Distribution network cable early fault positioning method based on zero sequence and grounding wire current correlation difference

Abstract

The invention discloses a distribution network cable early fault positioning method based on zero sequence and grounding wire current correlation difference, which comprises the following steps: acquiring zero sequence current and grounding wire current at the head end of each cable section, intercepting data windows of four power frequency periods by taking a fault triggering moment as a starting point when a single-phase grounding early arc fault is judged to occur, adopting fast Fourier transform and inverse transform to extract a seventh harmonic component and constructing a time domain waveform; constructing a discrete Lissajous curve, calculating a loopback area by using a shoelace formula, constructing an energy index and a self-adaptive energy threshold by combining the standard deviation of the two currents, and eliminating a section with insufficient harmonic energy; the effective section loopback area is normalized, and the section with the minimum normalized loopback area is selected from the suspected fault sections to be judged as the fault section according to the clustering result of the original loopback area, so that the early fault section of the cable can be quickly positioned, hidden dangers can be eliminated in time, and the reliability of the cable is improved. And operation safety and power supply reliability of the power distribution network are ensured.

Description

Technical Field

[0001] This invention belongs to the field of power system relay protection and fault diagnosis technology, specifically referring to a method for locating early faults in distribution network cables based on the difference in correlation between zero-sequence and grounding currents. Background Technology

[0002] With the continuous improvement of cable coverage in power distribution networks, cable lines are widely used in 10kV and other medium-voltage distribution networks to supply power to urban load centers, industrial parks, and important users. These cable lines have long laying paths and many branches, some passing through enclosed or semi-enclosed environments such as underground utility tunnels and pipe galleries. They are subject to long-term exposure to factors such as humidity, heat accumulation, mechanical vibration, external pressure, and construction defects, making the cable insulation prone to localized aging, moisture absorption, and mechanical damage, thus inducing early arc faults such as single-phase grounding. Early faults typically manifest as multi-cycle or half-cycle arcs, with small fault current amplitudes, short durations, and rapid changes in equivalent arc resistance, placing higher demands on fault monitoring and location.

[0003] In medium-voltage distribution networks, to limit single-phase ground fault current, reduce equipment insulation levels, and improve system transient stability, neutral-point non-effectively grounded operation is commonly adopted in engineering projects. In such systems, the single-phase ground fault current mainly consists of ground capacitance current and compensation device current, with an amplitude significantly lower than that of effectively grounded systems. Furthermore, the fault current waveform is significantly affected by factors such as system topology, compensation degree, load operating conditions, and arc conduction characteristics, exhibiting strong nonlinearity and distortion characteristics. Traditional segment location methods relying on the amplitude and phase relationship of power frequency zero-sequence voltage and zero-sequence current are significantly insufficient in sensitivity and stability for early arc faults under non-effectively grounded conditions, easily leading to misjudgments and missed detections. On the other hand, impedance methods and traveling wave methods based on accurate network parameters and equivalent impedance are difficult to model in actual distribution networks with numerous feeders, complex branch structures, and incomplete parameters. They are also sensitive to parameter errors and changes in operating conditions, exhibiting poor robustness. Moreover, these methods typically require high-sampling-rate measurement devices at both ends or multiple ends of the line, and rely on high-precision time synchronization and high-bandwidth, high-reliability communication systems to achieve centralized processing of multi-end measurement data. For existing distribution networks, the number of existing feeder automation terminals is limited, and communication conditions are constrained by communication methods, environmental conditions, and maintenance levels. Deploying multi-end synchronous measurement and high-bandwidth data exchange systems across the entire network is costly and difficult to implement, making it difficult to form a unified and reliable engineering application solution. Furthermore, the above methods are mostly aimed at permanent faults with large fault current amplitudes and long durations. For early arc faults with small current amplitudes and short durations, the transient characteristics are not significant enough, and the location results are easily affected by noise and operating conditions.

[0004] Furthermore, offline fault location devices for cables, such as pulse reflection and impedance ranging methods, are mostly used for accurate distance measurement of permanent faults after power outages. They cannot achieve online monitoring and section location of early single-phase grounding faults during operation. In actual engineering projects, after an early single-phase grounding fault occurs in a non-effectively grounded distribution network, maintenance personnel usually rely on limited zero-sequence quantity criteria for preliminary line selection, and then combine experience and manual line inspection to check suspicious cables section by section. The process of determining the fault section is time-consuming and labor-intensive, making it difficult to eliminate hidden dangers in a timely manner, and has an adverse impact on operational safety and power supply reliability. Summary of the Invention

[0005] The purpose of this invention is to propose a method for locating early faults in distribution network cables based on the difference in correlation between zero-sequence and grounding currents. This method can quickly locate early fault sections in cables, eliminate hidden dangers in a timely manner, and ensure the operational safety and power supply reliability of the distribution network.

[0006] To achieve the above objectives, the present invention provides a method for early fault location in distribution network cables based on the difference in correlation between zero-sequence and grounding currents, comprising the following steps: Step 1) Real-time acquisition of zero-sequence current and grounding current at the beginning of each section of the distribution network using measuring devices installed at the beginning of each line segment; After a fault occurs, the fault trigger time is used as the basis for determining the fault location method. t fault Starting from this point, zero-sequence current data for four power frequency cycles of each section are extracted. i 0( t ) and grounding current data i g ( t This forms the data analysis window; Step 2) Perform preprocessing and frequency domain frequency selection processing on the zero-sequence current and grounding current of each segment in the analysis data window, extract the harmonic components of the seventh harmonic, and construct the time-domain waveform corresponding to the harmonic component. Step 3) For each segment, construct a discrete Lissajous trajectory in a two-dimensional plane with the seventh harmonic zero-sequence current as the X-axis and the seventh harmonic grounding wire current as the Y-axis. Step 4) Calculate the area of ​​the directed loop of the Lissajous curve; Step 5) Calculate the standard deviation of the seventh harmonic zero-sequence current and the seventh harmonic grounding current in each cable section, and perform energy verification. Step 6) Normalize the loop area in Step 4) to obtain the normalized loop area that characterizes the linear correlation between the zero-sequence current and the ground wire current. Step 7) For the valid segments that pass the energy criterion screening, i.e. the segments that pass the energy verification in Step 5), cluster them into two classes based on the original loop closure area. Define the class with the larger mean of the original loop closure area as the suspected fault cluster, and select the segment with the smallest normalized loop closure area in this cluster as the fault segment.

[0007] As a further aspect of the present invention: step 2) specifically includes the following steps: 2.1) For each segment k The signal within the analysis window is de-meaned to eliminate DC drift, and a Hann window is added to reduce spectral leakage. 2.2) Perform a Fast Fourier Transform on the processed zero-sequence current and grounding current signals to obtain the spectra of the zero-sequence current and grounding current signals in each segment. and ; 2.3) In the spectrum, only the spectral values ​​at the seventh harmonic and its conjugate symmetrical frequency points are retained, and the remaining frequency points are set to zero to obtain a spectrum containing only the seventh harmonic; 2.4) Perform inverse fast Fourier transform on the processed seventh harmonic spectrum to obtain the zero-sequence current time-domain sequence and the ground wire current time-domain sequence containing only the seventh harmonic in each segment.

[0008] As a further aspect of the present invention: in step 3), the step of constructing the discrete Lissajous trajectory is as follows: 3.1) will i 0,k,7 [ n As the X-axis, i g,k,7 [ n Using the Y-axis, for each sampling point 𝑛, define a plane point. P k,n : ; in, The seventh harmonic zero-sequence current within the window n The instantaneous value of each sampling point. The seventh harmonic grounding wire current within the window n The instantaneous values ​​of each sampling point are used to obtain an ordered point sequence. ; 3.2) Connect them in chronological order to construct the discrete Lissajous trajectory for each segment.

[0009] As a further aspect of the present invention: in step 4), the area of ​​the directed loop of the Lissajous curve is calculated using the polygonal discrete shoelace formula. A k : ; Among them, by defining the signal's first... N w The value of +1 sampling point is equal to the value of the first sampling point, that is, set and To achieve periodic connection of signals in the time domain, the absolute value of the area of ​​the directed loop is taken. As a section k The area of ​​the Lissajous loop.

[0010] As a further aspect of the present invention: step 5) specifically includes the following steps: 5.1) Calculate the standard deviation σ for the seventh harmonic zero-sequence current and grounding current in each section. 0,k and σ g,k ; 5.2) Calculate the energy index of each segment in the seventh harmonic frequency band. E k : ; 5.3) For all sections E k Take the maximum value E max ; 5.4) Take the proportionality coefficient γ = 0.002 and define the energy threshold. : ; 5.5) Energy Verification Rules: ; When the energy index of a segment is greater than the energy threshold, the seventh harmonic signal of that segment is considered valid; when the energy index of a segment is not greater than the energy threshold, the seventh harmonic signal of that segment is considered invalid due to insufficient energy, to prevent the denominator from being zero when calculating the normalized loop area.

[0011] As a further aspect of the present invention: in step 6), the formula for calculating the normalized loop area is: ; The Lissajous loop area is normalized to eliminate the influence of current amplitude on the area.

[0012] As a further aspect of the present invention: In step 7), for all valid cable sections... k Based on the original Lissajous loop area of ​​each segment As a clustering feature, adopt k The mean clustering algorithm divides the effective segment into two classes, and defines the cluster with the larger original Lissajous loop area as the suspected fault cluster, and selects the normalized Lissajous loop area within the suspected fault cluster. A norm,k The smallest segment is designated as the faulty segment.

[0013] The aforementioned early fault location method relies on an early fault location device, which includes a sampling module, a storage module, a communication module, a power supply module, and a main control module. The power supply module supplies power to the other modules, and the main control module controls the sampling module, storage module, and communication module respectively, and calls the program instructions stored in the storage unit to execute the steps of the aforementioned early fault location method on the zero-sequence current and grounding current data collected by the sampling module. Specifically, the sampling module is used to sample the zero-sequence current and grounding current at the beginning of each cable section of the distribution network to obtain digital measurement data for fault analysis; the storage module is used to store the zero-sequence current and grounding current data at the beginning of each cable line in the distribution network, the fault trigger time, and intermediate calculation results such as the normalized Lissajous loop area; the communication module is used to realize data communication between the early fault section location device and an external master station, including uploading measurement data and calculation results and receiving control commands.

[0014] A system employing the aforementioned early fault location method is characterized by comprising: a zero-sequence current and grounding current measuring device, an early fault location device, a communication network, and a master station; the measuring device is a high-precision current transformer used to measure the zero-sequence current and grounding current at the beginning of a cable section; the early fault location device is used to calculate the normalized Lissajous curve loop area based on the early fault location method for distribution network cables according to the correlation difference between the zero-sequence and grounding currents; the communication network connects the early fault location device to the master station; and the master station is used to execute all valid cable sections... k The fault section identification function displays the waveforms of the zero-sequence current and grounding current in the faulty cable section, as well as the location of the faulty section.

[0015] Compared with existing technologies, the beneficial effects of this invention are as follows: Within a limited time window after a fault is triggered, this invention extracts the seventh harmonic component and constructs a Lissajous loop trajectory using only the directly measurable zero-sequence current and grounding current at the beginning of each cable section. The correlation strength between the two currents in the same frequency band is quantitatively characterized by the normalized loop area, transforming the complex coupling relationship into a geometric index with clear physical meaning, thus achieving a significant and stable distinction between faulty and healthy sections. This criterion is highly sensitive to waveform distortion caused by the fault conduction path and early arcing, but relatively insensitive to changes in line length, load operation mode, and transition resistance. It can be applied simultaneously to various early fault conditions such as multi-cycle arcing and half-cycle arcing. By selecting the seventh harmonic in the frequency domain and combining it with an energy threshold based on standard deviation to eliminate insufficient energy sections, it effectively suppresses power frequency steady-state components and noise interference, improving the robustness and anti-interference capability of the location results. Because this invention relies only on single-end measurement of a section, it does not require synchronous measurement at both ends or multiple ends of the line, nor does it rely on high-precision time synchronization and high-bandwidth communication networks. It does not require precise network parameters and complex equivalent modeling. The algorithm structure is simple and the computational load is small. It is easy to implement online deployment on the basis of existing power distribution automation and monitoring systems. It can quickly locate early fault sections of cables, eliminate hidden dangers in a timely manner, and ensure the operational safety and power supply reliability of the power distribution network. Attached Figure Description

[0016] Figure 1 This is a flowchart of the method for locating early faults in distribution network cables based on the correlation difference between zero-sequence and grounding currents according to the present invention.

[0017] Figure 2 This is a topology diagram of a 10kV neutral-point grounded distribution network simulation model constructed in an embodiment of the present invention, wherein... L A schematic diagram of the topology where early arcing faults occur in two segments.

[0018] Figure 3 This is a topology diagram of a 10kV neutral-point grounded distribution network simulation model constructed in an embodiment of the present invention, wherein... L 10 A topology diagram showing the occurrence of early arcing faults in a segment. Detailed Implementation

[0019] The invention will now be further described with reference to the accompanying drawings.

[0020] like Figure 1 As shown, the method for locating early faults in distribution network cables based on the difference in the correlation between zero-sequence and grounding currents includes the following steps: Current acquisition devices are installed at the beginning of each cable section in the distribution network to collect zero-sequence current and grounding current signals in real time. After a fault occurs, an analysis data window with a length of four power frequency cycles is extracted from the zero-sequence current and grounding current sequences of each section. Let the power frequency be... f 0, sampling frequency is f s The data window length is T w Then the number of window data samples N w for: ; The principle of constructing the analysis data window by extracting the zero-sequence current and grounding current data of each section for four power frequency cycles is as follows: early cable faults can be divided into half-cycle early faults and multi-cycle early faults according to the duration of the fault. The former lasts for about 1 / 4 cycle, and the latter lasts for about 1 to 4 cycles. The data window length of four power frequency cycles covers both half-cycle early faults and multi-cycle early faults.

[0021] After preprocessing the zero-sequence current and grounding current in each data window such as mean removal and windowing, a fast Fourier transform is performed. The frequency point corresponding to the seventh harmonic is determined according to the power frequency and sampling frequency. Only the frequency point and its conjugate frequency point are retained, and the amplitude of other frequency points is set to zero. Then, the time-domain waveforms of the zero-sequence current and grounding current containing only the seventh harmonic component are constructed through inverse transform. Using the seventh harmonic zero-sequence current as the X-axis and the seventh harmonic grounding wire current as the Y-axis, the sampling points within the data window are mapped onto a plane in chronological order, forming the seventh harmonic Lissajous loop trajectory for each segment. The area of ​​the Lissajous loop in each segment is calculated using the discrete shoelace formula. ; Among them, by defining the signal's first... N w The value of +1 sampling point is equal to the value of the first sampling point, that is, set and To achieve periodic connection of signals in the time domain, the absolute value of the area of ​​the directed loop is taken. As a section k The area of ​​the Lissajous loop.

[0022] An energy index is constructed based on the standard deviation of the seventh harmonic zero-sequence current and the grounding wire current: ; Where, σ 0,k σ is the standard deviation of the seventh harmonic zero-sequence current. g,k The standard deviation of the seventh harmonic grounding wire current. , These are the average values ​​of the zero-sequence current sample and the ground wire current sample, respectively.

[0023] Furthermore, an adaptive energy threshold is set: ; Sections with seventh harmonic energy below the adaptive threshold are marked as invalid sections to prevent the denominator from being zero when calculating the normalized loop area. For the remaining effective sections, the Lissajous curve loop area of ​​the section is normalized using the standard deviation of the seventh harmonic zero-sequence current and the grounding wire current: ; The normalized Lissajous loop area index is obtained and used to eliminate the influence of amplitude differences; For those selected by energy criteria m Valid segments k Let the area of ​​its original Lissajous loop be . A k ( k =1,2,…, m To mitigate the impact of extreme large values, a one-dimensional clustering feature is first constructed: ; by{ z k Using samples as examples, a binary k-means clustering algorithm is employed in the one-dimensional feature space to divide the effective segments into two classes. C 1 and C 2. Its clustering objective function is: ; The class center satisfies: ; After clustering, the cluster with the largest original Lissajous loop area is defined as a suspected fault cluster. Within this suspected fault cluster, the cluster is further divided based on the normalized Lissajous loop area. A norm,k Perform discrimination and select A norm,k The smallest segment is designated as the faulty segment.

[0024] The application of early fault location methods for distribution network cables based on the correlation difference between zero-sequence and grounding currents relies on fault location devices and fault location systems. The fault location devices include: The sampling module is used to sample the zero-sequence current and grounding current at the beginning of each cable section of the distribution network to obtain digital measurement data for fault analysis. The storage module is used to store data on zero-sequence current and grounding current at the beginning of each cable line in the distribution network, fault triggering time, and intermediate calculation results such as normalized Lissajous loop area. The communication module is used to enable data communication between the early fault section location device and the external master station, including uploading measurement data and calculation results and receiving control commands; The power module is used to provide operating power to the various functional modules inside the early fault section location device; The main control module is used to call the program instructions stored in the storage unit to perform the steps of the method for early fault location of distribution network cables by utilizing the correlation difference between zero-sequence current and ground wire current on the zero-sequence current and ground wire current data collected by the sampling module.

[0025] The fault location system includes: The zero-sequence current and grounding current measuring device is configured as a high-precision current transformer and its matching sampling circuit, and is installed at the beginning of each cable section of the distribution network to measure and output the zero-sequence current and grounding current at the beginning of each cable section. An early fault section location device is used to process data from zero-sequence current and grounding current measurement devices to calculate the normalized Lissajous loop area of ​​each cable section, based on the method for locating early faults in distribution network cables according to the difference in the correlation between zero-sequence current and grounding current. The communication network is used to establish a data transmission channel between the early fault location device and the main station to achieve reliable transmission of sampled data, control commands and calculation results; The main station is used to receive the current data and calculation results of each section uploaded by the early fault section location device, complete the comparison of each section and the comprehensive judgment of the fault section, and display the zero-sequence current and ground wire current waveforms of the fault cable section, the fault occurrence time and the location of the fault section in the distribution network topology.

[0026] This embodiment is built in PSCAD / EMTDC as follows: Figure 2 , Figure 3 The simulation model of the neutral-point grounded distribution network shown has a power frequency of 50Hz, a current sampling frequency of 200kHz, and uses cable laying with feeder lengths ranging from 1 to 5km, comprising 12 cable sections. Zero-sequence current and grounding current measurement points are configured at the beginning of each cable section to collect the single-end current required by the method of this invention.

[0027] Early cable faults were simulated using the Cassie arc model, simulating two types of early faults: multi-cycle arcs and half-cycle arcs. Faults were set at different fault locations. For each fault scenario, an analysis data window of four power frequency cycles was first extracted based on the fault trigger time. Preprocessing and seventh harmonic frequency band selection were performed on the zero-sequence current and grounding current at the beginning of each section, constructing the seventh harmonic Lissajous trajectory, calculating the normalized Lissajous loop area index, and eliminating invalid sections with insufficient seventh harmonic energy using the seventh harmonic energy threshold criterion. Finally, the section with the smallest normalized loop area was selected as the fault section through clustering. Some results under typical simulation conditions are shown in Table 1; the code output of the first set of experiments is shown in Table 2, and the fault location effect is as follows: Figure 2 As shown. Figure 2 In the middle, corresponding to the first group of experiments, Figure 3 The fault section was changed while keeping other conditions unchanged. Table 3 shows the location results after superimposing high-frequency noise on the original waveforms of the first set of tests.

[0028] Table 1. Segment location results under different fault conditions

[0029] Table 2 shows the specific code execution results.

[0030] Table 3. Localization results after adding noise

[0031] Tables 1, 2, and 3 show that under different fault types, fault durations, fault locations, and noise interference, the method of this invention consistently results in a normalized loop-around area for the faulted section that is significantly smaller than the minimum normalized loop-around area for all healthy sections, and the section identification results are all correct. Simulation results demonstrate that this method is insensitive to fault type and exhibits good section identification capabilities under both multi-cycle and half-cycle arc early fault conditions, enabling rapid and reliable section location of early cable faults in neutral-point non-effectively grounded distribution networks.

[0032] The invention has been described and verified above with reference to typical simulation conditions, demonstrating its basic principles, main features, and beneficial effects. This invention is not limited to the specific embodiments described above. Any equivalent substitutions or modifications made to the system topology, parameter values, harmonic order selection, threshold setting methods, etc., without departing from the spirit and scope of this invention, shall fall within the scope of protection defined by the claims of this invention.

Claims

1. A method for locating early faults in distribution network cables based on the difference in correlation between zero-sequence and grounding currents, characterized in that, Includes the following steps: Step 1) Use measuring devices installed at the beginning of each line section to collect the zero-sequence current and grounding current at the beginning of each section of the distribution network in real time; after a fault, use the fault trigger time... t fault Starting from this point, zero-sequence current data for four power frequency cycles of each section are extracted. i 0( t ) and grounding current data i g ( t This forms the data analysis window; Step 2) Perform preprocessing and frequency domain frequency selection processing on the zero-sequence current and grounding current of each segment in the analysis data window, extract the harmonic components of the seventh harmonic, and construct the time-domain waveform corresponding to the harmonic component. Step 3) For each segment, construct a discrete Lissajous trajectory in a two-dimensional plane with the seventh harmonic zero-sequence current as the X-axis and the seventh harmonic grounding wire current as the Y-axis. Step 4) Calculate the area of ​​the directed loop of the Lissajous curve; Step 5) Calculate the standard deviation of the seventh harmonic zero-sequence current and the seventh harmonic grounding current in each cable section, and perform energy verification. Step 6) Normalize the loop area in Step 4) to obtain the normalized loop area that characterizes the linear correlation between the zero-sequence current and the ground wire current. Step 7) For the valid segments that pass the energy criterion screening, i.e. the segments that pass the energy verification in Step 5), cluster them into two classes based on the original loop closure area. Define the class with the larger mean of the original loop closure area as the suspected fault cluster, and select the segment with the smallest normalized loop closure area in this cluster as the fault segment.

2. The method for locating early faults in distribution network cables based on the difference in correlation between zero-sequence and grounding currents according to claim 1, characterized in that, Step 2) specifically includes the following steps: 2.1) For each segment k The signal within the analysis window is de-meaned to eliminate DC drift, and a Hann window is added to reduce spectral leakage. 2.2) Perform a Fast Fourier Transform on the processed zero-sequence current and grounding current signals to obtain the spectra of the zero-sequence current and grounding current signals in each segment. and ; 2.3) In the spectrum, only the spectral values ​​at the seventh harmonic and its conjugate symmetrical frequency points are retained, and the remaining frequency points are set to zero to obtain a spectrum containing only the seventh harmonic; 2.4) Perform inverse fast Fourier transform on the processed seventh harmonic spectrum to obtain the zero-sequence current time-domain sequence and the ground wire current time-domain sequence containing only the seventh harmonic in each segment.

3. The method for locating early faults in distribution network cables based on the difference in correlation between zero-sequence and grounding currents according to claim 1, characterized in that, In step 3), the steps for constructing the discrete Lissajous trajectory are as follows: 3.1) will i 0,k,7 [ n As the X-axis, i g,k,7 [ n Using the Y-axis, for each sampling point 𝑛, define a plane point. P k,n : ； in, The seventh harmonic zero-sequence current within the window n The instantaneous value of each sampling point The seventh harmonic grounding wire current within the window n The instantaneous values ​​of each sampling point are used to obtain an ordered sequence of points. ; 3.2) Connect them in chronological order to construct the discrete Lissajous trajectory for each segment.

4. The method for locating early faults in distribution network cables based on the difference in correlation between zero-sequence and grounding currents according to claim 1, characterized in that, In step 4), the area of ​​the directed loop of the Lissajous curve is calculated using the polygonal discrete shoelace formula. A k : ； Among them, by defining the signal's first... N w The value of +1 sampling point is equal to the value of the first sampling point, that is, set and To achieve periodic connection of signals in the time domain, the absolute value of the area of ​​the directed loop is taken. As a section k The area of ​​the Lissajous loop.

5. The method for locating early faults in distribution network cables based on the difference in correlation between zero-sequence and grounding currents according to claim 1, characterized in that, Step 5) specifically includes the following steps: 5.1) Calculate the standard deviation σ for the seventh harmonic zero-sequence current and grounding current in each section. 0,k and σ g,k ; 5.2) Calculate the energy index of each segment in the seventh harmonic frequency band. E k : ； 5.3) For all sections E k Take the maximum value E max ; 5.4) Take the proportionality coefficient γ = 0.002 and define the energy threshold. : ； 5.5) Energy Verification Rules: ； When the energy index of a segment is greater than the energy threshold, the seventh harmonic signal of that segment is considered valid; when the energy index of a segment is not greater than the energy threshold, the seventh harmonic signal of that segment is considered invalid due to insufficient energy, to prevent the denominator from being zero when calculating the normalized loop area.

6. The method for locating early faults in distribution network cables based on the difference in correlation between zero-sequence and grounding currents according to claim 1, characterized in that, In step 6), the formula for calculating the normalized loop area is: ； The Lissajous loop area is normalized to eliminate the influence of current amplitude on the area.

7. The method for locating early faults in distribution network cables based on the difference in correlation between zero-sequence and grounding currents according to claim 1, characterized in that, In step 7), for all valid cable sections k Based on the original Lissajous loop area of ​​each segment As a clustering feature, adopt k The mean clustering algorithm divides the effective segment into two classes, and defines the cluster with the larger original Lissajous loop area as the suspected fault cluster, and selects the normalized Lissajous loop area within the suspected fault cluster. A norm,k The smallest segment is designated as the faulty segment.

8. The early fault location method according to any one of claims 1 to 7, characterized in that, This method relies on an early fault location device, which includes a sampling module, a storage module, a communication module, a power supply module, and a main control module. The power supply module supplies power to the other modules, and the main control module controls the sampling module, storage module, and communication module respectively, and calls the program instructions stored in the storage unit to execute the steps of the early fault location method according to any one of claims 1 to 7 on the zero-sequence current and grounding current data collected by the sampling module. Specifically, the sampling module samples the zero-sequence current and grounding current at the beginning of each cable section of the distribution network to obtain digital measurement data for fault analysis; the storage module stores the zero-sequence current and grounding current data at the beginning of each cable line in the distribution network, the fault trigger time, and intermediate calculation results such as the normalized Lissajous loop area; the communication module enables data communication between the early fault section location device and an external master station, including uploading measurement data and calculation results and receiving control commands.

9. A system employing the early fault location method as described in any one of claims 1 to 7, characterized in that, It includes a zero-sequence current and grounding current measuring device, an early fault location device, a communication network, and a master station; the measuring device is a high-precision current transformer used to measure the zero-sequence current and grounding current at the beginning of the cable section. An early fault location device is used to calculate the normalized Lissajous curve loop area based on the early fault location method for distribution network cables according to the difference in the correlation between the zero-sequence and grounding currents. The communication network connects the early fault location device to the main station. The master station is used to execute all valid cable sections. k The fault section identification function displays the waveforms of the zero-sequence current and grounding current in the faulty cable section, as well as the location of the faulty section.

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