Cable insulation state evaluation and early warning method based on transient traveling wave signal characteristics

Abstract

The present application relates to the technical field of cable detection, in particular to a cable insulation state evaluation and early warning method based on transient traveling wave signal characteristics, comprising: distinguishing intra-zone faults and extra-zone faults according to the fault distance and the high-low frequency energy difference of the transient traveling wave signal, combining the topological structure of the current cable to be detected to determine the preliminary identified fault point; performing secondary regional mapping on the fault point, integrating the spatial position of each fault point through the direction information corresponding to the transient traveling wave signal to determine the fault region topological graph of each fault point combination; positioning the fault section corresponding to the current fault point according to the fault region topological graph data updated at any time; combining the identified fault section with the duration, intensity and frequency of fault occurrence to evaluate the insulation problem level of the corresponding fault section; comparing the insulation problem levels of the fault section under multiple analyses to perform early warning according to the coincidence of each fault section. The accuracy and efficiency of cable early warning are realized.

Description

Cable insulation condition assessment and early warning method based on transient traveling wave signal characteristics Technical Field

[0001] This invention relates to the field of cable testing technology, specifically a method for cable insulation condition assessment and early warning based on transient traveling wave signal characteristics. Background Technology

[0002] Transient traveling waves refer to the high-frequency voltage and current traveling waves generated in a cable when a fault occurs due to the sudden change in impedance at the fault point. These traveling waves propagate along the cable and are reflected and refracted when they encounter impedance discontinuities. By analyzing the propagation and reflection characteristics of these traveling waves, cable faults can be monitored and located.

[0003] For example, Chinese Patent Publication No. CN120195500A discloses a method and system for grounding loop resistance detection and fault location integrating edge computing, which relates to the field of grounding detection technology. The method includes: performing key node analysis of the grounding loop and deploying edge computing units and configuring mapped monitoring sensors, including a high-frequency transient traveling wave detector, a broadband impedance spectrum measurement sensor, and a synchronization clock unit; during normal operation of the power grid device, monitoring is performed using the monitoring sensors and time synchronization alignment of the monitoring dataset is performed; the continuous situation field of the grounding loop is reconstructed by interpolation through the edge computing unit, and the continuous situation field is constructed based on three-dimensional fault features; the power grid device is monitored in real time using the monitoring sensors, and based on the real-time monitoring results and the continuous situation field, combined with local height gradient features and extreme value region features, fault source inversion is performed to establish fault location results.

[0004] For example, Chinese Patent Publication No. CN116699313A discloses a method and device for self-inspection of faults in multi-branch lines for line protection, which relates to the field of line fault self-inspection technology. The method includes: reading the target line characteristics of the target multi-branch line and constructing a transmission line distribution model; reading historical line transmission information records of the target multi-branch line and generating a transmission characteristic curve of the target multi-branch line; real-time monitoring to obtain real-time information along the line and real-time endpoint information, dynamically updating the transmission characteristic curve to obtain a dynamic transmission characteristic curve; constructing a dual-channel self-inspection model, analyzing the dynamic transmission characteristic curve, obtaining dynamic analysis results, and judging whether the line is faulty based on the analysis results. If so, fault handling is performed on the line.

[0005] Existing technologies use continuous interpolation to form a continuous situation field, employing time synchronization to illustrate the temporal evolution characteristics and local gradient characteristics of key nodes, and using local gradient characteristics to complete fault inversion. Furthermore, by comparing the voltage and current of branch lines with historical information from endpoints, dynamic self-checks are performed, thus completing line analysis and processing. However, existing technologies do not fully utilize the energy characteristic differences of fault signals. Relying solely on the gradient and time domain of the situation can easily lead to an overemphasis on handling faults outside the fault zone when identifying cable faults, resulting in ambiguity in cable fault location. Simultaneously, when locating cable fault points, it is also necessary to determine the number of fault occurrences, duration, and intensity to quantify whether there is continuous deterioration or propagation at each fault point, leading to a lack of information on cable insulation status identification. Summary of the Invention

[0006] To solve the above-mentioned technical problems, the technical solution adopted by the present invention is: a cable insulation status assessment and early warning method based on transient traveling wave signal characteristics, including: S1, reading the transient traveling wave signal of the cable to be tested, distinguishing between faults within the zone and faults outside the zone by the fault distance and high and low frequency energy difference of the transient traveling wave signal, and determining the initially identified fault point by combining the current topology of the cable to be tested.

[0007] S2. Perform secondary region mapping on the fault points. By integrating the spatial location of each fault point through the directional information corresponding to the transient traveling wave signal, determine the fault region topology map of each fault point combination.

[0008] S3, based on the fault area topology map data updated at any time, locates the fault segment corresponding to the current fault point.

[0009] S4 combines the identified faulty sections with the duration, intensity, and frequency of the faults to assess the insulation problem level of the corresponding faulty sections.

[0010] S5. Compare the insulation problem levels of the faulty sections under multiple analyses. If the insulation problem levels of multiple time periods belong to the same level, then issue an early warning based on the overlap of each faulty section.

[0011] The beneficial effects of this invention are as follows: First, this invention, through traveling wave ranging and high- and low-frequency energy difference discrimination, combined with cable topology and key node list, supplemented by wavelet decomposition to extract the time difference of adjacent modulus maxima, quantify high- and low-frequency energy index values, and correlate the initial traveling wave amplitude and wavefront rise slope, clarifies the relative position of each fault point, realizes the distinction between faults inside and outside the zone, and determines the specific location of faults within the zone, thereby improving the accuracy of fault point location.

[0012] Second, this invention corrects the coordinates of the fault point based on transient traveling wave direction information, divides the fault area by direction vector clustering, and constructs a fault area topology map; and combines the topology map update time window to synchronize transient faults within a unit time, clarifying the fault segment corresponding to the fault point; and clarifies the distribution of transient faults when the fault occurs, realizing the direct binding of the fault point and physical segment, providing a clear carrier for subsequent fault segment analysis.

[0013] Third, this invention uses the fault duration, fault intensity, and fault frequency of the fault section as core indicators, calculates the insulation warning coefficient through weighted summation, and classifies the insulation problem level according to the coefficient value range; finally, it determines the insulation problem level under multiple analyses, and generates a warning report by combining scenario type and insulation level; it ensures the objectivity and repeatability of insulation level assessment, supplements the characteristic description under each scenario, provides sufficient data information for subsequent cable processing, and improves the efficiency and accuracy of cable warning. Attached Figure Description

[0014] The present invention will be further described below with reference to the accompanying drawings and embodiments.

[0015] Figure 1 is a flowchart illustrating the cable insulation condition assessment and early warning method based on transient traveling wave signal characteristics.

[0016] Figure 2 is a flowchart of step S1 of the cable insulation condition assessment and early warning method based on transient traveling wave signal characteristics.

[0017] Figure 3 is a flowchart of step S2 of the cable insulation condition assessment and early warning method based on transient traveling wave signal characteristics.

[0018] Figure 4 is a flowchart of step S3 of the cable insulation condition assessment and early warning method based on transient traveling wave signal characteristics.

[0019] Figure 5 is a flowchart of step S4 of the cable insulation condition assessment and early warning method based on transient traveling wave signal characteristics.

[0020] Figure 6 is a flowchart of step S5 of the cable insulation condition assessment and early warning method based on transient traveling wave signal characteristics. Detailed Implementation

[0021] The embodiments of the present invention are described in detail below. The embodiments described below are exemplary and are only used to explain the present invention, and should not be construed as limiting the present invention. Where specific techniques or conditions are not specified in the embodiments, they shall be performed in accordance with the techniques or conditions described in the literature in the art or in accordance with the product manual.

[0022] Referring to Figure 1, the cable insulation status assessment and early warning method based on transient traveling wave signal characteristics includes: S1, reading the transient traveling wave signal of the cable under test, distinguishing between faults within and outside the zone based on the fault distance and high and low frequency energy difference of the transient traveling wave signal, and determining the initially identified fault point in combination with the current topology of the cable under test.

[0023] S2. Perform secondary region mapping on the fault points. By integrating the spatial location of each fault point through the directional information corresponding to the transient traveling wave signal, determine the fault region topology map of each fault point combination.

[0024] S3, based on the fault area topology map data updated at any time, locates the fault segment corresponding to the current fault point.

[0025] S4 combines the identified faulty sections with the duration, intensity, and frequency of the faults to assess the insulation problem level of the corresponding faulty sections.

[0026] S5. Compare the insulation problem levels of the faulty sections under multiple analyses. If the insulation problem levels of multiple time periods belong to the same level, then issue an early warning based on the overlap of each faulty section.

[0027] Transient traveling wave signals can be detected by using high-frequency current sensors and ultra-high-speed data acquisition units installed on cable joints, terminations, or grounding boxes in cable lines.

[0028] In step S1, the criterion for directly distinguishing between faults within and outside the transmission line area is to determine whether the fault point is within the overall protection range of the line protection device, in order to determine whether the current insulation status of the cable is normal and whether there is a fault section, thereby completing the insulation status assessment of the cable.

[0029] Under normal circumstances, based on the basic principles of traveling wave ranging, there are two methods: one is the single-end traveling wave ranging method, which uses the time difference of the traveling wave of a transient fault traveling once to and from the measurement point and the fault point to calculate the fault distance; the other is the double-end traveling wave ranging method, which uses the time difference of the initial traveling wave arriving at both ends of the line to measure the fault distance. Based on the measured fault distance, it is determined whether the current cable fault location belongs to the in-zone or out-of-zone fault. At the same time, it is necessary to combine the direction of the fault power to determine whether the in-zone or out-of-zone fault is in the forward or reverse direction, and record the specific section where the problem occurred.

[0030] In addition, the energy difference between high and low frequencies of transient traveling waves can be used to further distinguish between internal and external faults. During the propagation of transient traveling waves, the energy distribution of different frequency components will vary depending on the location of the fault (inside or outside the fault zone). By analyzing this difference, the fault type can be preliminarily determined.

[0031] As shown in Figure 2, the implementation of step S1 includes: S11, introducing the topology of the cable to be tested and determining the list of key nodes of the cable to be tested.

[0032] The topology includes the total length of the cable, the location of each key node in the cable, such as the location of joint 1, joint 2, joint 3 and the terminal, as well as the node type corresponding to each key node, such as intermediate joint, terminal head, grounding box, etc., and records the actual segment division in the cable to be tested.

[0033] S12, taking the bus section and the end of the line of the cable to be tested as measurement points, and performing traveling wave ranging on the transient traveling wave signal of the cable to be tested based on the time difference when the fault occurs, to obtain the fault distance after traveling wave ranging.

[0034] When using the single-ended traveling wave ranging method, the busbar is assumed to be... Fault distance from end to fault point It can be represented as: ;in, Indicates the speed of the transient traveling wave signal. The time difference representing the transient traveling wave signal at the time of a fault is the time difference of the transient traveling wave signal making one round trip between the measurement point and the fault point. Since the insulation performance of the cable is affected by inductance and capacitance, and the speed of each cable during traveling wave ranging is based on the inverse square root of the inductance and capacitance, the measured wave speed will change when the insulation performance is compromised. Based on the initial traveling wave and the reflected wave generated when a fault occurs, the time difference between these two waves will be synchronized with the time difference of one round trip between the measurement point and the fault point during traveling wave ranging. This allows for a preliminary determination of the abstract location of the fault point in the cable. Then, by using the cable topology, the distance can be converted into specific data to complete the initial identification of the fault point.

[0035] In two-end traveling wave ranging, it is assumed that the transient traveling wave signal reaches the bus. End and line end The times are respectively and The fault distance can be expressed as follows.

[0036] ;in, and These represent the distances from the M and N ends to the fault point, respectively; L is the length of line MN; the essence of dual-end distance measurement is to indicate which side the fault point is closer to, thereby determining the fault that occurred in the current cable insulation.

[0037] Preferably, when identifying the fault distance, step S12 is further implemented by: performing signal decomposition on the transient traveling wave signal, and determining the time difference of the transient traveling wave signal when a fault occurs by using the time difference between adjacent modulus maxima after wavelet transformation.

[0038] By using wavelet transform and modulus maxima method, the transient traveling wave signal is decomposed into multiple scales to find the wavefront and modulus maxima of the transient traveling wave signal. Since the transient traveling wave signal is equivalent to the fluctuation pattern of the voltage signal, its wavefront is the point of signal change, and it is most obvious at the modulus maxima. The wavefront can be found on the time axis of the current signal decomposition. The wavefront corresponding to the first modulus maxima point represents the arrival time of the initial traveling wave, and the wavefront corresponding to the second modulus maxima point represents the arrival time of the reflected wave. The difference between these two times is the current time difference, thereby determining the relative location of the fault point.

[0039] S13, map the fault distance to the location of the critical node, and obtain the relative position of each fault point by fuzzy mapping. At this point, the relative position of each fault distance at the corresponding critical node is identified, and the relative position of the corresponding fault point is marked.

[0040] The measured fault distance can be recorded by a measuring device deployed on one side. The fault distance is compared with the maximum distance within the zone to distinguish between in-zone and out-of-zone faults under cable fault conditions. The maximum distance within the zone is set according to the length of the current measuring cable. For example, if the line length is 5km, the maximum distance within the zone is 5km. If the error of traveling wave ranging is introduced, the corresponding distance can be increased by 2% to 5% to compensate for the error of traveling wave ranging. Fault distances smaller than the maximum in-zone range are considered in-zone faults, and otherwise are considered out-of-zone faults, thus completing the fuzzy location of the corresponding fault. Afterwards, the difference between high and low frequency energy in different scenarios needs to be used to filter out the fault points that match the current output.

[0041] S14 utilizes the high and low frequency energy differences between faults within and outside the area under different scenarios to filter the relative positions of fault points and output the initially identified fault points.

[0042] The implementation of step S14 also includes: S141, calculating the index values ​​of high and low frequency energy based on the high and low frequency energy of the transient traveling wave signal, and when the index values ​​of high and low frequency energy exceed the setting value corresponding to the fault outside the zone, the corresponding fault point is regarded as a fault inside the zone.

[0043] When identifying external and internal faults by using the difference in high and low frequency energy, if the index values ​​of high and low frequency energy exceed the set values ​​corresponding to external faults, an internal fault is initially suspected; for example, the index values ​​of high and low frequency energy... High-frequency energy values ​​during the corresponding time period and low frequency energy value Its equation can be expressed as: ;in, This indicates the setting value corresponding to an external fault, and its value is taken from the setting value of the opposite bus during a fault. The maximum value that can be taken can be adjusted by multiplying the setting value by 1.2 or other coefficients to describe the reliability of the setting value, so that the setting value conforms to the high and low frequency energy difference in the corresponding scenario. When a regional fault occurs, the fault point is close to the protection installation point, and the traveling wave will encounter the short circuit point and generate strong reflection in a short time. Therefore, the index values ​​of high and low frequency energy will be greater than the setting value. If an external fault occurs, the high frequency component will attenuate rapidly during long-distance propagation, causing its index value to be less than the setting value.

[0044] It should be noted that when the fault distance is within the corresponding range or the high and low frequency energy meets the corresponding setting value, it is possible to determine whether the current fault point belongs to the fault within the area or the fault outside the area. In this case, the two are judged continuously in order to filter out the abnormal points that appear, and to prevent the current cable under test from being interfered with by other cables, which would cause the fault identification location to be wrong.

[0045] S142, when the fault point is an intra-area fault, extract the initial traveling wave amplitude and wave front rise slope corresponding to the fault point, perform correlation matching with the initial traveling wave amplitude and wave front rise slope, and use the correlation-matched fault point as the initially identified fault point.

[0046] When using correlation matching, the initial traveling wave amplitude and wavefront rise slope obtained from actual measurements are compared with templates in the pre-established fault feature library to illustrate the specific situation under different scenarios. The Pearson correlation coefficient can be used to compare the initial traveling wave amplitude and wavefront rise slope of the current fault point with the fault feature library, and select the data with the highest similarity as the location and type when determining the current fault point.

[0047] For the initial traveling wave amplitude of the fault point, the closer the fault point is to the protection device, the larger the initial traveling wave amplitude will be. Similarly, the wavefront rise slope of different situations will also show different fault point types. For example, a direct grounding fault may lead to a faster rise slope, while a high impedance fault may show a slower rise slope. This is used to distinguish the fault situation under the insulation state represented by each fault point.

[0048] In one embodiment of the present invention, the direction information corresponding to the transient traveling wave signal indicates the path direction of the transient traveling wave propagating in the cable. During single-end testing, the direction information is the propagation direction of the traveling wave relative to the acquisition device. For example, the traveling wave flowing from the acquisition device to the far end of the cable is positive, and vice versa. During double-end testing, the direction information is the fixed path direction of the traveling wave relative to the cable topology. For example, the main direction along the cable trunk line from the beginning to the end, the branch direction from the trunk line to the branch line, the clockwise or counterclockwise ring network direction, etc., to illustrate the fault propagation situation of the current cable under the corresponding topology.

[0049] Alternatively, the voltage and current traveling waves at the beginning of the line can be collected. The energy difference between these two traveling waves can be used. If the energy difference is greater than 0, it indicates that the current fault is propagating in the forward direction; otherwise, it is propagating in the reverse direction.

[0050] As shown in Figure 3, the implementation of step S2 also includes: S21, mapping the fault point to the topology of the cable to be tested according to the direction information of the transient traveling wave signal, and correcting the direction of the coordinates of each fault point.

[0051] At this point, the fault point will be mapped a second time based on the coordinates of the cable topology. After determining its coordinates, its position will be adjusted according to the direction of the transient traveling wave signal to illustrate the mapping position of each fault point on the cable topology.

[0052] S22, if there are multiple fault points, then set a direction vector based on the coordinates of each fault point after direction correction, and perform clustering processing on the fault points through the direction vector to divide the fault regions corresponding to multiple fault points; at this time, the fault region represents the area formed by multiple fault points due to their close spatial location and consistent direction.

[0053] In step S22, fault points with the same propagation direction are clustered and the clustered data is placed into the corresponding fault region. At the same time, the boundary of the fault region is determined. For example, multiple related fault points can be formed into a region of a specific shape by the coordinates of the outermost fault point to illustrate the aggregation of fault points.

[0054] The implementation of step S22 also includes: S221, based on the direction vector of the fault point, determining whether multiple fault points are in the same direction. If they are not in the same direction, the fault points are divided into fault areas according to the topology of the cable to be tested. For example, there are two fault points, one located on the section from the main trunk A to the branch B, and the other located on the section from the branch B to the branch D. These two directional information are obviously different, so the fault areas are marked on the corresponding sections respectively. The marked fault areas will be set with each fault point as the center and the smallest rectangle or smallest circle surrounding the fault point.

[0055] S222, if they are in the same direction, cluster the fault points and divide the clustered locations into fault regions. During the clustering process, fault points in the same segment are clustered, and the coordinate interval between the current fault point is regarded as the divided fault region. The fault region will represent the sub-region of each segment in the cable topology. For example, if (2.5,0) and (2.8,0) appear in a segment, the positions corresponding to 2.5-2.8 are divided into a fault region using the smallest rectangle or smallest circle surrounding the fault point, and the boundary of the fault region is marked, thus completing the division of the fault region in the cable topology.

[0056] S23, bind the fault points of each fault area, and use the bound data as the output fault area topology map.

[0057] The output fault area topology map will record the coordinates of each fault point, the cable section to which it belongs, the corresponding boundary, direction and other information. After combining these data into a topology map, the fault area will be marked.

[0058] In one embodiment of the present invention, the fault section is used to describe the smallest evaluation unit in insulation assessment and to explain the cable insulation state at different physical boundaries.

[0059] As shown in Figure 4, the implementation of step S3 includes: S31, when the fault area topology map is updated, the section where each fault point is located is determined according to the start time and end time of each update. This section represents the specific line segment on the cable and is the location coordinate of the physical boundary of the fault point.

[0060] S32 compares the transient faults at the corresponding sections within a unit of time, and synchronizes the transient faults to the corresponding fault points according to the number and duration of the transient faults, using the section where the fault point is located as the output fault section. The output fault section should consist of multiple transient faults, rather than one-time permanent faults, in order to obtain as much information as possible about the cable condition in each section, thereby assessing any abnormalities in the cable insulation.

[0061] If the fault identified at the current fault point is a permanent fault, it will directly enter the early warning stage without further processing. The early warning will be issued and the fault will be handled directly according to the measured fault point.

[0062] In one embodiment of the present invention, in step S4, based on the identification of the corresponding fault section, the duration, intensity and number of faults occurring on the corresponding line are selected, and the overlap of each section is determined according to the number of faults, and finally the insulation status assessment is completed.

[0063] As shown in Figure 5, the implementation of step S4 also includes: S41, setting the insulation warning coefficient for each fault point based on the duration, intensity and number of faults occurring at any location on the fault section.

[0064] To ensure the accuracy of insulation warning results, real-time monitoring of cable lines under the same busbar is required, and the insulation warning coefficient should be adjusted accordingly. for: ;in, , and These represent the number of times, duration, and intensity of a fault occurring at a point i on the faulty section within a certain time period; , and These are the weights corresponding to the number of failures, duration, and intensity, respectively. The values ​​of the three weights can be set based on the ratio of each feature value to the total feature value after the number of failures, duration, and intensity are converted into feature values, or they can be set based on the numerical values ​​of 0.4, 0.2, and 0.4 to set the weights of the number of failures, duration, and intensity.

[0065] The number of faults, duration, and intensity will be handled according to the expected number of warnings to illustrate the value of the insulation warning coefficient under relative expectation.

[0066] When setting the insulation warning coefficient in step S41, the implementation method also includes: counting the expected number of warnings for the current fault section, and setting the index value of the number of faults by comparing the expected number of warnings with the number of faults occurring at the fault point per unit time.

[0067] By using the ratio of the duration of a fault occurring at a fault point to the duration of a permanent fault within a unit of time, the index value of the fault duration under the corresponding expected number of warnings is determined.

[0068] The index value of fault intensity under the corresponding expected number of warnings is determined by using the ratio of the voltage value of the fault point occurring per unit time to the voltage peak value of the metallic fault.

[0069] An insulation warning coefficient is set based on the weighted sum of the index values ​​of the number of faults, the index value of the fault duration, and the index value of the fault intensity.

[0070] For example, the index value of the number of failures. It can be represented as: Where N represents the desired number of warnings, which can be set to 5, or to the average number of faults occurring in all fault sections within a unit of time, to illustrate the relative situation of faults occurring at each location. This represents the number of times a fault occurs at a specific fault point i within a faulty segment per unit time.

[0071] As for the index value of fault duration It can be represented as: Where D is the threshold value for determining a permanent fault, which means that after a certain period of time, a fault at the corresponding location is considered a permanent fault, rather than a transient fault, thus identifying the index value corresponding to the duration. It represents the duration of each instantaneous fault at a fault point i in the fault segment within a unit of time.

[0072] Final Fault Intensity Index Value Represented as: Where U represents the peak voltage of a metallic fault, indicating the voltage value at which the insulation performance of the corresponding cable is compromised and a significant metallic fault occurs. Let be the voltage intensity at a certain fault point i in the fault section per unit time. Based on the ratio of the voltage value to the peak voltage of a metallic fault, we can know the specific situation of insulation degradation, and thus further explain the situation of insulation degradation at the fault point.

[0073] S42 sets the insulation problem level for each fault point based on the range of values ​​for the insulation warning coefficient.

[0074] After calculating the insulation warning factor, a judgment should be made immediately. The system should issue an early warning and report fault information to achieve instantaneous judgment of the cable insulation status, thereby identifying the specific circumstances of permanent and transient faults. If the value is less than 1, it is classified into insulation problem levels one, two, three, and four according to its value range, such as the intervals of 0-0.3, 0.3-0.5, 0.5-0.7, and 0.7-1.0. Values ​​greater than 1 are regarded as problem levels for direct early warning, and other problem levels will be described with additional information on the current cable insulation status according to their intervals.

[0075] At this point, 0-0.3 indicates slight degradation, meaning there are occasional faults in the insulation layer, but no continuous degradation has occurred; 0.3-0.5 indicates that occasional faults are starting to increase slowly, and intermittent degradation has already occurred; 0.5-0.7 indicates that continuous degradation has begun to form, and the number of faults has increased significantly; 0.7-1.0 indicates that the fault intensity and frequency have reached the critical value of metallic faults, and the cable is about to be broken down by voltage.

[0076] In one embodiment of the present invention, step S5 collects multiple outputs of insulation problem level data and groups the fault occurrences within a unit time period according to the time period of each analysis.

[0077] As shown in Figure 6, the implementation of step S5 includes: S51, dividing the faulty sections analyzed multiple times according to their location to obtain multiple sets of section data; each group contains the insulation problem level of the corresponding section under multiple analyses.

[0078] S52. Compare the data for each segment and check the insulation problem level in chronological order to determine whether the current faulty segment belongs to the scenario type of complete overlap, partial overlap, or no overlap after multiple analyses. Complete overlap means that the insulation problem level corresponding to the number of faults is the same in multiple consecutive time periods. Partial overlap means that some insulation problem levels are the same in multiple time periods. No overlap means that the insulation problems are different in multiple time periods, or no faults have occurred.

[0079] S53, based on the combination of scenario type and insulation problem level, set early warning reports for each fault section. The essence of step S5's early warning is to verify the overlap in time and space during multiple analyses to reveal the stability or spread of the current transient fault. For example, in scenarios with complete overlap, the insulation performance of the corresponding cable is relatively stable, and an early warning report can be directly output based on the data combination from multiple time periods. In partially overlapping scenarios, it indicates significant changes in insulation performance over different time periods, potentially indicating deterioration factors such as moisture or electrical treeing, leading to deterioration of the cable's insulation performance or unstable measurements, requiring priority intervention. In scenarios without overlap, insulation performance changes are scattered, possibly greatly affected by the environment. It is necessary to check the corresponding cable location according to the data presented by its insulation problem level and verify the common environmental factors appearing in multiple time period analyses to assist in judging the cable's insulation performance.

[0080] Although embodiments of the present invention have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting the present invention. Those skilled in the art can make changes, modifications, substitutions and variations to the above embodiments within the scope of the present invention, which are still covered within the protection scope of the present invention.

Claims

1. A method for cable insulation condition assessment and early warning based on transient traveling wave signal characteristics, characterized in that, include: S1. Read the transient traveling wave signal of the cable under test. Use the fault distance and high and low frequency energy difference of the transient traveling wave signal to distinguish between faults within and outside the area. Combined with the current topology of the cable under test, determine the initially identified fault points. S2. Perform secondary region mapping on the fault points. Use the direction information corresponding to the transient traveling wave signal to integrate the spatial positions of each fault point and determine the fault area topology map of the combination of each fault point. S3. Based on the fault area topology map data updated at any time, locate the fault segment corresponding to the current fault point; S4. Combine the identified fault segment with the duration, intensity and frequency of the fault occurrence to assess the insulation problem level of the corresponding fault segment; S5. Compare the insulation problem level of the fault segment under multiple analyses. If the insulation problem level of multiple time periods belongs to the same level, then issue an early warning based on the overlap of each fault segment.

2. The cable insulation condition assessment and early warning method based on transient traveling wave signal characteristics according to claim 1, characterized in that, The implementation of step S1 includes: S11, introducing the topology of the cable to be tested and determining the list of key nodes of the cable to be tested; S12, taking the bus section and the end of the line of the cable to be tested as measurement points, and performing traveling wave ranging on the transient traveling wave signal of the cable to be tested based on the time difference when the fault occurs, to obtain the fault distance after traveling wave ranging; S13, mapping the fault distance to the location of the key nodes, and obtaining the relative position of each fault point in a fuzzy mapping manner; S14, using the high and low frequency energy differences of faults within and outside the area under different scenarios, filtering the relative positions of fault points, and outputting the initially identified fault points.

3. The cable insulation condition assessment and early warning method based on transient traveling wave signal characteristics according to claim 2, characterized in that, The implementation of step S12 also includes: performing signal decomposition on the transient traveling wave signal, and determining the time difference of the transient traveling wave signal when a fault occurs by using the time difference between adjacent modulus maxima after wavelet transformation.

4. The cable insulation condition assessment and early warning method based on transient traveling wave signal characteristics according to claim 2, characterized in that, The implementation of step S14 further includes: S141, calculating the index values ​​of high and low frequency energy based on the high and low frequency energy of the transient traveling wave signal, and when the index values ​​of high and low frequency energy exceed the set value corresponding to the fault outside the area, the corresponding fault point is regarded as a fault within the area; S142, when the fault point is a fault within the area, extracting the initial traveling wave amplitude and wavefront rise slope corresponding to the fault point, performing correlation matching with the initial traveling wave amplitude and wavefront rise slope, and using the correlation-matched fault point as the initially identified fault point.

5. The cable insulation condition assessment and early warning method based on transient traveling wave signal characteristics according to claim 1, characterized in that, The implementation of step S2 also includes: S21, mapping the fault points to the topology of the cable to be tested according to the direction information of the transient traveling wave signal, and correcting the direction of the coordinates of each fault point; S22, if there are multiple fault points, setting a direction vector based on the corrected coordinates of each fault point, and performing clustering processing on the fault points through the direction vector to divide the fault regions corresponding to multiple fault points; S23, binding the fault points in each fault region, and using the bound data as the output fault region topology map.

6. The cable insulation condition assessment and early warning method based on transient traveling wave signal characteristics according to claim 5, characterized in that, The implementation of step S22 also includes: S221, based on the direction vector of the fault point, determining whether multiple fault points are in the same direction; if they are not in the same direction, dividing each fault point into a fault area according to the topology of the cable to be tested; S222, if they are in the same direction, performing clustering processing on each fault point, and dividing the clustered location into a fault area.

7. The cable insulation condition assessment and early warning method based on transient traveling wave signal characteristics according to claim 1, characterized in that, The implementation of step S3 includes: S31, when the fault area topology map is updated, determine the segment where each fault point is located based on the start time and end time of each update; S32, compare the transient faults in the corresponding segment within a unit time, and synchronize the transient faults to the corresponding fault points according to the number of transient faults and the duration of transient faults, and use the segment where the fault point is located as the output fault segment.

8. The cable insulation condition assessment and early warning method based on transient traveling wave signal characteristics according to claim 1, characterized in that, The implementation of step S4 also includes: S41, setting the insulation warning coefficient for each fault point based on the duration, intensity and frequency of the fault occurring at any location in the fault section; S42, setting the insulation problem level for each fault point based on the value range of the insulation warning coefficient.

9. The cable insulation condition assessment and early warning method based on transient traveling wave signal characteristics according to claim 8, characterized in that, When setting the insulation warning coefficient in step S41, the implementation method further includes: statistically analyzing the expected number of warnings for the current fault section; setting an index value for the number of faults by comparing the expected number of warnings with the number of times a fault occurs at the fault point within a unit time; determining an index value for the fault duration under the corresponding expected number of warnings by using the ratio of the duration of a fault occurring at the fault point within a unit time to the duration of a permanent fault; determining an index value for the fault intensity under the corresponding expected number of warnings by using the ratio of the voltage value of a fault occurring at the fault point within a unit time to the voltage peak value of a metallic fault; and setting the insulation warning coefficient based on the weighted sum of the index values ​​for the number of faults, the duration of the fault, and the intensity of the fault.

10. The cable insulation condition assessment and early warning method based on transient traveling wave signal characteristics according to claim 1, characterized in that, The implementation of step S5 includes: S51, dividing the faulty sections analyzed multiple times according to their location to obtain multiple sets of section data; S52, comparing each set of section data, checking the insulation problem level in chronological order, and determining whether the current faulty section belongs to the scenario type of complete overlap, partial overlap, or no overlap after multiple analyses; S53, setting early warning reports for each faulty section based on the combination of scenario type and insulation problem level.

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