Power distribution network cable fault point location method and system, computer device and medium

Abstract

A power distribution network cable fault point location method and system, a computer device and a medium, belonging to the technical field of power distribution networks. The location method comprises: S101, when a cable has a fault, a transient signal of a wide-area frequency band is generated, a fault traveling wave containing high-frequency components; a traveling wave line mode component having a relatively small chromatic dispersion is used to perform measurement; decoupling an extracted fault traveling wave signal; S102: the traveling wave voltage and current will have a sharp change when the traveling wave generated by the fault point reaches a measurement end, and the traveling wave head can appear as a high-frequency sudden change in a time-frequency graph, the sudden change point being the position of the wave head; S103: performing EEMD decomposition on the fault traveling wave line mode component, and extracting a first IMF component for Hilbert transform to obtain a time-frequency graph thereof, a sampling moment corresponding to the position of a first frequency sudden change point on the time-frequency graph being the arrival time of the fault traveling wave head; and using a double-end fault location algorithm to calculate a distance with respect to the fault point. The result of the location method has relatively high precision, and, compared with the actual fault position, has a relative error not more than 4%.

Description

Distribution network cable fault point distance measurement method, system, computer equipment and medium Technical Field

[0001] The present invention belongs to the technical field of distribution networks, and in particular relates to a method, system, computer equipment and medium for measuring distance to a cable fault point in a distribution network. Background Art

[0002] With the development of distribution networks and the advancement of urbanization, power cables are gradually replacing overhead lines in large numbers in urban distribution systems. Since cables are typically laid underground in cable trenches, visual inspection of the fault point after a fault occurs is impossible, making troubleshooting and locating the fault difficult and impacting system power supply reliability and operational safety. Traditional power cable fault location measurement relies primarily on offline measurement. The biggest drawback of this method is that some faults are difficult to reproduce under high-voltage impulses, resulting in measurement failures. Furthermore, repeated injection of high-voltage pulses can shorten the lifespan of the entire cable. Current practical cable fault location methods primarily involve shutting down the faulty cable and then injecting pulses. This method suffers from poor real-time performance, does not meet the requirements for intelligent power line operation, and is detrimental to the development of smart grids. The traveling wave method, based on traveling wave transmission theory, utilizes the refraction and reflection phenomena of traveling waves propagating through the line to perform distance measurement. Using the fault traveling wave method for cable fault location is theoretically possible in real time. Furthermore, since it utilizes the fault traveling wave generated by the fault point itself for distance measurement, it eliminates the need for additional signal generation equipment, making it convenient and fast. Therefore, online fault traveling wave ranging has incomparable advantages over offline type and is the focus and direction of cable fault ranging research.

[0003] The traveling wave method is a ranging method based on traveling wave transmission theory. It utilizes the refraction and reflection phenomena of traveling waves propagating through a line to perform ranging. Accurately calibrating the traveling wave head at the moment it reaches the measurement end and determining the traveling wave velocity are key to traveling wave ranging. Current research primarily uses wavelet analysis to extract the fault traveling wave head. However, wavelet analysis results are affected by factors such as the type of wavelet basis, sampling rate, and decomposition scale. Theoretically, wavelet transforms have an infinite number of wavelet bases. Without a thorough analysis of their characteristics and the selection of appropriate wavelet basis functions based on the characteristics of the traveling wave signal, satisfactory results are difficult to obtain. The empirical mode decomposition (EMD) method is an adaptive decomposition algorithm that can effectively analyze and process non-stationary signals. It can effectively separate the frequency components of non-stationary signals. This algorithm overcomes the shortcomings of wavelet analysis, which require manual selection of wavelet bases and decomposition scales, and has found application in non-stationary signal processing. However, EMD suffers from modal aliasing, where a single intrinsic mode function (IMF) component contains widely varying characteristic time scales, or similar characteristic time scales are distributed across different IMF components. This results in low accuracy in fault traveling wave head signal identification and large errors in fault location. Technical issues

[0004] Through the above analysis, the problems and defects of the existing technology are as follows: the existing technology uses the traditional empirical mode decomposition algorithm, which is prone to modal aliasing, affecting the calibration of the arrival time of the fault traveling wave head, resulting in low accuracy of the algorithm's fault ranging and large errors. Technical Solutions

[0005] In view of the problems existing in the prior art, the present invention provides a method, system, computer equipment and medium for measuring the distance to a distribution network cable fault point.

[0006] The present invention is implemented as follows: a method for measuring the distance to a distribution network cable fault point, the method comprising the following steps:

[0007] In the first step, a wide-band transient signal is generated when a cable fault occurs. The fault traveling wave contains high-frequency components, and the traveling wave line mode component with smaller dispersion is used for detection. The extracted fault traveling wave signal is decoupled.

[0008] In the second step, when the traveling wave generated by the fault point reaches the measurement end, both the traveling wave voltage and current will change sharply. The traveling wave head will appear as a high-frequency mutation in the time-frequency diagram, and the mutation point is the wave head position. EEMD decomposition is performed on the fault traveling wave line mode component, and the first IMF component is extracted and Hilbert transformed to obtain its time-frequency diagram. The sampling time corresponding to the first frequency mutation point on the time-frequency diagram is the arrival time of the fault traveling wave head.

[0009] The third step is to calculate the distance to the fault point using the dual-terminal ranging algorithm.

[0010] Furthermore, the first step specifically includes: decoupling the extracted fault traveling wave signal by using Karen Bell transform.

[0011] The decoupling process is as follows:

[0012] ;

[0013] ;

[0014] In the formula 、 、 are the three-phase currents of the line respectively; 、 、 are the decoupled 0-mode current, α-mode current, and β-mode current components, respectively. α-mode and β-mode are both called line-mode components, and the velocity equations of traveling waves at different modes are obtained:

[0015] ;

[0016] in 、 and 、 They are the zero mode and line mode parameters of the cable line respectively.

[0017] Furthermore, the second step specifically includes: identifying the fault traveling wave head, using the EEMD algorithm, superimposing Gaussian white noise on the original signal, performing multiple EMD decompositions, and taking the mean of the IMF components as the final result;

[0018] 1) Give the signal to be analyzed Add white noise;

[0019] 2) Perform EMD decomposition to decompose the noisy signal and obtain the individual IMFs;

[0020] 3) Repeat steps 1) and 2) but add different white noise each time;

[0021] 4) Take the mean of each IMF component obtained from multiple decompositions as the final result.

[0022] Furthermore, the second step specifically includes: calibrating the fault traveling wave head using the Hilbert transform algorithm:

[0023] set up is a time series, is its Hilbert transform, namely:

[0024] ;

[0025] Its inverse transform is:

[0026] ;

[0027] Get the parsed signal:

[0028] ;

[0029] Where: is the instantaneous amplitude, ;

[0030] is the phase, The instantaneous frequency is defined as:

[0031] ;

[0032] That is, analytical signal The derivative of the phase.

[0033] Furthermore, in the second step, the collected fault traveling wave signal is decomposed by EEMD to obtain a series of inherent modal components containing only one vibration mode, and then the first IMF component is Hilbert transformed to obtain the instantaneous frequency of this IMF component. The mutation point of the instantaneous frequency is the wave head of the collected fault traveling wave.

[0034] Furthermore, the third step specifically includes: in the two-terminal ranging algorithm, F is the fault point, t1 and t2 are the time it takes for the fault traveling wave to reach the M end and the N end respectively, L is the total length of the cable, and v is the traveling wave velocity. The cable fault location equation is derived as follows:

[0035] .

[0036] Another object of the present invention is to provide a computer device, which includes a memory and a processor, wherein the memory stores a computer program, and when the computer program is executed by the processor, the processor executes the distribution network cable fault point distance measurement method.

[0037] Another object of the present invention is to provide a computer-readable storage medium storing a computer program, which, when executed by a processor, enables the processor to execute the distribution network cable fault point distance measurement method.

[0038] Another object of the present invention is to provide an information data processing terminal, which is used to implement the distribution network cable fault point distance measurement method.

[0039] Another object of the present invention is to provide a distribution network cable fault point distance measurement system based on the distribution network cable fault point distance measurement method, the distribution network cable fault point distance measurement system comprising:

[0040] The traveling wave line mode component extraction module is used to extract the fault traveling wave signal from the wide-band transient signal generated when the cable fault occurs. The fault traveling wave contains high-frequency components, and the traveling wave line mode component with smaller dispersion is used for detection; the extracted fault traveling wave signal is decoupled;

[0041] The fault traveling wave head identification and calibration module is used to detect the arrival time of the fault traveling wave head. When the traveling wave generated by the fault point reaches the measurement end, the traveling wave voltage and current will undergo sharp changes. The traveling wave head will appear as a high-frequency mutation in the time-frequency diagram, and the mutation point is the wave head position. EEMD decomposition is performed on the fault traveling wave line mode component, and the first IMF component is extracted and Hilbert transformed to obtain its time-frequency diagram. The location of the first frequency mutation point on the time-frequency diagram is the arrival time of the fault traveling wave head.

[0042] The fault point distance calculation module is used to calculate the distance of the fault point in the cable using a two-end ranging algorithm. Beneficial effects

[0043] In combination with the above technical solutions and the technical problems solved, the advantages and positive effects of the technical solutions to be protected by the present invention are as follows:

[0044] First, the cable fault distance measurement method based on the EEMD algorithm proposed in the present invention is simple and feasible, and is basically not affected by the fault resistance. It can effectively measure the distance of faults occurring at different locations of the cable, and the distance measurement result is highly accurate, with the maximum relative error compared with the actual fault location not exceeding 4%.

[0045] Second, the present invention proposes a two-end traveling wave online fault location method for distribution network cables based on ensemble empirical mode decomposition (EEMD). It mainly solves the problem that the traditional empirical mode decomposition algorithm is prone to modal aliasing, which affects the accurate identification and calibration of the arrival time of the fault traveling wave head, resulting in low accuracy and large errors in the algorithm's fault location. It realizes the accurate calibration of the fault traveling wave signal head, and has higher fault location accuracy and more accurate positioning than the traditional algorithm.

[0046] Third, the expected benefits and commercial value of the technical solution of the present invention after transformation are as follows: With the development of urbanization, the proportion of cables in distribution networks, especially urban distribution networks, is increasing, and the resulting problems of cable line fault detection and positioning are becoming increasingly serious. The present invention proposes a double-end fault ranging method and system suitable for distribution network cable lines. Relevant equipment can be directly developed based on the present invention, or the existing fault ranging equipment can be modified using the technical solution of the present invention, which can greatly improve the accuracy of on-site fault ranging, thereby ensuring the power supply reliability of the system. This technical solution is easy to transform, has rich application scenarios, and is in high demand. It has a broad application space and huge commercial value.

[0047] Fourth, based on the distribution network cable fault point distance measurement method provided by the present invention, the following significant technical advances are brought about:

[0048] 1) High accuracy:

[0049] By adopting EEMD decomposition and Hilbert transform technology, this method can more accurately detect the arrival moment of the traveling wave head, thereby improving the accuracy of ranging.

[0050] 2) Quick response:

[0051] Since this method focuses on high-frequency components, it can quickly identify the traveling waves generated by the fault point, greatly shortening the fault location time.

[0052] 3) Reduce misjudgments:

[0053] By decoupling the fault traveling wave signal and analyzing the high-frequency components, this method can greatly reduce misjudgments caused by external noise or other non-fault factors.

[0054] 4) Wide-area monitoring:

[0055] This method has high sensitivity to transient signals in a wide frequency band, making it possible to achieve high-accuracy fault location even for long-distance distribution network cables.

[0056] 5) Strong adaptability:

[0057] Since the traveling wave line mode component with smaller dispersion is used for detection, the method has good adaptability to cables of different types, materials and lengths.

[0058] 6) Technology Integration:

[0059] This method allows for integration with other technologies (such as fiber optic temperature measurement or digital traveling wave relay technology) to further improve the accuracy and reliability of fault detection and location.

[0060] 7) Reduce grid downtime:

[0061] Accurately and quickly locating the fault point means that repairs can be carried out faster, thereby reducing grid downtime and improving power supply reliability.

[0062] 8) Economic benefits:

[0063] By reducing false positives, minimizing downtime, and rapidly locating faults, this approach can save electricity providers significant operating and maintenance costs.

[0064] The method for measuring the distance to the fault point of a distribution network cable provided by the present invention represents a significant technological advancement and provides a highly efficient, accurate and reliable fault location tool for modern power systems. BRIEF DESCRIPTION OF THE DRAWINGS

[0065] 1 is a flow chart of a method for measuring distance to a distribution network cable fault point according to an embodiment of the present invention;

[0066] FIG2 is a flow chart of an EMD decomposition algorithm provided by an embodiment of the present invention;

[0067] FIG3 is a schematic diagram of a dual-terminal traveling wave ranging principle provided by an embodiment of the present invention;

[0068] 4 is a schematic diagram of the structure of a distribution network cable fault point distance measurement system according to an embodiment of the present invention;

[0069] FIG5 is a schematic diagram of a fault current waveform collected according to an embodiment of the present invention;

[0070] 6 is a schematic diagram of extracting a double-terminal fault traveling wave line mode component according to an embodiment of the present invention;

[0071] FIG7 is a schematic diagram of a head-end sampling point provided by an embodiment of the present invention;

[0072] FIG8 is a schematic diagram of terminal sampling points provided by an embodiment of the present invention. Modes for Carrying Out the Invention

[0073] In order to make the purpose, technical solutions and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0074] Based on the distribution network cable fault point distance measurement method provided by the present invention, the following are two specific embodiments and their implementation solutions:

[0075] Example 1: Implementation scheme based on digital traveling wave relay

[0076] 1) System configuration:

[0077] Configure digital traveling wave relays at both ends of the cable.

[0078] A high-speed sampling ADC (analog-to-digital converter) is set at each traveling wave relay end for signal acquisition.

[0079] 2) Implementation steps:

[0080] S101: When a cable fault occurs, the traveling wave relay immediately begins to collect high-frequency changing signals. The collected signals first pass through a bandpass filter to filter out non-high-frequency components, and then undergo decoupling processing.

[0081] S102: Decompose the high-frequency signal using the EEMD method to extract the first IMF component. Then, use the Hilbert transform to generate a time-frequency diagram. The time corresponding to the first frequency mutation point detected on the time-frequency diagram is the arrival time of the traveling wave head.

[0082] S103: Calculate the fault location using a two-terminal distance measurement algorithm based on the arrival times of the traveling waves recorded by the traveling wave relays at both ends.

[0083] Example 2: Implementation plan based on optical fiber temperature measurement technology

[0084] 1) System configuration:

[0085] Deploy a distributed fiber optic temperature measurement system (DTS) along the cable.

[0086] Use fiber optic sensors to capture temperature changes and other related physical parameter changes caused by cable faults.

[0087] 2) Implementation steps:

[0088] S101: When a cable fault occurs, the fiber optic sensor captures high-frequency changes in temperature and other physical parameters. Specific algorithms are used to extract the fault traveling wave signal from these changes and decouple it.

[0089] S102: Decompose the captured signal using the EEMD method to extract the first IMF component. Then, generate a time-frequency diagram using the Hilbert transform. The time corresponding to the first frequency mutation point detected on the time-frequency diagram is the arrival time of the traveling wave head.

[0090] S103: Since the DTS system can accurately measure the location of temperature changes, the fault location can be directly calculated using the measured time and the known cable length and traveling wave propagation speed.

[0091] Both embodiments provide effective methods for distance measurement of distribution network cable fault points, but the specific choice of embodiment depends on the actual application scenario, budget and technical requirements.

[0092] As shown in FIG1 , the method for measuring the distance to a distribution network cable fault point provided by an embodiment of the present invention includes the following steps:

[0093] S101: When a cable fault occurs, a transient signal with a wide frequency band is generated. The fault traveling wave contains high-frequency components, and the traveling wave line mode component with smaller dispersion is used for detection. The extracted fault traveling wave signal is decoupled.

[0094] S102: When the traveling wave generated by the fault point reaches the measurement end, both the voltage and current of the traveling wave will change sharply. The traveling wave head will appear as a high-frequency mutation in the time-frequency diagram. The mutation point is the wave head position. EEMD decomposition is performed on the fault traveling wave line mode component. The first IMF component is extracted and Hilbert transformed to obtain its time-frequency diagram. The sampling time corresponding to the first frequency mutation point on the time-frequency diagram is the arrival time of the fault traveling wave head.

[0095] S103: Calculate the distance to the fault point using a dual-terminal ranging algorithm.

[0096] The method for measuring the distance to a cable fault point in a distribution network provided by an embodiment of the present invention includes the following steps:

[0097] (1) Extraction of traveling wave line mode components

[0098] Cable faults generate transient signals across a wide frequency band, and the fault traveling wave contains abundant high-frequency components. Traveling wave signals of different moduli and frequencies propagate at different speeds, causing distortion of the traveling wave head during propagation and affecting accurate calibration of the head. The present invention uses traveling wave line mode components with minimal dispersion for detection.

[0099] The complex electromagnetic coupling between the three phases of the cable causes distortion of the fault traveling wave head during propagation, reducing ranging accuracy. Therefore, the extracted fault traveling wave signal needs to be decoupled, which is achieved by using Karen Bell transform in this invention.

[0100] The decoupling process is as follows:

[0101] (1)

[0102] (2)

[0103] In the formula 、 、 are the three-phase currents of the line respectively; 、 、 are the decoupled 0-mode current, α-mode current, and β-mode current components, respectively. The α-mode and β-mode components are both called line-mode components. Further, the velocity equations of traveling waves at different moduli can be derived:

[0104] (3)

[0105] in 、 and 、 They are the zero mode and line mode parameters of the cable line respectively.

[0106] (2) Identification and calibration of fault traveling wave head

[0107] Wave head identification: When the traveling wave generated by the fault point reaches the measurement end, both the traveling wave voltage and current will change sharply. The traveling wave head will appear as a high-frequency mutation in the time-frequency diagram, and the mutation point is the wave head position.

[0108] Wave head calibration: Perform EEMD decomposition on the fault traveling wave line mode components, extract the first IMF component and perform Hilbert transform to obtain its time-frequency diagram. The sampling time corresponding to the first frequency mutation point on the time-frequency diagram is the arrival time of the fault traveling wave head.

[0109] EEMD algorithm process:

[0110] The essence of the EEMD algorithm is to superimpose Gaussian white noise on the original signal, perform multiple EMD decompositions, and take the mean of the IMF components as the final result.

[0111] 1) Give the signal to be analyzed Add white noise;

[0112] 2) Perform EMD decomposition to decompose the noisy signal and obtain the individual IMFs;

[0113] 3) Repeat steps 1) and 2) but add different white noise each time;

[0114] 4) Take the mean of each IMF component obtained from multiple decompositions as the final result.

[0115] As shown in Figure 2, the two important parameters of the EEMD algorithm are the number of groups N and the amplitude of the added Gaussian white noise. The present invention adopts: when N=100, in most cases, the standard deviation of the noise amplitude is 0.2 times the standard deviation of the signal.

[0116] Hilbert transform algorithm:

[0117] set up is a time series, is its Hilbert transform, namely:

[0118] (4)

[0119] Its inverse transform is:

[0120] (5)

[0121] Get the parsed signal:

[0122] (6)

[0123] Where: is the instantaneous amplitude,

[0124] is the phase, The instantaneous frequency can be defined as:

[0125] (7)

[0126] That is, analytical signal The derivative of the phase.

[0127] After performing EEMD decomposition on the collected fault traveling wave signal, a series of inherent modal components containing only one vibration mode can be obtained. Then, performing Hilbert transform on the first IMF component can obtain the instantaneous frequency of this IMF component. The position corresponding to the mutation point of the instantaneous frequency is the wave head of the collected fault traveling wave.

[0128] (3) Calculation method of fault point distance

[0129] The dual-terminal ranging algorithm has the advantages of simple principle and high positioning accuracy. Its specific algorithm is shown in Figure 4;

[0130] Where F is the fault point, t1 and t2 are the time it takes for the fault traveling wave to reach the M and N ends respectively, L is the total length of the cable, and v is the speed of the traveling wave. From this, the cable fault location equation can be derived:

[0131] (8)

[0132] As shown in FIG4 , a distribution network cable fault point distance measurement system provided by an embodiment of the present invention includes:

[0133] The traveling wave line mode component extraction module is used to extract the fault traveling wave signal from the wide-band transient signal generated when the cable fault occurs. The fault traveling wave contains high-frequency components, and the traveling wave line mode component with smaller dispersion is used for detection; the extracted fault traveling wave signal is decoupled;

[0134] The fault traveling wave head identification and calibration module is used to detect the arrival time of the fault traveling wave head. When the traveling wave generated by the fault point reaches the measurement end, the traveling wave voltage and current will undergo sharp changes. The traveling wave head will appear as a high-frequency mutation in the time-frequency diagram, and the mutation point is the wave head position. EEMD decomposition is performed on the fault traveling wave line mode component, and the first IMF component is extracted and Hilbert transformed to obtain its time-frequency diagram. The location of the first frequency mutation point on the time-frequency diagram is the arrival time of the fault traveling wave head.

[0135] The fault point distance calculation module is used to calculate the distance of the fault point in the cable using a two-end ranging algorithm.

[0136] The embodiments of the present invention have achieved some positive results during the development or use process and indeed have great advantages over the prior art. The following content describes them in conjunction with data, charts, etc. from the experimental process.

[0137] First, a cable-based 10kV distribution network model was built using PSCAD / EMTDC software. The cable length was set to 10km, and the fault was set to occur 2km from the cable head end, with phase A grounding fault. Different transition resistances (0.1Ω, 10Ω, and 100Ω) were set for simulation analysis. The simulation lasted 0.05s, the fault occurred at 0.02s, and the sampling frequency was 1MHz.

[0138] Algorithm implementation process:

[0139] 1) Collect the fault current waveform, as shown in Figure 5

[0140] 2) Extracting the traveling wave line mode components of the double-ended fault

[0141] The phase-mode transformation of the three-phase current sampled at both ends is performed to obtain its α-mode component, and the α-mode component of the current traveling wave from t = 0.0198s to 0.0204s is extracted for analysis, as shown in Figure 6.

[0142] 3) Perform EEMD decomposition on the extracted double-terminal fault traveling wave line mode components and perform Hilbert transform on the first IMF component, as shown in Figures 7 and 8;

[0143] The arrival time of the fault traveling wave head detected at the head end is the 211th sampling point, and the arrival time of the fault traveling wave head detected at the end end is the 241st sampling point. According to formula (8), the distance between the fault point and the head end can be calculated to be 2026.1m. The actual distance between the fault point and the first section of the cable is 2000m, and the relative error of the algorithm is 1.305%.

[0144] Table 1 Distance measurement results at different fault distances and transition resistances

[0145]

[0146] From the ranging results in Table 1, it can be seen that the cable fault ranging method based on the EEMD algorithm proposed in the present invention is simple and feasible, and is basically not affected by the fault resistance. It can effectively measure the distance of faults occurring at different locations of the cable, and the ranging results are highly accurate, with the maximum relative error compared with the actual fault location not exceeding 4%.

[0147] It should be noted that the embodiments of the present invention can be implemented by hardware, software, or a combination of software and hardware. The hardware portion can be implemented using dedicated logic; the software portion can be stored in a memory and executed by an appropriate instruction execution system, such as a microprocessor or dedicated design hardware. Those skilled in the art will appreciate that the above-mentioned devices and methods can be implemented using computer-executable instructions and / or contained in processor control code, for example, such as a carrier medium such as a disk, CD or DVD-ROM, a programmable memory such as a read-only memory (firmware), or a data carrier such as an optical or electronic signal carrier. The devices and modules of the present invention can be implemented by hardware circuits such as very large-scale integrated circuits or gate arrays, semiconductors such as logic chips, transistors, or programmable hardware devices such as field programmable gate arrays, programmable logic devices, etc., can also be implemented by software executed by various types of processors, or can be implemented by a combination of the above-mentioned hardware circuits and software, such as firmware.

[0148] The above description is only a specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any modifications, equivalent substitutions and improvements made by any technician familiar with this technical field within the technical scope disclosed by the present invention and within the spirit and principles of the present invention should be covered by the scope of protection of the present invention.

Claims

1. A method for measuring the distance between cable fault points in a distribution network, characterized in that: The following steps are involved: In the first step, when a cable fault occurs, a transient signal with a wide frequency band is generated. The fault traveling wave contains high-frequency components, and the traveling wave line mode component with smaller dispersion is used for detection; the extracted fault traveling wave signal is decoupled; In the second step, when the traveling wave generated by the fault point reaches the measurement end, the traveling wave voltage and current will change sharply, and the traveling wave head will appear as a high-frequency mutation in the time-frequency diagram, and the mutation point is the wave head position; the fault traveling wave line mode component is decomposed by EEMD, and the first IMF component is extracted to perform Hilbert transform to obtain its time-frequency diagram. The sampling time corresponding to the first frequency mutation point position on the time-frequency diagram is the arrival time of the fault traveling wave head; The third step is to use the dual-terminal ranging algorithm to calculate the distance to the fault point.

2. The method for measuring the distance between the cable fault point in the distribution network according to claim 1, characterized in that: The first step specifically includes: decoupling the extracted fault traveling wave signal by adopting Karen Bell transformation. The decoupling process is as follows: ； ； In the formula 、 、 They are the three-phase currents of the line respectively; 、 、 They are the decoupled 0-mode current, α-mode current and β-mode current components respectively; α-mode and β-mode are both called line mode components, and the wave velocity equation of the traveling wave at different modes is obtained: ； in 、 and 、 They are the zero mode and line mode parameters of the cable line respectively.

3. The method for measuring the distance between the cable fault point in the distribution network according to claim 1, characterized in that: The second step specifically includes: identifying the fault traveling wave head, using the EEMD algorithm, superimposing Gaussian white noise on the original signal, performing multiple EMD decompositions, and taking the mean of the IMF components as the final result; 1) Give the signal to be analyzed Add white noise; 2) Perform EMD decomposition to decompose the signal after adding noise and obtain each IMF; 3) Repeat steps 1) and 2), but add different white noise each time; 4) Take the mean of each IMF component obtained from multiple decompositions as the final result.

4. The method for measuring the distance between the cable fault point in the distribution network according to claim 1, characterized in that: The second step specifically includes: the fault traveling wave head is calibrated using the Hilbert transform algorithm: set up is a time series, is its Hilbert transform, that is: ； Its inverse transformation is: ； Get the parsed signal: ； Where: is the instantaneous amplitude, ； is the phase, . The instantaneous frequency is defined as: ； The analytical signal The derivative of the phase.

5. The method for measuring the distance between the cable fault point in the distribution network according to claim 1, characterized in that: In the second step, the collected fault traveling wave signal is decomposed by EEMD to obtain a series of inherent modal components containing only one vibration mode, and then the first IMF component is Hilbert transformed to obtain the instantaneous frequency of this IMF component. The mutation point of the instantaneous frequency is the wave head of the collected fault traveling wave.

6. The method for measuring the distance between cable fault points in a distribution network according to claim 1, characterized in that: The third step specifically includes: in the two-terminal distance measurement algorithm, F is the fault point, t1 and t2 are the time when the fault traveling wave reaches the M end and the N end respectively, L is the total length of the cable, and v is the speed of the traveling wave, and the cable fault location equation is derived: 。 7. A computer device, characterized in that: The computer device includes a memory and a processor, the memory stores a computer program, and when the computer program is executed by the processor, the processor executes the distribution network cable fault point distance measurement method according to any one of claims 1 to 6.

8. A computer-readable storage medium storing a computer program, wherein when the computer program is executed by a processor, the processor executes the distribution network cable fault point distance measurement method according to any one of claims 1 to 6.

9. An information data processing terminal, characterized in that: The information data processing terminal is used to implement the distribution network cable fault point distance measurement method as described in any one of claims 1 to 6.

10. A distribution network cable fault point distance measurement system based on the distribution network cable fault point distance measurement method according to any one of claims 1 to 6, characterized in that: include: The traveling wave line mode component extraction module is used to extract the fault traveling wave signal from the wide-band transient signal generated when the cable fails. The fault traveling wave signal contains high-frequency components, and the traveling wave line mode component with smaller dispersion is used for detection; the extracted fault traveling wave signal is decoupled; The fault traveling wave head identification and calibration module is used to detect the arrival time of the fault traveling wave head. When the traveling wave generated by the fault point reaches the measuring end, the traveling wave voltage and current will change sharply, and the traveling wave head will appear as a high-frequency mutation in the time-frequency diagram, and the mutation point is the wave head position; the fault traveling wave line mode component is decomposed by EEMD, and the first IMF component is extracted to perform Hilbert transform to obtain its time-frequency diagram. The sampling time corresponding to the first frequency mutation point position on the time-frequency diagram is the arrival time of the fault traveling wave head; The fault point distance calculation module is used to calculate the fault point distance using a dual-end distance measurement algorithm.

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