Fault monitoring device and fault monitoring method for uninterruptible operation of power distribution network

Abstract

The invention relates to the technical field of power distribution network fault monitoring, in particular to a fault monitoring device and a fault monitoring method for power distribution network non-outage operation, and the method comprises the steps: obtaining a transient data sequence of a plurality of power distribution lines; monitoring the transient data sequence, and judging whether the transient data sequence meets a preset fault triggering condition or not; if the transient data sequence meets the fault triggering condition, determining a multi-channel transient waveform data set of the distribution line based on the transient data sequence; and performing comparative analysis on the multi-channel transient waveform data set, and determining a fault line positioning result according to a comparative analysis result. According to the invention, the method achieves the recognition and quick positioning of a line fault in a non-power-cut operation state, and guarantees the continuous and stable operation of a power system.

Description

Technical Field

[0001] This application relates to the field of power distribution network fault monitoring technology, and in particular to a fault monitoring device and method for power distribution network uninterrupted operation. Background Technology

[0002] In modern power systems, the distribution network is a crucial link connecting power users to the main power grid, and its safe and stable operation is essential for ensuring power supply reliability. With urbanization and increasing electricity load, the length and complexity of distribution lines are also growing. However, during operation, the distribution network is frequently prone to grounding faults and short-circuit faults due to various reasons such as natural disasters, equipment aging, and external damage. These faults not only cause power outages for users, affecting the normal production and lives of residents and businesses, but in severe cases, they can even lead to equipment damage and secondary disasters.

[0003] Traditional methods for monitoring faults in distribution networks typically rely on circuit breaker tripping, manual line inspection, or simple fault indicators. These methods have several shortcomings: First, circuit breaker tripping can lead to widespread power outages, affecting power supply continuity, and the accuracy of fault location is limited, often requiring time-consuming manual inspections, which is inefficient. Second, manual line inspections are inefficient, especially in inclement weather or at night, and pose safety hazards. Furthermore, while existing fault indicators can provide some fault indication, they are usually based on static thresholds or simple logic judgments, lacking the ability to detect transient, hidden, or high-impedance faults, easily leading to misjudgments or missed detections, and failing to accurately locate the fault source, resulting in longer fault investigation and restoration times and increased maintenance costs. Especially in the context of live-line work (Live-line work), the requirements for real-time, accurate, and non-disruptive fault monitoring are even higher. Existing technologies struggle to meet the need for rapid and accurate fault location without interrupting power supply, in order to quickly isolate faults and restore normal power supply, thus affecting the reliability and power quality of the power grid. Therefore, there is room for improvement. Summary of the Invention

[0004] This application provides a fault monitoring device and method for live-line operation in power distribution networks, which can identify and quickly locate line faults under live-line operation conditions, ensuring the continuous and stable operation of the power system.

[0005] The first aspect of this application provides a fault monitoring device for live-line work in power distribution networks: a fault monitoring device for live-line work in power distribution networks includes:

[0006] The acquisition unit is connected to multiple power distribution lines and is used to acquire transient data sequences from each of the power distribution lines.

[0007] The collection unit, connected to the acquisition unit, is used to receive transient data sequences collected from multiple acquisition units, perform data calculations on the transient data sequences, and obtain fault line location results.

[0008] By adopting the above technical solution, and by connecting multiple power distribution lines through the acquisition unit and collecting transient data sequences from each power distribution line, the original electrical information of the power grid operation can be obtained in real time, thereby providing comprehensive basic data support for fault analysis. By receiving transient data sequences from multiple acquisition units through the aggregation unit and performing data calculations on the transient data sequences, massive amounts of distributed monitoring data can be centrally processed and comprehensively analyzed, thereby efficiently obtaining accurate fault line location results and improving the automation and accuracy of fault identification.

[0009] Optionally, the acquisition unit and the aggregation unit maintain time synchronization through a clock synchronization mechanism to ensure the synchronization of the transient data sequence.

[0010] By adopting the above technical solution, the acquisition unit and the collection unit maintain time synchronization through a clock synchronization mechanism to ensure the synchronization of transient data sequences. This ensures that transient data from different measurement points are accurately aligned in the time dimension, thereby avoiding misjudgment caused by timing deviations and significantly improving the accuracy and reliability of fault diagnosis and location.

[0011] Optionally, the aggregation unit further includes a communication module, which is used to encapsulate the fault line location result determined by the aggregation unit into a fault information message and send it to the backend main station server through the communication network.

[0012] By adopting the above technical solution, the fault location result determined by the aggregation unit is encapsulated into a fault information message through the communication module of the aggregation unit and sent to the back-end main station server through the communication network. This enables remote, real-time and automated transmission of fault information, allowing power operation and maintenance personnel to quickly obtain fault location information and take timely countermeasures, greatly shortening fault handling time and reducing power outage losses.

[0013] The second aspect of this application provides a fault monitoring method for live-line work in a power distribution network, applied to the fault monitoring device for live-line work in a power distribution network according to the first aspect. The fault monitoring method includes:

[0014] Acquire transient data sequences from multiple power distribution lines, wherein the transient data sequences include at least one of transient current sequences and transient voltage sequences;

[0015] The transient data sequence is monitored to determine whether it meets the preset fault triggering conditions.

[0016] If the transient data sequence satisfies the fault triggering condition, then based on the transient data sequence, the multi-channel transient waveform dataset of the power distribution line is determined;

[0017] The multi-channel transient waveform dataset is compared and analyzed, and the fault location result is determined based on the comparison and analysis results.

[0018] By adopting the above technical solution and acquiring transient data sequences of multiple power distribution lines, the electrical operating status of the power distribution lines can be comprehensively and in real time, thus providing a continuous data stream for fault detection. By monitoring the transient data sequences and determining whether preset fault triggering conditions are met, potential fault events can be intelligently identified, avoiding invalid data processing and improving monitoring efficiency. If the fault triggering conditions are met, a multi-channel transient waveform dataset of the power distribution line can be determined based on the transient data sequence, and a complete waveform containing synchronization information of all relevant lines can be constructed, thus providing a detailed and reliable data source for fault analysis. By comparing and analyzing the multi-channel transient waveform dataset and determining the fault line location result based on the comparison and analysis results, the characteristics of the fault line can be intelligently identified from complex waveform data, thereby achieving automatic, rapid, and accurate identification of the fault line.

[0019] Optionally, monitoring the transient data sequence and determining whether the transient data sequence meets preset fault triggering conditions specifically includes:

[0020] Obtain the amplitude of electrical parameters in the transient data sequence, wherein the amplitude of electrical parameters includes at least one of current amplitude and transient voltage amplitude;

[0021] Based on the electrical parameter amplitude, the difference in electrical parameter amplitude between two adjacent period values ​​in the transient data sequence is calculated, and the electrical parameter change rate is obtained by dividing by the previous period value.

[0022] When the rate of change of the electrical parameter is detected to exceed a preset amplitude change rate threshold, it is determined whether the amplitude of the electrical parameter at the current moment exceeds the preset amplitude threshold.

[0023] If the amplitude of the electrical parameter exceeds the preset amplitude threshold, the current time is determined as the fault triggering time point, and the transient data sequence is determined to meet the fault triggering condition.

[0024] By adopting the above technical solution, and by acquiring the amplitude of electrical parameters in the transient data sequence and calculating the rate of change of electrical parameters in adjacent cycles, the system can sensitively capture the violent electrical fluctuations at the moment a fault occurs in the power distribution line, thereby achieving early detection of fault events. When the rate of change of electrical parameters is detected to exceed a preset threshold, it is further determined whether the amplitude of the electrical parameters at the current moment exceeds the preset amplitude threshold. This can eliminate false triggers caused by normal load fluctuations or transient interference, thereby ensuring the accuracy of fault judgment and anti-interference capability. If the amplitude of electrical parameters exceeds the preset amplitude threshold, the current moment is determined as the fault trigger point, and the transient data sequence is determined to meet the fault triggering conditions. This provides an accurate starting time reference for subsequent fault waveform extraction and analysis, thereby improving the real-time performance and effectiveness of the entire fault analysis process.

[0025] Optionally, determining the multi-channel transient waveform dataset of the power distribution line based on the transient data sequence specifically includes:

[0026] Using the fault triggering time point as a time reference, and according to the transient data sequence, a first transient data sequence before the time reference and a second transient data sequence after the time reference are obtained according to a preset time period.

[0027] The discrete sampling points contained in the first transient data sequence and the second transient data sequence are reconstructed in time sequence to obtain the corresponding transient waveform;

[0028] Based on the transient waveform, construct the multi-channel transient waveform dataset of the power distribution line.

[0029] By adopting the above technical solution, and using the fault triggering time point as the time reference, the first and second transient data sequences with preset time periods before and after it are obtained. This allows for the capture of the complete electrical transient process before and after the fault, thereby comprehensively recording the fault waveform characteristics and providing data support for in-depth analysis. By reconstructing the discrete sampling points contained in the first and second transient data sequences in a time sequence, the corresponding transient waveforms can be obtained. This transforms the original sampling data into an intuitive and continuous waveform diagram, facilitating waveform analysis and feature extraction. By constructing a multi-channel transient waveform dataset for power distribution lines based on the transient waveforms, the waveforms of different lines and different phases can be uniformly managed and presented, thus laying a data foundation for comprehensive comparison and analysis and improving analysis efficiency.

[0030] Optionally, the step of comparing and analyzing the multi-channel transient waveform dataset, and determining the fault location result based on the comparison and analysis results, specifically includes:

[0031] Based on the multi-channel transient waveform dataset, the polarity of the first half-wave of the transient waveform is determined;

[0032] The polarity of the first half of the transient waveform is compared and analyzed. Based on the comparison and analysis results, the power distribution lines are divided to obtain line groups.

[0033] Based on the aforementioned line group, the location result of the faulty line is determined.

[0034] By adopting the above technical solution, the polarity of the first half of the transient waveform can be determined based on the multi-channel transient waveform dataset, and key directional information of fault transient wave propagation can be extracted, thus providing a rapid basis for preliminary differentiation of fault areas. By comparing and analyzing the polarity of the first half of the transient waveform to divide the line groups, the lines can be classified according to the transient wave propagation characteristics, thereby effectively narrowing the scope of fault investigation. By determining the fault line location result based on the line group, the fault line can be further refined and finally locked using the pre-classified line set, achieving efficient preliminary fault location.

[0035] Optionally, the step of dividing the power distribution lines into line groups based on the comparison and analysis results specifically includes:

[0036] Based on the comparison and analysis results, if there is a situation where the polarity of the first half wave of the transient waveform of the power distribution line is inconsistent, the power distribution line is divided to obtain at least two polarity line groups, wherein the at least two polarity line groups have opposite first half wave polarities.

[0037] A similarity analysis is performed on the transient waveforms of the various power distribution lines grouped under the same polarity.

[0038] Based on the similarity analysis results, power distribution lines with similarity below a preset similarity threshold are identified from the same polarity line group.

[0039] Based on the power distribution lines, the polarity line groups are divided to obtain the final line groups.

[0040] By adopting the above technical solution, if there is an inconsistency in the polarity of the first half-wave of the transient waveform of the distribution line, it is divided into at least two polarity line groups with opposite first half-wave polarities. This utilizes the characteristic that the transient current or voltage has opposite polarities on both sides of the fault point to quickly and initially divide the line into possible fault direction areas, thereby significantly narrowing the fault search range. By performing similarity analysis on the transient waveforms of each distribution line within the same polarity line group, the characteristics of the lines within the same polarity group can be further refined, identifying abnormal lines and thus improving fault identification accuracy. Furthermore, by identifying distribution lines with similarity scores below a preset similarity threshold based on the similarity analysis results, abnormal lines within the same polarity group with inconsistent technical characteristics can be accurately identified, further refining the line group division and improving the accuracy and robustness of fault location.

[0041] Optionally, determining the fault location result based on the line group specifically includes:

[0042] If there are distribution lines with opposite first half-wave polarities in the line group, then count the number of the corresponding distribution lines respectively.

[0043] The group of one or more power distribution lines with the fewest number of lines is identified as the fault group containing the faulty line.

[0044] The fault location result is generated based on the power distribution lines included in the fault group.

[0045] By adopting the above technical solution, if there are distribution lines with opposite first half-wave polarities in the line group, the number of the corresponding distribution lines can be counted respectively, which can quantify the distribution of lines in different polarity areas, thus providing a solid basis for judging the location of the fault point. By identifying one or more line groups with the fewest distribution lines as the fault group containing the faulty line, the fault current distribution characteristics can be used to quickly locate the set of lines most likely to be faulty, thereby significantly narrowing the scope of fault investigation and improving the location efficiency. By generating the fault line location result based on the distribution lines contained in the fault group, the analysis result can be directly converted into a specific fault line indication, thus providing power operation and maintenance personnel with a clear and operable basis for fault repair.

[0046] Optionally, the fault monitoring method further includes:

[0047] When a fault is detected in the power distribution line, an external positioning signal is injected into the power distribution line through the grounding device;

[0048] Determine whether multiple monitoring points of the power distribution line have received the external positioning signal;

[0049] If a monitoring point on the power distribution line fails to receive the external positioning signal, the location of the monitoring point will be determined as the location area of ​​the fault.

[0050] By adopting the above technical solution, when a fault is detected in the power distribution line, an external positioning signal is immediately injected into the power distribution line through the grounding device. This transforms traditional passive monitoring into active detection, providing active excitation for more accurate segmented fault location. This overcomes the limitations of relying solely on transient waves from natural faults for location. By determining whether multiple monitoring points along the power distribution line receive the external positioning signal, the signal propagation boundary can be defined using the signal reception status of the monitoring points along the line. This allows for a preliminary assessment of the approximate area of ​​the fault. If a monitoring point fails to receive the external positioning signal, its location is determined as the fault location area. This provides maintenance personnel with a precise fault investigation range, significantly improving the efficiency and accuracy of fault detection.

[0051] In summary, this application includes at least one of the following beneficial technical effects:

[0052] 1. By connecting multiple power distribution lines through the acquisition unit and collecting transient data sequences of each power distribution line, the original electrical information of the power grid operation can be obtained in real time, thereby providing comprehensive basic data support for fault analysis. By receiving transient data sequences collected from multiple acquisition units through the aggregation unit and performing data calculations on the transient data sequences, massive amounts of distributed monitoring data can be centrally processed and comprehensively analyzed, thereby efficiently obtaining accurate fault line location results and improving the automation and accuracy of fault identification.

[0053] 2. By acquiring transient data sequences from multiple power distribution lines, the electrical operating status of the power distribution lines can be comprehensively and in real time, thus providing a continuous data stream for fault detection. By monitoring the transient data sequences and determining whether preset fault triggering conditions are met, potential fault events can be intelligently identified, avoiding invalid data processing and improving monitoring efficiency. If the fault triggering conditions are met, the multi-channel transient waveform dataset of the power distribution line can be determined based on the transient data sequence, and a complete waveform containing synchronization information of all relevant lines can be constructed, thus providing a detailed and reliable data source for fault analysis. By comparing and analyzing the multi-channel transient waveform dataset and determining the fault line location result based on the comparison and analysis results, the characteristics of the fault line can be intelligently identified from complex waveform data, thereby achieving automatic, rapid and accurate identification of the fault line.

[0054] 3. By immediately injecting an external location signal into the power distribution line through the grounding device when a fault is detected, the traditional passive monitoring can be transformed into active detection. This provides active excitation for more accurate segmented fault location, thus overcoming the limitations of relying solely on transient waves of natural faults for location. By determining whether multiple monitoring points along the power distribution line receive the external location signal, the signal propagation boundary can be defined using the signal reception status of the monitoring points along the line, thereby initially determining the approximate area of ​​the fault point. If a monitoring point fails to receive the external location signal, the location of that monitoring point is determined as the fault location area, thus providing maintenance personnel with a precise fault investigation range and significantly improving the efficiency and accuracy of fault point detection. Attached Figure Description

[0055] Figure 1 This is a schematic diagram of the structure of a fault monitoring device for uninterrupted power supply operation in a power distribution network according to one embodiment of this application;

[0056] Figure 2 This is a flowchart illustrating the implementation of a fault monitoring method for live-line working in a power distribution network according to one embodiment of this application.

[0057] Figure 3 This is a flowchart illustrating the implementation of step S20 in a fault monitoring method for uninterrupted power supply operations in a distribution network according to an embodiment of this application.

[0058] Figure 4 This is a flowchart illustrating the implementation of step S30 in a fault monitoring method for uninterrupted power supply operations in a distribution network according to an embodiment of this application.

[0059] Figure 5 This is a flowchart illustrating the implementation of step S40 in a fault monitoring method for uninterrupted power supply operations in a distribution network according to an embodiment of this application.

[0060] Figure 6 This is a flowchart illustrating the implementation of step S42 in a fault monitoring method for uninterrupted power supply operations in a distribution network according to an embodiment of this application.

[0061] Figure 7 This is a flowchart illustrating the implementation of step S43 in a fault monitoring method for uninterrupted power supply operations in a distribution network according to an embodiment of this application.

[0062] Figure 8 This is another implementation flowchart of a fault monitoring method for uninterrupted power supply operation in a power distribution network according to one embodiment of this application. Detailed Implementation

[0063] The following embodiments will help those skilled in the art to further understand the function of this application, but do not limit this application in any way. It should be noted that those skilled in the art can make several modifications and improvements without departing from the concept of this application. These all fall within the protection scope of this application.

[0064] In the following description, specific details such as particular system architectures and techniques are set forth for illustrative purposes and not for limitation, in order to provide a thorough understanding of the embodiments of this application. However, those skilled in the art will understand that this application may also be implemented in other embodiments without these specific details. In other instances, detailed descriptions of well-known systems, apparatuses, circuits, and methods have been omitted so as not to obscure the description of this application with unnecessary detail.

[0065] It should be understood that, when used in this application specification and the appended claims, the term "comprising" indicates the presence of the described features, integrals, steps, operations, elements and / or components, but does not exclude the presence or addition of one or more other features, integrals, steps, operations, elements, components and / or a collection thereof.

[0066] The present application will be further described in detail below with reference to the accompanying drawings.

[0067] In one embodiment, such as Figure 1 As shown, this application discloses a fault monitoring device for live-line working in a power distribution network, the fault monitoring device comprising:

[0068] The acquisition unit is connected to multiple power distribution lines and is used to acquire transient data sequences from each power distribution line.

[0069] The collection unit, connected to the acquisition unit, is used to receive transient data sequences collected from multiple acquisition units, perform data calculations on the transient data sequences, and obtain the fault line location results.

[0070] The acquisition unit includes a current acquisition unit and a voltage acquisition unit, and is designed to be installed and removed while energized at the entry and exit points of 10kV distribution network cable lines, or connected to the PT cabinet via a connector or terminal block, in order to acquire the electrical parameters of the line in real time.

[0071] Specifically, current acquisition uses high-precision current transformers to collect three-phase currents on the secondary side of the cable and synthesizes zero-sequence current in real time for short-circuit and grounding fault assessment. Voltage acquisition is used for line voltage detection, monitoring phase voltages such as UAN, UBN, and UCN, or line voltages and zero-sequence voltages such as UAB, UBC, and U0+. The acquisition unit continuously and accurately records transient data such as transient current and voltage sequences of the line, which form the basis for subsequent line fault diagnosis and fault location. To ensure data reliability and accuracy, the acquisition unit has a high-speed sampling rate of up to 12.8kHz, with up to 256 sampling points per cycle, and can achieve three-phase synchronous sampling and high-precision fault recording, ensuring that even transient or hidden faults can be effectively captured.

[0072] As the core processing component of the device described in this application, the aggregation unit, which can also refer to the aggregation terminal itself, integrates a high-performance processor and storage capabilities. It can receive and synchronize transient data sequences transmitted in real time by multiple acquisition units, and perform complex algorithmic calculations and analyses on these transient data sequences. For example, the aggregation unit monitors in real time whether the transient data sequences meet preset fault triggering conditions, such as the rate of change of electrical parameter amplitudes and whether the amplitude exceeds a threshold. If met, it further constructs a multi-channel transient waveform dataset based on these data. Subsequently, the aggregation unit uses advanced algorithms, such as waveform first half-wave polarity comparison analysis and similarity analysis, to accurately determine the fault type, such as phase-to-phase short circuit or single-phase grounding, and identify the faulty line. Simultaneously, this unit also possesses edge computing capabilities, enabling it to complete fault assessment and preliminary location locally, effectively preventing false tripping and failure to trip caused by load fluctuations or inrush currents during closing, thereby providing intelligent and accurate fault alarm signals.

[0073] In one embodiment, the acquisition unit and the collection unit maintain time synchronization through a clock synchronization mechanism to ensure the synchronization of transient data sequences.

[0074] Specifically, this clock synchronization mechanism provides a unified and high-precision time reference for each acquisition unit distributed across different power distribution lines. This ensures that every transient data sampling point generated by the acquisition unit is based on a unified time reference, making effective timing alignment and correlation comparison of transient waveforms from different lines possible. For example, without precise synchronization, reliable conclusions cannot be drawn when determining the direction of fault wave propagation or comparing the polarity of the first half-wave. This mechanism guarantees the quality of input data for subsequent fault analysis algorithms, providing the physical basis for identifying faulty and non-faulty lines and distinguishing signal differences between upstream and downstream of the fault point. It significantly improves the reliability and accuracy of the entire fault monitoring and location system, eliminating analysis errors caused by disordered data timing.

[0075] In one embodiment, the aggregation unit further includes a communication module, which is used to encapsulate the fault line location results determined by the aggregation unit into a fault information message and send it to the backend main station server through the communication network.

[0076] Specifically, the aggregation unit also includes a communication module. This module encapsulates the fault location results determined by the aggregation unit into fault information messages and sends them to the backend master server via the communication network. This communication module supports multiple communication methods, such as remote 4G wireless communication (GPRS) and local Bluetooth wireless communication. Once the aggregation unit identifies and confirms the fault location results, the communication module quickly standardizes and encapsulates key fault information such as the time of fault occurrence, fault type, and fault line number to form fault information messages. Subsequently, these messages are uploaded to the backend master server in real time and proactively through a reliable wireless communication channel. This process supports two-way confirmation and retransmission functions to ensure reliable data delivery. Simultaneously, combined with local Bluetooth functionality, it also facilitates on-site maintenance personnel to perform local maintenance operations such as parameter reading, configuration, modification, and program upgrades via a mobile app, enabling real-time control and remote management of the line status.

[0077] In one embodiment, such as Figure 2 As shown, this application discloses a fault monitoring method for live-line work in power distribution networks, applied to the aforementioned fault monitoring device for live-line work in power distribution networks. The fault monitoring method specifically includes the following steps:

[0078] S10: Obtain transient data sequences from multiple power distribution lines. The transient data sequences shall include at least one of the transient current sequence and the transient voltage sequence.

[0079] Specifically, by deploying multiple independent acquisition units at key measurement points in the power distribution network, such as ring main units, towers, or cable joints, the electrical parameters of the power distribution lines they monitor, such as current and voltage, are continuously and frequently collected digitally. This forms a series of time-varying and high-density instantaneous data points, i.e., transient data sequences. These sequences can accurately depict the dynamic changes in electrical quantities of the line before and after abnormal conditions such as short circuits or grounding faults. They are the most original and critical data foundation for subsequent fault identification and location. For example, the operating status of the line can be comprehensively reflected by collecting three-phase current or three-phase voltage data on the line.

[0080] S20: Monitor the transient data sequence and determine whether the transient data sequence meets the preset fault triggering conditions.

[0081] Specifically, the real-time electrical data streams collected by the acquisition unit and continuously flowing into the aggregation unit from multiple power distribution lines are analyzed and judged in real time. This accurately identifies any abnormal phenomena or signal characteristics that may indicate line faults, such as sudden increases in short-circuit current or grounding current. The preset fault triggering conditions are a set of rules defined based on experience or calculation models, used to distinguish between normal fluctuations in the line and potential fault events. The judgment process aims to efficiently filter out routine load changes or disturbances. Only when the transient data sequence shows significant electrical quantity anomalies that conform to fault characteristics is it judged as meeting the triggering conditions, thereby initiating a more in-depth fault judgment process. This avoids misjudgments or false alarms caused by non-fault factors such as normal load fluctuations, equipment switching operations, or grid disturbances, ensuring that subsequent complex calculations are only initiated when a real fault occurs, thereby improving the real-time performance and effectiveness of the entire monitoring method.

[0082] S30: If the transient data sequence meets the fault triggering conditions, then the multi-channel transient waveform dataset of the power distribution line is determined based on the transient data sequence.

[0083] Specifically, once the aforementioned fault triggering conditions are determined to be met, i.e., signs of potential faults in the line are detected through the aforementioned steps, a continuous data window containing changes in key electrical quantities before and after the fault is extracted from the previously continuously recorded and high-speed sampled original transient data sequence, using the fault triggering moment as the time reference point. These current and voltage sampling points from different distribution lines are then used to construct a unified and multi-dimensional transient waveform set. The waveforms of all channels have high time synchronization due to sharing a unified time reference. This set can intuitively present the electrical dynamic response of each line at the moment of the fault, providing direct and high-quality input data for subsequent comparative analysis to accurately determine the faulty line.

[0084] S40: Compare and analyze the multi-channel transient waveform dataset, and determine the faulty line result based on the comparison and analysis results.

[0085] Specifically, by comparing the morphological characteristics, temporal relationships, or other intrinsic attributes of multiple transient waveforms from different power distribution lines contained in the multi-channel transient waveform dataset constructed in the aforementioned steps, one or more algorithms are applied. By comparing the specific performance of the transient waveforms of different power distribution lines when a fault occurs, the intrinsic correlation or differences between them are revealed. For example, by analyzing the amplitude, speed, or waveform shape of the changes in electrical quantities of different lines, the source or direction of the fault can be inferred. Based on these carefully designed comparison logics and analysis rules, a clear fault line result is finally obtained, such as the fault occurring in feeder No. 1. Finally, a clear conclusion is output, indicating which line or lines have failed, i.e., the fault line result.

[0086] In one embodiment, such as Figure 3 As shown, in step S20, the transient data sequence is monitored to determine whether it meets the preset fault triggering conditions, specifically including:

[0087] S21: Obtain the amplitude of electrical parameters in the transient data sequence. The amplitude of electrical parameters includes at least one of the current amplitude and the transient voltage amplitude.

[0088] Specifically, electrical parameter amplitude refers to the key values ​​that can represent the current electrical quantity from the transient data sequence obtained by continuous sampling. For example, the effective value of current in each cycle or the peak value in the transient voltage sequence can be calculated. These amplitudes are direct quantitative indicators that reflect the current operating status of the line and determine whether there are abnormal fluctuations. Their accurate extraction is the basis for subsequent calculation of the rate of change of electrical parameters.

[0089] S22: Based on the electrical parameter amplitude, calculate the difference in electrical parameter amplitude between two adjacent period values ​​in the transient data sequence, and divide by the previous period value to obtain the electrical parameter change rate.

[0090] Specifically, based on the obtained electrical parameter amplitude, such as the amplitude of a phase current, the absolute difference between its current cycle value and the immediately preceding cycle value is calculated. Then, this difference is divided by the previous cycle value to obtain the relative ratio of the change of the electrical parameter between the two cycles. This is the electrical parameter change rate. For example, if the current amplitude suddenly drops from 100A to 50A at a certain moment, then its change rate is (50-100) / 100=-0.5, or -50%. This method of calculating the relative change rate can effectively reflect the severity of electrical quantity changes, is not affected by the daily load fluctuation of the line, and provides an indicator sensitive to electrical quantity changes. It can quickly capture instantaneous anomalies that indicate line faults, such as sudden rises or falls in current or voltage caused by short circuits or grounding faults. Even minor faults can be quantified and identified in a timely manner as long as they cause a sufficient change rate.

[0091] S23: When the rate of change of electrical parameters is detected to exceed the preset amplitude rate of change threshold, determine whether the amplitude of electrical parameters at the current moment exceeds the preset amplitude threshold.

[0092] Specifically, when the calculated rate of change of electrical parameters, such as the rate of change of current reaching 50% or the rate of change of voltage exceeding 30%, first exceeds a pre-set threshold for the rate of change of amplitude used to identify drastic changes, the system immediately performs a second judgment. This involves checking whether the amplitude of the corresponding electrical parameter at that moment also exceeds another pre-set threshold for confirming an absolute level anomaly in the electrical quantity. For example, after detecting a voltage drop, the system further determines whether the current voltage amplitude is below 0.8 times the rated voltage; or after a current surge, it determines whether the current current amplitude exceeds 2.0 times the rated current. This step-by-step and combined judgment mechanism aims to improve the accuracy of fault identification. Furthermore, this dual-judgment technology effectively avoids misjudgments caused by a single trigger condition. For example, normal switching operations on the line may cause drastic changes in electrical parameters within a short period, but the amplitude remains within the normal range; or prolonged heavy loads on the line may cause the amplitude to remain consistently high, but the rate of change is not drastic. By simultaneously satisfying both the rate of change and the amplitude condition, the system ensures that only electrical anomalies that truly meet the fault characteristics are further processed, thereby improving the reliability and anti-interference capability of fault trigger judgment.

[0093] S24: If the amplitude of the electrical parameter exceeds the preset amplitude threshold, the current moment is determined as the fault trigger moment, and the transient data sequence is determined to meet the fault trigger condition.

[0094] Specifically, if the second judgment is also satisfied, that is, not only is a drastic change rate of electrical parameters detected, but the amplitude of electrical parameters at the current moment also exceeds the preset absolute threshold, then the current precise moment is clearly marked as the fault trigger moment. This indicates that the device has confirmed that the electrical anomaly in the current transient data sequence meets the preset conditions that indicate the existence of a fault. Therefore, the transient data sequence is formally determined to meet the fault trigger conditions.

[0095] In one embodiment, such as Figure 4 As shown, in step S30, which involves determining the multi-channel transient waveform dataset of the power distribution line based on the transient data sequence, the specific steps include:

[0096] S31: Using the fault trigger point as the time reference, according to the transient data sequence and a preset time period, obtain the first transient data sequence before the time reference and the second transient data sequence after the time reference.

[0097] Specifically, using the fault triggering time point determined in the aforementioned steps as a precise time reference—for example, assuming the triggering time point is T0 seconds—the system will retrieve a preset time period, such as 150 milliseconds, to obtain all transient data within 150ms before T0 seconds, forming a first transient data sequence. This data reflects the normal operating state of the line before the fault occurs or the precursors of the impending fault. Simultaneously, the system will also retrieve a preset time period backward, such as obtaining all transient data within 150ms after T0 seconds, forming a second transient data sequence. This data records in detail the evolution of electrical quantities after the fault occurs, including the instantaneous surges in fault current and voltage, transient oscillations, and eventual steady-state.

[0098] S32: Reconstruct the time sequence of the discrete sampling points contained in the first transient data sequence and the second transient data sequence to obtain the corresponding transient waveform.

[0099] Specifically, each set of first and second transient data sequences is essentially composed of a large number of digital quantization points collected at strict time intervals, such as one per microsecond. The time sequence reconstruction process involves logically sorting and connecting these independent and discrete digital sampling points according to their precise timestamps, thereby generating continuous curves that reflect the changes of electrical quantities over time. These are transient waveforms. For example, each sampled value of current or voltage is plotted on a graph with its sampling time as the horizontal axis and its value as the vertical axis, and then connected to create a detailed electrical waveform diagram, thus obtaining the corresponding transient waveform.

[0100] S33: Based on the transient waveforms, construct a multi-channel transient waveform dataset for power distribution lines.

[0101] Specifically, the transient waveforms reconstructed in the aforementioned steps, originating from different phases (A, B, C), different electrical quantity types (current, voltage, zero-sequence quantity), and different monitored distribution lines, are systematically integrated and encapsulated to form a unified, structured data set. Each transient waveform in this set is considered an independent channel, and all channels share the same time reference and are strictly aligned. For example, a typical multi-channel dataset may include the A-phase current waveform of line 1, the B-phase voltage waveform of line 1, the C-phase current waveform of line 2, and the zero-sequence voltage waveform of line 3. All these waveforms collectively depict the comprehensive performance of the entire distribution network at the moment of fault, enabling the fault diagnosis algorithm to simultaneously access and compare electrical responses from multiple lines and multiple parameters, thereby effectively identifying the fault propagation path and locating the fault source. For example, by comparing the polarity of the first half-wave or the difference in arrival time of different line current waveforms, the location of the fault can be determined. This plays a decisive role in accurately distinguishing faulty lines from non-faulty lines and improving the accuracy of fault location.

[0102] In one embodiment, such as Figure 5 As shown, in step S40, the multi-channel transient waveform dataset is compared and analyzed. Based on the comparison and analysis results, the faulty line is determined, specifically including:

[0103] S41: Determine the polarity of the first half of the transient waveform based on the multi-channel transient waveform dataset.

[0104] Specifically, for each waveform in the multi-channel transient waveform dataset, such as the voltage or current waveform of each phase or line, the direction of the first significant change after the fault triggering point is identified and determined. For example, if the voltage waveform shows the first falling peak immediately after the fault occurs, its first half-wave polarity is negative; if the current waveform shows the first rising trough immediately after the fault occurs, its first half-wave polarity is positive. This is usually determined by analyzing the trend of the waveform's change within a short time window near the fault initiation point or the sign of the first peak or trough. Because the propagation of the fault transient wave determines that its polarity will change specifically when it reaches different locations, accurate determination of the polarity of the first half-wave is a key prerequisite for using electrical wave propagation theory to determine the fault direction and divide the area, providing a direct and efficient distinguishing mark for subsequent line comparison analysis.

[0105] S42: Compare and analyze the polarity of the first half of the transient waveform, and divide the power distribution lines according to the comparison and analysis results to obtain line groups.

[0106] Specifically, the polarities of the first half-waves of transient waveforms from different distribution lines or different phases, determined in the aforementioned steps, are cross-referenced and compared. The purpose is to logically classify multiple distribution lines into different line groups based on the similarity or dissimilarity of these polarities. For example, lines with positive first half-wave polarities can be grouped together, and those with negative polarities can be grouped into another group. Alternatively, they can be grouped according to the polarity change relative to a reference point, much like distinguishing and grouping different magnetic materials based on the N / S polarity of a magnet. By initially delineating the area where a fault may occur and narrowing down the fault search area, based on the characteristics of transient wave propagation, lines close to the fault point but located in different directions often exhibit opposite or specific relationships in the polarities of the first half-waves of their transient responses. By grouping lines with the same polarity into one group and lines with opposite polarities into another, faulty sections and non-faulty sections can be effectively distinguished, thus providing an efficient and clearly categorized clue for final fault location.

[0107] S43: Determine the result of the faulty line based on the line group.

[0108] Specifically, based on the divided line groups, preset fault location rules are used to make a final judgment on these groups to determine which one or more distribution lines are faulty. For example, in a typical fault direction judgment principle, the fault point is usually considered to be located in the group of lines whose polarity is opposite to that of other lines in the first half of the wave, or whose polarity is special and changes most drastically. If only one line group exhibits specific fault characteristics, such as abnormal polarity or the largest amplitude, then the lines contained in that group are faulty lines. If there is a specific polarity reversal relationship between different groups, the fault point is usually located on the boundary line or node where the polarity reversal occurs. The final output is a clear location result, such as a fault in distribution line L3, which allows fault diagnosis to transition directly from the analysis stage to the decision-making stage. This provides maintenance personnel with clear information about the faulty lines, significantly shortens the fault finding time, and provides core and direct technical support for quickly restoring power supply, reducing power outage time, and improving power supply reliability.

[0109] In one embodiment, such as Figure 6 As shown, in step S42, based on the comparison and analysis results, the power distribution lines are divided into line groups, specifically including:

[0110] S421: Based on the comparison analysis results, if there is a situation where the polarity of the first half of the transient waveform of the power distribution line is inconsistent, the power distribution line is divided to obtain at least two polarity line groups, wherein at least two polarity line groups have opposite first half-wave polarities.

[0111] Specifically, after obtaining the polarity of the first half of the transient waveform of all distribution lines, the system checks whether there are differences in these polarities. For example, the polarity of the first half of the current in some lines is rising (positive polarity), while in others it is falling (negative polarity). If such inconsistency is detected, the system immediately divides the distribution lines into at least two independent polarity groups based on the difference between positive and negative polarities, such as a positive polarity group and a negative polarity group. All lines within these two groups share the same polarity, while the polarities between the two groups are clearly opposite. This utilizes the key physical principle that the polarity of transient waves will reverse at the fault point, which can efficiently classify most of the lines in the line network into a large area that is consistent with the relative position of the fault point, thereby significantly narrowing the possible range of fault occurrence and laying the foundation for subsequent refined analysis, avoiding invalid calculations.

[0112] S422: Perform similarity analysis on the transient waveforms of each distribution line group divided into the same polarity line group.

[0113] Specifically, after the distribution lines are initially grouped according to the polarity of the first half-wave, in order to further improve the positioning accuracy, a more detailed comparison of the complete transient waveforms of each distribution line within the same polarity group is performed. For example, several lines belonging to the positive polarity group are compared. This can be achieved by calculating the correlation coefficient, Euclidean distance, dynamic time warping (DTW) distance, etc., to quantify their similarity in terms of shape, amplitude variation trend, oscillation frequency, etc., thereby identifying whether there are anomalous waveforms that are significantly different from other lines within the group, revealing deeper differences in electrical characteristics within the same polarity group. Although these lines have the same polarity of the first half-wave, the waveform characteristics of lines that are actually near the fault point will show a high degree of consistency and special fault characteristics, such as transient amplitude, damping, and oscillation frequency. Lines that are far from the fault point or less affected will show a lower similarity in their waveforms, thus providing a more refined criterion for screening out the truly fault-related lines from the same polarity group.

[0114] S423: Based on the similarity analysis results, identify power distribution lines with similarity below the preset similarity threshold from the same polarity line group.

[0115] Specifically, similarity values ​​(such as quantitative similarity values) between waveforms of various distribution lines within the same group are calculated. These values ​​are then compared to a pre-set similarity threshold. If the transient waveform of a distribution line has a similarity lower than the average similarity with other lines in the group or with the typical waveform of the group, this line is identified as an abnormal line in that polarity line group. These abnormal lines may be genuine faulty lines with waveform characteristics significantly different from other non-faulty lines, or they may be lines indirectly affected by a fault but with atypical waveform characteristics. This effectively identifies lines that do not conform to the mainstream pattern in waveform details. These non-conforming lines are often direct participants or key reflectors of fault events. This step is crucial for refined localization, enabling subsequent judgments to focus on lines with genuine diagnostic value.

[0116] S424: Based on the power distribution lines, the polarity of the circuit groups is divided to obtain the final circuit groups.

[0117] Specifically, based on the identified distribution lines with similarity below a preset threshold, the initial polarity line groups formed during the initial phase will be readjusted to generate more accurate final line groups. For example, if a line in a polarity line group is identified as an abnormal line, it may be separated from the original group to form a new line group, or merged with lines in another group that have similar abnormal characteristics. The final line groups will be a collection of highly consistent internal waveform characteristics, but significantly different waveform characteristics between groups. For example, one group may contain all normally operating lines exhibiting high similarity, while another group or a few groups may contain faulty lines or lines severely affected by the fault, with high internal similarity but significant differences from other groups. These final line groups will be directly used to identify faulty lines in the following sections, because one or more groups will clearly represent the area or line where the fault occurred, thus providing the most reliable and accurate guidance for subsequent fault isolation and recovery operations, greatly improving the accuracy and practicality of fault location.

[0118] In one embodiment, such as Figure 7 As shown, in step S43, the fault location result is determined based on the line group, specifically including:

[0119] S431: If there are distribution lines with opposite first half-wave polarities in the line group, count the number of the corresponding distribution lines respectively.

[0120] Specifically, after obtaining the final line groups, to further determine the fault source, these line groups will be checked again for significant differences in the polarity of the first half-wave. Particular attention will be paid to line groups that were initially identified in the previous steps and may be further refined to have opposite first half-wave polarities. This step involves counting the number of distribution lines contained within each such line group, such as a positive polarity group and a negative polarity group. For example, counting how many lines are in the positive polarity group and how many are in the negative polarity group. In distribution network faults, often only a few lines that are directly faulty or closest to the fault point will exhibit transient waveform polarities that are diametrically opposed to those of non-faulty lines. By counting these lines, this characteristic can be used to provide preliminary clues for identifying the fault range.

[0121] S432: Identify one or more line groups with the fewest number of distribution lines as the fault group containing the faulty line.

[0122] Specifically, after counting the number of lines in different polarity line groups, a core comparison is made to identify one or more line groups containing the fewest distribution lines. Based on the physical characteristics of fault current or voltage transient wave propagation, the fault point is usually located at a certain point in the entire network. This causes the transient signal emitted from that point to exhibit a specific response pattern along the fault path, such as the fewest lines, while lines on other non-faulty paths exhibit a different response pattern with more lines. In distribution network faults, often only a few lines that directly experience the fault or are closest to the fault point will exhibit transient waveform polarities that are diametrically opposed to those of non-faulty lines. Therefore, the line group with the fewest lines is often the one directly connected to the fault point or the area closest to the fault point, and is thus identified as the fault group. For example, if the positive polarity group has 8 lines and the negative polarity group has 2 lines, then the negative polarity group will be identified as the fault group.

[0123] S433: Generate fault line results based on the power distribution lines included in the fault group.

[0124] Specifically, once the faulty line group (e.g., the negative polarity group) is identified, the system directly extracts the identification information of all distribution lines within that faulty group. These extracted distribution lines are then confirmed as the final faulty lines for this fault event. They may be a single line name, such as 10kV Line A, or a combination of multiple lines, such as 10kV Line B and 10kV Line C. This result will be presented to the operator or transmitted to the dispatch system in a clear and unambiguous manner, for example, by highlighting the faulty line on the interface.

[0125] In one embodiment, such as Figure 8 As shown, the fault monitoring method also includes:

[0126] S50: When a fault is detected in the power distribution line, an external positioning signal is injected into the power distribution line through the grounding device.

[0127] Specifically, once a fault in a power distribution line is successfully identified, an active location mechanism is activated to pinpoint the exact location of the fault, such as which tower, branch point, or piece of equipment on the line is faulty. This mechanism uses a dedicated grounding device, such as a pulse injector or signal generator connected to the ground grid, to inject a preset external location signal with specific frequency or waveform characteristics—such as a non-power frequency pulse signal, a high-frequency signal, or a coded signal—into the identified faulty power distribution line. By injecting the signal through the grounding device, the conductivity of the earth's circuit can be fully utilized to effectively excite the faulty line, thereby generating a propagation signal that is easily captured by monitoring equipment, providing a physical basis for subsequent precise segmentation and location.

[0128] S60: Determine whether multiple monitoring points on the power distribution line have received external positioning signals.

[0129] Specifically, after the external positioning signal is injected, multiple monitoring points pre-deployed along the power distribution line—such as distributed fiber optic sensors, remote terminal units (RTUs), or decentralized fault indicators—continuously listen to and detect whether they have received the injected external positioning signal. Each monitoring point records the signal arrival status (received or not received) and sends its status information back to the fault monitoring device. By comparing the signal reception status of different monitoring points, it is possible to intuitively determine where the signal is interrupted, thus initially locating the fault area. This provides a direct and real-time basis for subsequent fault segmentation and location based on signal propagation characteristics, avoiding blind line inspections and greatly improving the efficiency of fault finding.

[0130] S70: If a monitoring point on a power distribution line fails to receive an external location signal, the location of the monitoring point will be determined as the fault location area.

[0131] Specifically, the judgment result indicates which monitoring points received the signal and which did not. By tracing the line, the first monitoring point that failed to receive the external positioning signal is located. Based on the principle that the signal is emitted from the injection point and propagates along the line, if the signal could be received normally before a certain monitoring point but cannot be received at this monitoring point, then the fault point must be located between the previous monitoring point that successfully received the signal and the monitoring point that failed to receive the signal, or on the line immediately in front of the monitoring point that failed to receive the signal. Therefore, the specific geographical location of the monitoring point that failed to receive the external positioning signal, or the line segment immediately upstream, is determined as the most likely fault location area. This provides maintenance personnel with a clear and narrow working range, allowing them to directly dispatch personnel to this specific area for troubleshooting and repair. This significantly shortens the fault duration, reduces the intensity and cost of manual inspections, and plays a crucial role in the rapid response and power restoration of uninterrupted power supply operations.

[0132] The fault monitoring device described in this application achieves fault detection during live-line work by collecting secondary side signals from the incoming and outgoing line bays of the ring main unit in the distribution network. This device supports live installation and removal, and can continuously monitor current and voltage parameters on the secondary side of the incoming and outgoing line bays of the ring main unit in the distribution network, possessing high-precision fault recording capabilities. Specifically, both voltage and current signals are obtained from the secondary side, eliminating the need for operators to contact primary high-voltage equipment. Installation, removal, and data access wiring can be performed while the line is operating normally, making the entire process simple, convenient, and safe. After installation, the device monitors the line's load current and fault signals in real time. When a short circuit or ground fault occurs, the device detects fault characteristics such as sudden current changes, zero-sequence voltage changes, or zero-sequence current changes. Once preset trigger conditions are met, the device immediately initiates high-precision fault recording synchronously across all bays, and analyzes and judges the waveform data through built-in algorithms and edge computing functions to accurately identify the fault type and location, ultimately transmitting the fault information to the main station system via a wireless network.

[0133] Specifically, in this solution, fault monitoring for live-line work is primarily achieved through the innovative fault monitoring device proposed in this application. When a fault is detected in a power distribution line, firstly, based on a multi-channel transient waveform dataset, the polarity of the first half-wave of the transient waveform of each power distribution line is determined. Then, these first half-wave polarities are compared and analyzed. If inconsistencies in polarity are found, the power distribution line is initially divided into at least two polarity line groups with opposite first half-wave polarities. To further improve positioning accuracy, a similarity analysis is performed on the complete transient waveforms of each power distribution line within the same polarity line group. Based on the analysis results, power distribution lines with similarity below a preset threshold are identified. Then, based on these lines, the polarity line groups are further divided to obtain the final line groups with highly consistent internal characteristics. Subsequently, based on the number of power distribution lines in these line groups, one or more line groups with the fewest numbers are identified as the fault group containing the faulty line, thus generating a preliminary fault line result. To achieve more precise segmented positioning of the fault point... This method also includes actively injecting an external location signal into the identified faulty line through a grounding device after a fault is detected. Then, it is determined whether multiple monitoring points along the distribution line receive the external location signal. If any monitoring point fails to receive the signal, the location of that monitoring point or its adjacent upstream line segment is determined as the final location of the fault. Finally, all fault information and precise location results are transmitted in real time to the main station system via wireless communication such as 4G or GPRS, providing power operation and maintenance personnel with a fast and accurate basis for fault handling. This allows for rapid fault location and resolution without interrupting power supply, significantly improving the reliability and operational efficiency of the distribution network.

[0134] It should be understood that the sequence number of each step in the above embodiments does not imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of this application.

[0135] The above-described embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of this application, and should all be included within the protection scope of this application.

Claims

1. A fault monitoring device for live-line operation in power distribution networks, characterized in that, The fault monitoring device for uninterrupted power distribution network operation includes: The acquisition unit is connected to multiple power distribution lines and is used to acquire transient data sequences from each of the power distribution lines. The collection unit, connected to the acquisition unit, is used to receive transient data sequences collected from multiple acquisition units, perform data calculations on the transient data sequences, and obtain fault line location results.

2. The fault monitoring device according to claim 1, characterized in that, The acquisition unit and the aggregation unit maintain time synchronization through a clock synchronization mechanism to ensure the synchronization of the transient data sequence.

3. The fault monitoring device according to claim 1, characterized in that, The aggregation unit further includes a communication module, which is used to encapsulate the fault line location result determined by the aggregation unit into a fault information message and send it to the backend main station server through the communication network.

4. A fault monitoring method for live-line working in a power distribution network, applied to the fault monitoring device as described in any one of claims 1-3, characterized in that, The fault monitoring method includes: Acquire transient data sequences from multiple power distribution lines, wherein the transient data sequences include at least one of transient current sequences and transient voltage sequences; The transient data sequence is monitored to determine whether it meets the preset fault triggering conditions. If the transient data sequence satisfies the fault triggering condition, then based on the transient data sequence, the multi-channel transient waveform dataset of the power distribution line is determined; The multi-channel transient waveform dataset is compared and analyzed, and the fault location result is determined based on the comparison and analysis results.

5. The fault monitoring method according to claim 4, characterized in that, The monitoring of the transient data sequence to determine whether the transient data sequence meets the preset fault triggering conditions specifically includes: Obtain the amplitude of electrical parameters in the transient data sequence, wherein the amplitude of electrical parameters includes at least one of current amplitude and transient voltage amplitude; Based on the electrical parameter amplitude, the difference in electrical parameter amplitude between two adjacent period values ​​in the transient data sequence is calculated, and the electrical parameter change rate is obtained by dividing by the previous period value. When the rate of change of the electrical parameter is detected to exceed a preset amplitude change rate threshold, it is determined whether the amplitude of the electrical parameter at the current moment exceeds the preset amplitude threshold. If the amplitude of the electrical parameter exceeds the preset amplitude threshold, the current time is determined as the fault triggering time point, and the transient data sequence is determined to meet the fault triggering condition.

6. The fault monitoring method according to claim 5, characterized in that, The step of determining the multi-channel transient waveform dataset of the power distribution line based on the transient data sequence specifically includes: Using the fault triggering time point as a time reference, and according to the transient data sequence, a first transient data sequence before the time reference and a second transient data sequence after the time reference are obtained according to a preset time period. The discrete sampling points contained in the first transient data sequence and the second transient data sequence are reconstructed in time sequence to obtain the corresponding transient waveform; Based on the transient waveform, construct the multi-channel transient waveform dataset of the power distribution line.

7. The fault monitoring method according to claim 6, characterized in that, The step of comparing and analyzing the multi-channel transient waveform dataset, and determining the fault location result based on the comparison and analysis results, specifically includes: Based on the multi-channel transient waveform dataset, the polarity of the first half-wave of the transient waveform is determined; The polarity of the first half of the transient waveform is compared and analyzed. Based on the comparison and analysis results, the power distribution lines are divided to obtain line groups. Based on the aforementioned line group, the location result of the faulty line is determined.

8. The fault monitoring method according to claim 7, characterized in that, The process of dividing the power distribution lines into line groups based on the comparison and analysis results specifically includes: Based on the comparison and analysis results, if there is a situation where the polarity of the first half wave of the transient waveform of the power distribution line is inconsistent, the power distribution line is divided to obtain at least two polarity line groups, wherein the at least two polarity line groups have opposite first half wave polarities. A similarity analysis is performed on the transient waveforms of the various power distribution lines grouped under the same polarity. Based on the similarity analysis results, power distribution lines with similarity below a preset similarity threshold are identified from the same polarity line group. Based on the power distribution lines, the polarity line groups are divided to obtain the final line groups.

9. The fault monitoring method according to claim 7, characterized in that, The step of determining the faulty line location result based on the line group specifically includes: If there are distribution lines with opposite first half-wave polarities in the line group, then count the number of the corresponding distribution lines respectively. The group of one or more power distribution lines with the fewest number of lines is identified as the fault group containing the faulty line. The fault location result is generated based on the power distribution lines included in the fault group.

10. The fault monitoring method according to claim 4, characterized in that, The fault monitoring method further includes: When a fault is detected in the power distribution line, an external positioning signal is injected into the power distribution line through the grounding device; Determine whether multiple monitoring points of the power distribution line have received the external positioning signal; If a monitoring point on the power distribution line fails to receive the external positioning signal, the location of the monitoring point will be determined as the location area of ​​the fault.

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