring device at end A and the monitoring device at end B, the wave velocity, and the current temperature into the two-end traveling wave ranging formula. Based on the location information of the monitoring device at end A and the distance, the fault point is mapped to geographic coordinates to obtain the location information of the fault point.

8. A fault location system combining voltage traveling wave and current traveling wave, characterized in that, The system includes: The data acquisition module is used to acquire traveling wave data of the faulty transmission line using a wideband current and voltage transformer, and obtain multiple current traveling wave signals and multiple voltage traveling wave signals. The first analysis module is used to perform multi-scale feature analysis and multi-channel correlation analysis on the multi-channel current traveling wave signal and the multi-channel voltage traveling wave signal to obtain a set of candidate points for the traveling wave front; The filtering module is used to filter out travel wave head confirmation points from the travel wave head candidate point set using a dynamic selection mechanism; The second analysis module is used to analyze the traveling wave front confirmation point using a dual-end ranging algorithm to obtain the location information of the fault point in the transmission line where the fault occurred.

9. An electronic device, characterized in that, include: At least one processor and memory; The memory and processor are connected via a bus; The memory is used to store one or more programs; When the one or more programs are executed by the at least one processor, the fault location method combining voltage and current traveling waves as described in any one of claims 1 to 7 is implemented.

10. A readable storage medium, characterized in that, It contains an execution program, which, when executed, implements the fault location method combining voltage and current traveling waves as described in any one of claims 1 to 7.

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