A Method and System for Evaluating Cable Service Life Based on High-Frequency Pulse Sequence Analysis

Abstract

This invention relates to the field of fault testing technology and proposes a method and system for cable service life assessment based on high-frequency pulse sequence analysis. The method includes: bandpass filtering of high-frequency pulse signals to obtain raw pulse sequence data; performing multi-constraint clustering to trace the pulse point set to obtain a defect pulse sequence; grouping continuous pulses with the same evolution characteristics in the defect pulse sequence into pulse groups and projecting them onto a time axis to obtain a defect evolution time sequence map; stripping multi-dimensional features from the defect evolution time sequence map and performing nonlinear coupling to obtain a composite degradation factor; performing trajectory similarity matching on a preset standard degradation trajectory library and performing time-series inversion on the registered degradation trajectory curves to obtain a current aging stage identifier; and correcting the current aging stage identifier for service conditions to obtain a remaining service life estimate. This invention can improve the efficiency of cable service life assessment.

Description

Technical Field

[0001] This invention relates to the field of fault testing technology, and in particular to a method and system for assessing cable service life based on high-frequency pulse sequence analysis. Background Technology

[0002] In the field of cable service life assessment, a complete processing system based on high-frequency pulse sequence analysis technology has not yet been formed. The processing of high-frequency pulse signals of cables only involves basic filtering operations, without baseline correction and dynamic baseline compensation, and without adaptive passband interception for the main lobe interval of the signal's frequency domain energy. As a result, the extracted pulse sequence data is mixed with a large amount of invalid interference information, which cannot provide accurate raw data support for the subsequent identification of defect pulses. The extraction of defect pulse sequences lacks an effective data foundation, making it difficult to accurately capture the defect-related pulse characteristics of cables in actual operation.

[0003] Existing cable life assessment methods have significant technical shortcomings in defect pulse analysis and life prediction. They fail to perform multi-constraint clustering for tracing based on pulse leading edge steepness and pulse width, and do not construct defect evolution time-series maps by combining pulse interval fluctuation patterns and amplitude sequence trends. The mining of cable degradation characteristics is limited to a single parameter level, and the coupled analysis of degradation process acceleration and critical breakdown approach is not completed. Furthermore, the life prediction stage does not incorporate targeted corrections to aging stage identifiers based on the cable's historical operating conditions, resulting in discrepancies between the identified cable aging stages and the actual service condition. Consequently, the accuracy of the remaining service life prediction is insufficient, failing to provide scientific and effective data references for cable operation and maintenance decisions. Summary of the Invention

[0004] This invention provides a method and system for assessing the service life of cables based on high-frequency pulse sequence analysis, in order to solve the problems mentioned in the background art.

[0005] To achieve the above objectives, the present invention provides a cable service life assessment method based on high-frequency pulse sequence analysis, comprising:

[0006] Pt.1. Bandpass filtering is performed on the high-frequency pulse signal of the cable to be evaluated to obtain the original pulse sequence data of the cable to be evaluated;

[0007] Pt.2. Based on the leading edge steepness and pulse width of the original pulse sequence data, perform multi-constraint clustering to trace the pulse point set in the original pulse sequence data to obtain the defect pulse sequence of the cable to be evaluated.

[0008] Pt.3. Based on the time interval fluctuation pattern between adjacent pulses in the defect pulse sequence and the monotonicity trend of the pulse amplitude sequence, continuous pulses with the same evolution characteristics in the defect pulse sequence are grouped into pulse groups, and the pulse groups are projected onto the time axis to obtain the defect evolution time sequence map of the cable to be evaluated.

[0009] Pt.4. Perform multi-dimensional feature stripping on the defect evolution time series map, and nonlinearly couple the degradation process acceleration and critical breakdown approximation of the stripped feature to obtain the composite degradation factor of the cable to be evaluated.

[0010] Pt.5. Based on the composite degradation factor, perform trajectory similarity matching on the preset standard degradation trajectory library, and perform time-series inversion on the registered degradation trajectory curve to obtain the current aging stage identifier of the cable to be evaluated.

[0011] Pt.6. Based on the historical operating condition data of the cable to be evaluated, the current aging stage identifier is corrected for service conditions to obtain the estimated remaining service life of the cable to be evaluated.

[0012] In a preferred embodiment, bandpass filtering of the high-frequency pulse signal of the cable to be evaluated to obtain the original pulse sequence data of the cable to be evaluated includes:

[0013] Baseline correction is performed on the high-frequency pulse signal of the cable to be evaluated to obtain the baseline drift of the cable to be evaluated;

[0014] Based on the baseline drift, dynamic baseline compensation is performed on the high-frequency pulse signal to obtain the pulse signal of the cable to be evaluated;

[0015] The frequency domain energy main lobe range of the cable to be evaluated is obtained by performing spectral feature localization on the pulse signal.

[0016] Based on the frequency domain energy main lobe interval, the pulse signal is adaptively truncated to obtain the original pulse sequence data of the cable to be evaluated.

[0017] In a preferred embodiment, the step of performing multi-constraint clustering on the pulse point set in the original pulse sequence data based on the leading edge steepness and pulse width to obtain the defect pulse sequence of the cable to be evaluated includes:

[0018] Waveform edge detection is performed on the original pulse sequence data to obtain the leading edge steepness and pulse width of the cable to be evaluated;

[0019] Based on the leading edge steepness and the pulse width, the pulse points in the original pulse sequence data are subjected to dual threshold morphology screening to obtain the candidate pulse sequence of the cable to be evaluated;

[0020] The candidate pulse sequences are matched for morphological similarity to obtain the pulse waveform cluster of the cable to be evaluated;

[0021] The physical causes of the pulse waveform clusters are determined to obtain the defect pulse sequence of the cable to be evaluated.

[0022] In a preferred embodiment, based on the fluctuation pattern of the time interval between adjacent pulses in the defect pulse sequence and the monotonicity trend of the pulse amplitude sequence, continuous pulses with the same evolution characteristics in the defect pulse sequence are grouped into pulse groups, and the pulse groups are projected onto a time-series axis to obtain the defect evolution time-series map of the cable to be evaluated, including:

[0023] Based on the pulse interval fluctuation spectrum of the defect pulse sequence, the defect pulse sequence is divided into evolution stages to obtain the evolution stage pulse sub-sequence of the cable to be evaluated.

[0024] Monotonicity direction identification is performed on the amplitude sequence of the pulse sub-sequence in the evolution stage to obtain the sequence reversal point of the cable to be evaluated;

[0025] Based on the sequence reversal point, the evolution stage pulse subsequence is divided into sub-stages to obtain the evolution stage pulse fragments of the cable to be evaluated.

[0026] The pulse amplitude range of the pulse segments in the evolution sub-stage is located to obtain the pulse amplitude cluster of the cable to be evaluated;

[0027] The pulse amplitude clusters are screened using pulse density parameters to obtain the pulse groups of the cable to be evaluated;

[0028] The start and end times of the pulse group on the time axis are mapped to the time domain projection interval of the cable to be evaluated.

[0029] The amplitude envelope of the pulse amplitude sequence of the pulse group is fitted to obtain the envelope curve of the cable to be evaluated;

[0030] Using the time-domain projection interval as the horizontal axis span and the envelope curve as the vertical axis amplitude trajectory, a time series map of the defect evolution of the cable to be evaluated is constructed.

[0031] In a preferred embodiment, the step of performing multi-dimensional feature stripping on the defect evolution timeline and nonlinearly coupling the degradation process acceleration and critical breakdown approximation of the stripped features to obtain the composite degradation factor of the cable to be evaluated includes:

[0032] The defect evolution time series map is deconstructed to obtain the time interval sequence and envelope curve sequence of the cable to be evaluated.

[0033] The time interval sequence is stripped of the interval span parameter to obtain the interval span value of the cable to be evaluated;

[0034] An envelope curve curvature evolution analysis is performed on the envelope curve sequence to obtain the slope change rate sequence of the cable to be evaluated;

[0035] Based on the interval span value and the slope change rate sequence, the degradation process parameters of the defect evolution time series are stripped to obtain the degradation process acceleration of the cable to be evaluated.

[0036] Based on the peak and valley amplitudes of the envelope curve sequence, parametric extraction is performed on the defect evolution time series map to obtain the critical breakdown approximation of the cable to be evaluated.

[0037] The composite degradation factor of the cable to be evaluated is obtained by parametrically fusing and mapping the degradation process acceleration with the critical breakdown approximation.

[0038] In a preferred embodiment, the step of performing envelope curve curvature evolution analysis on the envelope curve sequence to obtain the slope change rate sequence of the cable to be evaluated includes:

[0039] The envelope curve sequence is resampled using curve arc length parameterization to obtain a sequence of equal arc length curve segments of the cable to be evaluated;

[0040] The curvature evolution state of the equal arc length curve segment sequence is traced to obtain the curvature evolution trajectory curve of the cable to be evaluated;

[0041] The curvature abrupt change points are detected on the curvature evolution trajectory curve to obtain the curvature abrupt change point set of the cable to be evaluated;

[0042] Using the set of curvature abrupt change points as the dividing points, the sequence of equal arc length curve segments is divided into the deterioration sub-stage curve segments of the cable to be evaluated;

[0043] The curvature change rate of the curve segment of the degradation sub-stage is calculated to obtain the slope change rate sequence of the cable to be evaluated.

[0044] In a preferred embodiment, the formula for calculating the composite degradation factor is as follows:

[0045] ;

[0046] In the formula, The composite degradation factor, To accelerate the degradation process, The critical breakdown approximation is... The frequency of curvature abrupt changes in the set of curvature abrupt change points. The preset reference time interval span, The interval span value, The peak amplitude of the envelope curve sequence is... The valley amplitude of the envelope curve sequence. The preset curvature change gain coefficient, This is a correction factor for the preset time interval span. The preset amplitude ratio correction factor. For natural functions, It is the natural logarithm function.

[0047] In a preferred embodiment, the step of performing trajectory similarity matching on a preset standard degradation trajectory library based on the composite degradation factor, and performing time-series inversion on the registered degradation trajectory curves to obtain the current aging stage identifier of the cable to be evaluated, includes:

[0048] The composite degradation factor is mapped to the feature parameter dimension space in the preset standard degradation trajectory library to obtain the normalized composite degradation factor of the cable to be evaluated.

[0049] Based on the normalized composite degradation factor, Euclidean distance analysis is performed on the standard degradation trajectory curves in the standard degradation trajectory library to obtain the trajectory similarity distance value of the cable to be evaluated.

[0050] The minimum distance among the trajectory similarity distance values ​​is selected for optimal retrieval to obtain the deterioration trajectory curve of the cable to be evaluated;

[0051] Based on the normalized composite degradation factor, the degradation trajectory curve is projected and inverted to locate the time axis points of the cable to be evaluated.

[0052] Based on the time axis points, the stage attribution of the degradation trajectory curve is identified to obtain the current aging stage identifier of the cable to be evaluated.

[0053] In a preferred embodiment, the step of correcting the current aging stage identifier based on the historical operating data of the cable to be evaluated to obtain the estimated remaining service life of the cable to be evaluated includes:

[0054] Extract load fluctuation characteristic parameters, cumulative ambient temperature characteristic parameters, and humidity change characteristic parameters from the historical operating data of the cable to be evaluated;

[0055] The load fluctuation characteristic parameter, the ambient temperature cumulative characteristic parameter, and the humidity change characteristic parameter are registered with operating condition influence weights to obtain the comprehensive operating condition influence factor of the cable to be evaluated.

[0056] Based on the preset aging stage-life benchmark mapping table, the current aging stage identifier is mapped to a stage benchmark value to obtain the benchmark life mapping trajectory point of the cable to be evaluated.

[0057] The working condition correction amount is evaluated by comparing the comprehensive working condition influence factor with the baseline life mapping trajectory point to obtain the working condition disturbance offset of the cable to be evaluated.

[0058] Based on the operating condition disturbance offset, the trajectory offset of the reference life mapping trajectory point is corrected to obtain the estimated remaining operating life of the cable to be evaluated.

[0059] To address the above problems, this invention also provides a cable service life assessment system based on high-frequency pulse sequence analysis, the system comprising:

[0060] The pulse filtering module is used to perform bandpass filtering on the high-frequency pulse signal of the cable to be evaluated to obtain the original pulse sequence data of the cable to be evaluated.

[0061] The source tracing clustering module is used to perform multi-constraint clustering on the pulse point set in the original pulse sequence data based on the leading edge steepness and pulse width to obtain the defect pulse sequence of the cable to be evaluated.

[0062] The time-series graph module is used to group continuous pulses with the same evolution characteristics in the defect pulse sequence into pulse groups based on the time interval fluctuation pattern between adjacent pulses in the defect pulse sequence and the monotonicity trend of the pulse amplitude sequence, and to project the pulse groups onto the time-series axis to obtain the defect evolution time-series graph of the cable to be evaluated.

[0063] The degradation coupling module is used to perform multi-dimensional feature stripping on the defect evolution time series map and to nonlinearly couple the degradation process acceleration and critical breakdown approximation of the stripped feature to obtain the composite degradation factor of the cable to be evaluated.

[0064] The trajectory matching module is used to perform trajectory similarity matching on a preset standard degradation trajectory library based on the composite degradation factor, and to perform time-series inversion on the registered degradation trajectory curves to obtain the current aging stage identifier of the cable to be evaluated.

[0065] The lifespan prediction module is used to correct the current aging stage identifier based on the historical operating condition data of the cable to be evaluated, and obtain the estimated remaining operating life of the cable to be evaluated.

[0066] Compared with the prior art, the present invention has the following beneficial effects:

[0067] 1. This invention performs refined processing of high-frequency pulse signals from cables throughout the entire process. It achieves precise preprocessing of signals through baseline correction and dynamic baseline compensation. It combines the steepness of the leading edge and the pulse width to complete the multi-constraint clustering and source tracing of defect pulse sequences. It can also construct a defect evolution time series map based on pulse evolution characteristics, and peel off the acceleration of the degradation process and the critical breakdown approach degree from multiple dimensions and complete nonlinear coupling to form a composite degradation factor that can accurately characterize the cable degradation state. This makes the extraction and analysis of cable degradation characteristics more comprehensive and accurate, and greatly improves the depth and effectiveness of cable degradation state identification.

[0068] 2. This invention relies on composite degradation factors to achieve accurate similarity matching of the standard degradation trajectory library, and realizes accurate identification of the current aging stage of the cable through time-series inversion. At the same time, it extracts multiple feature parameters from the cable's historical operating conditions to complete the registration of comprehensive operating condition influence factors. Based on these factors, the aging stage identification is modified with targeted service conditions, so that the remaining service life estimate closely matches the actual service state of the cable. This improves the accuracy and reliability of the cable service life assessment results, provides a scientific quantitative basis for cable operation and maintenance planning and decision-making, and the standardized assessment steps also effectively improve the overall efficiency of cable service life assessment. Attached Figure Description

[0069] Figure 1 A flowchart illustrating a cable service life assessment method based on high-frequency pulse sequence analysis provided in an embodiment of the present invention;

[0070] Figure 2 A functional block diagram of a cable service life assessment system based on high-frequency pulse sequence analysis provided in an embodiment of the present invention;

[0071] The objectives, features, and advantages of this invention will be further explained in conjunction with the embodiments and with reference to the accompanying drawings. Detailed Implementation

[0072] It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.

[0073] This application provides a method for assessing cable service life based on high-frequency pulse sequence analysis. The execution entity of this method includes, but is not limited to, at least one of the following electronic devices that can be configured to execute the method provided in this application: a server, a terminal, etc. In other words, the method for assessing cable service life based on high-frequency pulse sequence analysis can be executed by software or hardware installed on a terminal device or a server device. The server includes, but is not limited to, a single server, a server cluster, a cloud server, or a cloud server cluster. The server can be an independent server or a cloud server that provides basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communication, middleware services, domain name services, security services, content delivery networks (CDN), and big data and artificial intelligence platforms.

[0074] Reference Figure 1 The diagram shown is a flowchart illustrating a cable service life assessment method based on high-frequency pulse sequence analysis according to an embodiment of the present invention. In this embodiment, the cable service life assessment method based on high-frequency pulse sequence analysis includes:

[0075] Pt.1. Bandpass filtering is performed on the high-frequency pulse signal of the cable to be evaluated to obtain the original pulse sequence data of the cable to be evaluated;

[0076] In this embodiment of the invention, the process of bandpass filtering the high-frequency pulse signal of the cable to be evaluated to obtain the original pulse sequence data of the cable to be evaluated includes:

[0077] Baseline correction is performed on the high-frequency pulse signal of the cable to be evaluated to obtain the baseline drift of the cable to be evaluated;

[0078] Based on the baseline drift, dynamic baseline compensation is performed on the high-frequency pulse signal to obtain the pulse signal of the cable to be evaluated;

[0079] The frequency domain energy main lobe range of the cable to be evaluated is obtained by performing spectral feature localization on the pulse signal.

[0080] Based on the frequency domain energy main lobe interval, the pulse signal is adaptively truncated to obtain the original pulse sequence data of the cable to be evaluated.

[0081] The average amplitude of the signal during the period without signal interference during the high-frequency pulse signal acquisition of the cable to be evaluated is used as the baseline. The difference between the amplitude of each sampling point of the high-frequency pulse signal of the cable to be evaluated and the amplitude of the baseline is calculated. The specific value of the difference is statistically analyzed point by point. The set of values ​​formed by integrating the difference values ​​of all sampling points in the order of sampling time is the baseline drift of the cable to be evaluated.

[0082] The baseline drift value corresponding to each sampling point in the high-frequency pulse signal of the cable to be evaluated is superimposed on the original amplitude of the sampling point. The amplitude of each sampling point is corrected point by point. The correction operation eliminates the amplitude deviation caused by the baseline drift. The complete signal obtained after this point-by-point correction operation is the pulse signal of the cable to be evaluated.

[0083] A complete frequency domain transformation operation is performed on the pulse signal of the cable to be evaluated, converting the pulse signal in the time domain dimension into a spectrum signal in the frequency domain dimension. The energy values ​​corresponding to each frequency point in the spectrum signal are statistically analyzed. First, the total energy value of the spectrum signal is calculated. Then, with the center frequency of the spectrum signal as the reference, each frequency point is traversed sequentially towards the high-frequency side and the low-frequency side, and the energy value is accumulated. When the proportion of the accumulated energy value on one side to the total energy value reaches 99%, the traversal operation on that side is stopped. The frequency range between the frequency points where the traversal stops on the high-frequency side and the low-frequency side is the main lobe interval of the frequency domain energy of the cable to be evaluated.

[0084] Based on the upper and lower limits of the main lobe frequency range of the frequency domain energy of the cable to be evaluated, the passband range of the passband filter is precisely set. The pulse signal of the cable to be evaluated is subjected to passband filtering, retaining only the frequency components within the passband range and completely eliminating all frequency components outside the passband range. The frequency components retained after filtering are then subjected to time-domain restoration. The restored time-domain signal is arranged into discrete pulse amplitude data sequences according to the sampling time sequence. This ordered pulse amplitude data sequence is the original pulse sequence data of the cable to be evaluated.

[0085] Pt.2. Based on the leading edge steepness and pulse width of the original pulse sequence data, perform multi-constraint clustering to trace the pulse point set in the original pulse sequence data to obtain the defect pulse sequence of the cable to be evaluated.

[0086] In this embodiment of the invention, the step of performing multi-constraint clustering to trace the pulse point set in the original pulse sequence data based on the leading edge steepness and pulse width of the original pulse sequence data to obtain the defect pulse sequence of the cable to be evaluated includes:

[0087] Waveform edge detection is performed on the original pulse sequence data to obtain the leading edge steepness and pulse width of the cable to be evaluated;

[0088] Based on the leading edge steepness and the pulse width, the pulse points in the original pulse sequence data are subjected to dual threshold morphology screening to obtain the candidate pulse sequence of the cable to be evaluated;

[0089] The candidate pulse sequences are matched for morphological similarity to obtain the pulse waveform cluster of the cable to be evaluated;

[0090] The physical causes of the pulse waveform clusters are determined to obtain the defect pulse sequence of the cable to be evaluated.

[0091] To locate the waveform characteristics of the original pulse sequence data of the cable to be evaluated, pulse-by-pulse sampling is performed. First, the starting and ending sampling points of the rising edge of each pulse are determined. The starting sampling point is the sampling point where the pulse amplitude reaches 10% of its peak value, and the ending sampling point is the sampling point where the pulse amplitude reaches 90% of its peak value. The ratio of the amplitude change to the time change between the two sampling points is calculated to obtain the leading edge steepness of a single pulse. Then, the starting and ending sampling points where the pulse amplitude is higher than 50% of its peak value are determined. The number of sampling points between the two points is multiplied by the fixed sampling interval to obtain the pulse width of a single pulse. The leading edge steepness and pulse width of all pulses are integrated in the order of sampling time. The resulting overall data set is the leading edge steepness and pulse width of the cable to be evaluated.

[0092] The preset effective threshold range for leading edge steepness is 0.05V / μs to 5V / μs, and the preset effective threshold range for pulse width is 0.1μs to 10μs. For each pulse point in the original pulse sequence data, its corresponding leading edge steepness and pulse width values ​​are extracted. It is then determined whether the leading edge steepness is within the preset effective threshold range and whether the pulse width is within the preset effective threshold range. Only pulse points that meet both conditions are retained. All retained pulse points are arranged sequentially according to the original sampling time. The resulting ordered set of pulse points is the candidate pulse sequence for the cable to be evaluated.

[0093] The complete waveform features of each candidate pulse in the candidate pulse sequence are extracted, specifically including four core features: rise edge duration, fall edge duration, peak position in the pulse time domain, and amplitude variation trend in the entire time domain. Taking the first pulse in the candidate pulse sequence as the reference waveform, the four core features of each of the remaining candidate pulses are extracted in turn and compared with the corresponding features of the reference waveform. The overlap ratio of features is statistically analyzed, and the feature overlap threshold is set to 85%. Candidate pulses with a feature overlap of 85% or higher are classified into the same waveform category. All pulses in the candidate pulse sequence are classified in this way. Each classified waveform category is a pulse waveform cluster of the cable to be evaluated.

[0094] A physical feature library of pulse waveforms corresponding to various inherent defects in cables during operation is pre-established. The feature library clearly defines the exclusive pulse waveform features corresponding to each cable defect, such as insulation damage, partial discharge, and conductor aging. The overall waveform features of each pulse waveform cluster are precisely compared with the exclusive pulse waveform features of various cable defects in the feature library one by one. Pulse waveform clusters that do not match the exclusive waveform features of various cable defects are eliminated, and only pulse waveform clusters that match the exclusive waveform features of cable defects are retained. The pulse points in all retained pulse waveform clusters are re-integrated into a continuous pulse sequence according to the original sampling time sequence. This integrated pulse sequence is the defect pulse sequence of the cable to be evaluated.

[0095] Pt.3. Based on the time interval fluctuation pattern between adjacent pulses in the defect pulse sequence and the monotonicity trend of the pulse amplitude sequence, continuous pulses with the same evolution characteristics in the defect pulse sequence are grouped into pulse groups, and the pulse groups are projected onto the time axis to obtain the defect evolution time sequence map of the cable to be evaluated.

[0096] In this embodiment of the invention, based on the time interval fluctuation pattern between adjacent pulses in the defect pulse sequence and the monotonicity trend of the pulse amplitude sequence, continuous pulses with the same evolution characteristics in the defect pulse sequence are grouped into pulse groups, and the pulse groups are projected onto a time-series axis to obtain the defect evolution time-series map of the cable to be evaluated, including:

[0097] Based on the pulse interval fluctuation spectrum of the defect pulse sequence, the defect pulse sequence is divided into evolution stages to obtain the evolution stage pulse sub-sequence of the cable to be evaluated.

[0098] Monotonicity direction identification is performed on the amplitude sequence of the pulse sub-sequence in the evolution stage to obtain the sequence reversal point of the cable to be evaluated;

[0099] Based on the sequence reversal point, the evolution stage pulse subsequence is divided into sub-stages to obtain the evolution stage pulse fragments of the cable to be evaluated.

[0100] The pulse amplitude range of the pulse segments in the evolution sub-stage is located to obtain the pulse amplitude cluster of the cable to be evaluated;

[0101] The pulse amplitude clusters are screened using pulse density parameters to obtain the pulse groups of the cable to be evaluated;

[0102] The start and end times of the pulse group on the time axis are mapped to the time domain projection interval of the cable to be evaluated.

[0103] The amplitude envelope of the pulse amplitude sequence of the pulse group is fitted to obtain the envelope curve of the cable to be evaluated;

[0104] Using the time-domain projection interval as the horizontal axis span and the envelope curve as the vertical axis amplitude trajectory, a time series map of the defect evolution of the cable to be evaluated is constructed.

[0105] First, calculate the time interval between every two adjacent pulses in the defect pulse sequence of the cable to be evaluated. Arrange all time intervals in the order of pulse occurrence to form a pulse interval sequence. Construct a pulse interval fluctuation spectrum based on this sequence. Set the pulse interval fluctuation deviation threshold to 20%. Calculate the relative deviation value between two adjacent time intervals in the fluctuation spectrum. When the relative deviation value exceeds 20%, mark the position as the evolution stage dividing point. Divide the defect pulse sequence into multiple continuous pulse sequence segments with the dividing point as the boundary. Each continuous pulse sequence segment is the evolution stage pulse subsequence of the cable to be evaluated.

[0106] The peak amplitude of all pulses in the pulse subsequence of each evolution stage is extracted and arranged in the order of pulse appearance to form an amplitude sequence. Starting from the first data in the amplitude sequence, the magnitude relationship between two adjacent amplitudes is compared sequentially to determine whether the adjacent amplitudes are increasing, decreasing, or equal in monotonicity. The preset monotonicity duration determination number is 5 consecutive data. When the monotonicity direction of 5 consecutive adjacent amplitudes changes, the pulse sampling point at the point of direction change is marked as the sequence reversal point. All the marked sampling points of this type in the pulse subsequence of each evolution stage are integrated, and the resulting point set is the sequence reversal point of the cable to be evaluated.

[0107] Using the sequence reversal point in the pulse subsequence of each evolution stage as a clear dividing boundary, the originally continuous evolution stage pulse subsequence is divided into multiple continuous pulse segments without sequence reversal points. Each continuous pulse segment formed after the division is the evolution stage pulse segment of the cable to be evaluated.

[0108] The peak amplitude of all pulses in each evolutionary sub-stage pulse segment is extracted, and the maximum and minimum peak amplitudes within the segment are calculated to determine the exclusive pulse amplitude range corresponding to each evolutionary sub-stage pulse segment. The preset amplitude range overlap threshold is 90%. By comparing the amplitude ranges of pulse segments from different evolutionary sub-stages, pulse segments from different evolutionary sub-stages with an amplitude range overlap of 90% or higher are grouped into the same category. The set formed by integrating the amplitude range corresponding to each category and all the pulse segments from the evolutionary sub-stages to which it belongs is the pulse amplitude cluster of the cable to be evaluated.

[0109] The number of pulses contained in each pulse amplitude cluster per unit time is calculated, and this value is the pulse density of the pulse amplitude cluster. First, the average pulse density of all evolution sub-stage pulse segments within the same pulse amplitude cluster is calculated. The preset pulse density deviation threshold is 15%. The relative deviation between the pulse density of each evolution sub-stage pulse segment within the cluster and the average pulse density within the cluster is judged one by one. Only evolution sub-stage pulse segments with a relative deviation within 15% are retained. All retained pulse segments within the same pulse amplitude cluster are re-integrated into a continuous pulse sequence according to the pulse appearance time order. The integrated continuous pulse sequence is the pulse group of the cable to be evaluated.

[0110] The actual acquisition time of the first pulse in each pulse group is extracted as the start time of the pulse group, and the actual acquisition time of the last pulse in each pulse group is extracted as the end time of the pulse group. The start time and the end time are taken as the two endpoints of the interval. The continuous time range that includes the time information of all pulses in the pulse group is marked on the time axis, which is the time domain projection interval of the cable to be evaluated.

[0111] Extract the peak amplitude of all pulses in each pulse group, arrange them in the order of their appearance to form a pulse amplitude sequence, mark all data points of the pulse amplitude sequence on the coordinate system with time as the horizontal axis and pulse peak amplitude as the vertical axis, connect the amplitude maxima points in each continuous local area in sequence and smooth them to form a continuous curve that completely envelops all data points of the pulse amplitude sequence. This continuous curve is the envelope curve of the cable to be evaluated.

[0112] Using time as the horizontal axis and pulse peak amplitude as the vertical axis, the time-domain projection interval corresponding to each pulse group is precisely marked on the horizontal axis of the graph, ensuring that the span of the horizontal axis perfectly matches the time range of the time-domain projection interval. Then, the envelope curve corresponding to the pulse group is precisely plotted within the vertical axis region corresponding to the marked horizontal axis span. The graph portions corresponding to all pulse groups are continuously and seamlessly stitched together according to the pulse occurrence time sequence, forming a complete visualization graph, which is the defect evolution time-series graph of the cable to be evaluated.

[0113] Pt.4. Perform multi-dimensional feature stripping on the defect evolution time series map, and nonlinearly couple the degradation process acceleration and critical breakdown approximation of the stripped feature to obtain the composite degradation factor of the cable to be evaluated.

[0114] In this embodiment of the invention, the step of performing multi-dimensional feature stripping on the defect evolution time series map and nonlinearly coupling the degradation process acceleration of the stripped feature stripping with the critical breakdown approximation to obtain the composite degradation factor of the cable to be evaluated includes:

[0115] The defect evolution time series map is deconstructed to obtain the time interval sequence and envelope curve sequence of the cable to be evaluated.

[0116] The time interval sequence is stripped of the interval span parameter to obtain the interval span value of the cable to be evaluated;

[0117] An envelope curve curvature evolution analysis is performed on the envelope curve sequence to obtain the slope change rate sequence of the cable to be evaluated;

[0118] Based on the interval span value and the slope change rate sequence, the degradation process parameters of the defect evolution time series are stripped to obtain the degradation process acceleration of the cable to be evaluated.

[0119] Based on the peak and valley amplitudes of the envelope curve sequence, parametric extraction is performed on the defect evolution time series map to obtain the critical breakdown approximation of the cable to be evaluated.

[0120] The composite degradation factor of the cable to be evaluated is obtained by parametrically fusing and mapping the degradation process acceleration with the critical breakdown approximation.

[0121] The step of performing envelope curve curvature evolution analysis on the envelope curve sequence to obtain the slope change rate sequence of the cable to be evaluated includes:

[0122] The envelope curve sequence is resampled using curve arc length parameterization to obtain a sequence of equal arc length curve segments of the cable to be evaluated;

[0123] The curvature evolution state of the equal arc length curve segment sequence is traced to obtain the curvature evolution trajectory curve of the cable to be evaluated;

[0124] The curvature abrupt change points are detected on the curvature evolution trajectory curve to obtain the curvature abrupt change point set of the cable to be evaluated;

[0125] Using the set of curvature abrupt change points as the dividing points, the sequence of equal arc length curve segments is divided into the deterioration sub-stage curve segments of the cable to be evaluated;

[0126] The curvature change rate of the curve segment of the degradation sub-stage is calculated to obtain the slope change rate sequence of the cable to be evaluated.

[0127] The formula for calculating the composite degradation factor is as follows:

[0128] ;

[0129] In the formula, The composite degradation factor, To accelerate the degradation process, The critical breakdown approximation is... The frequency of curvature abrupt changes in the set of curvature abrupt change points. The preset reference time interval span, The interval span value, The peak amplitude of the envelope curve sequence is... The valley amplitude of the envelope curve sequence. The preset curvature change gain coefficient, This is a correction factor for the preset time interval span. The preset amplitude ratio correction factor. For natural functions, It is the natural logarithm function.

[0130] The defect evolution time series map is decomposed into a hierarchical topology. According to the chronological order of the pulse groups, the time domain projection interval corresponding to each pulse group in the map is extracted to form an independent time interval unit. The envelope curve corresponding to each pulse group is extracted to form an independent envelope curve unit. All time interval units are arranged continuously in the original time order to form an ordered set, which is the time interval sequence of the cable to be evaluated. At the same time, all envelope curve units are arranged continuously in the original time order to form an ordered set, which is the envelope curve sequence of the cable to be evaluated.

[0131] For the time interval sequence of the cable to be evaluated, the start and end times of each time interval unit are extracted, and the time difference between the end and start times of each time interval unit is calculated. This time difference is the span parameter of a single time interval unit. The span parameters of all time interval units are continuously integrated according to the original arrangement order of the time interval sequence, and the resulting ordered set of values ​​is the interval span value of the cable to be evaluated.

[0132] For each envelope curve in the envelope curve sequence of the cable to be evaluated, sampling points are taken at equal intervals with a fixed time interval of 0.01μs as the sampling reference. The time coordinates and amplitude coordinates of all sampling points on each envelope curve are obtained. The ratio of the amplitude change to the time change between two adjacent sampling points on each envelope curve is calculated to obtain the single-point slope value. Then, the ratio of the difference between the slope values ​​of two adjacent single points to the time change is calculated to obtain the single-point slope change rate. All single-point slope change rates on each envelope curve are arranged in chronological order. Finally, the slope change rate sequences of all envelope curves are integrated in the original order of the envelope curve sequence. The complete and ordered numerical set formed is the slope change rate sequence of the cable to be evaluated.

[0133] Using the span parameter of each time interval unit in the span value of the cable to be evaluated as the normalization coefficient, the slope change rate values ​​in the corresponding time interval of the slope change rate sequence are normalized, that is, each slope change rate value is divided by the span parameter of the corresponding interval. After the normalization of all values ​​is completed, the processed slope change rate values ​​are continuously integrated in chronological order. The resulting ordered set of values ​​that can characterize the change of cable degradation rate is the degradation process acceleration of the cable to be evaluated.

[0134] The maximum and minimum amplitude points of each envelope curve in the envelope curve sequence of the cable to be evaluated are extracted. The corresponding amplitude values ​​are the peak amplitude and valley amplitude of a single envelope curve, respectively. Based on the critical amplitude of insulation breakdown specified by the cable manufacturer, the ratio of the peak amplitude of each envelope curve to the benchmark amplitude is calculated. Then, the difference between the peak amplitude and valley amplitude of a single envelope curve is used for numerical correction. All the corrected values ​​of the envelope curves are integrated in the original order of the envelope curve sequence. The resulting ordered set of values ​​that can characterize the degree to which the cable approaches the breakdown state is the critical breakdown approach degree of the cable to be evaluated.

[0135] The values ​​of the acceleration of the degradation process of the cable to be evaluated and the critical breakdown approach are matched one-to-one according to the time dimension. Based on the parameter change range of the entire life cycle of cable degradation, the two sets of matched values ​​are mapped to a unified numerical range of 0 to 1. Then, the mapped values ​​are subjected to hierarchical fusion processing, that is, each set of corresponding values ​​is weighted and integrated according to the proportion of degradation process and the proportion of breakdown approach. All the fused values ​​are continuously integrated in chronological order to form a single comprehensive numerical set, which is the composite degradation factor of the cable to be evaluated.

[0136] For each envelope curve in the envelope curve sequence of the cable to be evaluated, a fixed equal arc length sampling step of 0.1 mm is preset. First, the arc length between adjacent points is calculated sequentially through the curve coordinate points and accumulated to obtain the total arc length of each envelope curve. Then, starting from the starting endpoint of each envelope curve, curve segments are sequentially extracted according to the preset fixed equal arc length sampling step until the end endpoint of the curve is extracted. All equal arc length segments corresponding to each envelope curve are arranged according to the curve direction. Then, all equal arc length segments of the envelope curves are integrated according to the original order of the envelope curve sequence. The resulting ordered set of curve segments is the equal arc length curve segment sequence of the cable to be evaluated.

[0137] For each equal-arc-length curve segment in the sequence of equal-arc-length curve segments of the cable to be evaluated, the temporal and amplitude coordinates of the two endpoints and the midpoint of the segment are extracted. The curvature of the curve is determined based on the spatial relationship of the three coordinates, thereby obtaining a single curvature value corresponding to each equal-arc-length curve segment. Then, with the arc length as the horizontal axis and the curvature value as the vertical axis, all curvature values ​​in the sequence of equal-arc-length curve segments are labeled sequentially according to the original arrangement order of the segments and connected continuously and smoothly. The resulting continuous curve that can completely represent the change of curvature with the arc length is the curvature evolution trajectory curve of the cable to be evaluated.

[0138] The preset threshold for the relative rate of change of curvature is 30%. For the curvature evolution trajectory curve of the cable to be evaluated, the absolute difference between two adjacent curvature values ​​on the curve is calculated in turn. Then, the absolute difference is divided by the previous curvature value to obtain the relative rate of change of adjacent curvature. When the calculated relative rate of change reaches 30%, the endpoint of the curve segment of equal arc length corresponding to the position is marked on the curvature evolution trajectory curve. This marked point is the curvature abrupt change point. All the marked curvature abrupt change points on the curvature evolution trajectory curve are integrated in order of arc length. The resulting point set is the curvature abrupt change point set of the cable to be evaluated.

[0139] Each point in the set of curvature abrupt change points of the cable to be evaluated is used as a clear dividing boundary. In the sequence of equal arc length curve segments, all equal arc length curve segments between two adjacent curvature abrupt change points are continuously integrated. At the same time, the equal arc length curve segments between the start endpoint of the sequence and the first curvature abrupt change point, and between the last curvature abrupt change point and the end endpoint of the sequence are integrated separately. Each combination of continuous equal arc length curve segments formed after integration is the deterioration sub-stage curve segment of the cable to be evaluated.

[0140] For each degradation sub-stage curve segment of the cable to be evaluated, the curvature and arc length values ​​corresponding to all equal arc length curve segments within the segment are extracted. The ratio of the difference in curvature value to the difference in arc length value between two adjacent equal arc length curve segments within the segment is calculated sequentially to obtain the curvature change rate value within that degradation sub-stage curve segment. Then, the curvature change rate values ​​of each degradation sub-stage curve segment are mapped to the corresponding slope change rate value according to the correspondence between arc length and time. The slope change rate values ​​of all degradation sub-stage curve segments are continuously integrated according to the original time order of the envelope curve sequence. The resulting ordered set of values ​​is the slope change rate sequence of the cable to be evaluated.

[0141] The acceleration of the degradation process is a characteristic parameter of the cable to be evaluated obtained by stripping the degradation process parameters from the defect evolution time series map based on the interval span value and slope change rate sequence.

[0142] The critical breakdown approximation is a characteristic parameter of the cable to be evaluated, obtained by parametric extraction of the defect evolution time sequence spectrum based on the peak and valley amplitudes of the envelope curve sequence.

[0143] The frequency of curvature abrupt changes is the specific number of curvature abrupt changes contained in the set of curvature abrupt changes obtained after detecting curvature abrupt changes in the curvature evolution trajectory curve.

[0144] The reference time interval span is a fixed value that is a standard time interval span pre-set for cable degradation assessment.

[0145] The interval span value is a characteristic parameter of the cable to be evaluated obtained after stripping the interval span parameter from the time interval sequence.

[0146] Peak amplitude is the specific numerical value of the maximum amplitude corresponding to each envelope curve extracted from the envelope curve sequence.

[0147] The valley amplitude is the minimum amplitude value extracted from each envelope curve in the envelope curve sequence. The curvature mutation gain coefficient is a fixed correction coefficient pre-set to determine the degree of influence of curvature mutation on cable degradation.

[0148] The time interval span correction factor is a fixed correction factor that is pre-set to assess the impact of the time interval span on cable degradation.

[0149] The amplitude ratio correction factor is a fixed correction factor that is pre-set to assess the impact of the ratio of peak amplitude to valley amplitude on cable degradation.

[0150] This calculation method combines the acceleration of the degradation process with the frequency of curvature abrupt changes through exponential gain processing, combines the critical breakdown approach with the frequency of curvature abrupt changes through logarithmic processing, then corrects the time dimension by using the ratio of the reference time interval span to the interval span value, and corrects the amplitude dimension by using the ratio of the peak amplitude to the valley amplitude. Finally, the processed degradation process acceleration and critical breakdown approach are nonlinearly coupled to obtain a composite degradation factor that comprehensively reflects the speed of the degradation process of the cable under evaluation, the degree of critical breakdown approach, the impact of the degradation abrupt change caused by curvature abrupt changes, the time dimension impact of the time interval span, and the amplitude dimension impact of the peak-to-valley amplitude ratio. This factor, as a comprehensive feature parameter characterizing the overall degradation state of the cable under evaluation, provides a unified and effective feature basis for subsequent trajectory similarity matching based on a preset standard degradation trajectory library, and also lays a precise parameter foundation for accurately identifying the current aging stage of the cable under evaluation.

[0151] Pt.5. Based on the composite degradation factor, perform trajectory similarity matching on the preset standard degradation trajectory library, and perform time-series inversion on the registered degradation trajectory curve to obtain the current aging stage identifier of the cable to be evaluated.

[0152] In this embodiment of the invention, the step of performing trajectory similarity matching on a preset standard degradation trajectory library based on the composite degradation factor, and performing time-series inversion on the registered degradation trajectory curves to obtain the current aging stage identifier of the cable to be evaluated, includes:

[0153] The composite degradation factor is mapped to the feature parameter dimension space in the preset standard degradation trajectory library to obtain the normalized composite degradation factor of the cable to be evaluated.

[0154] Based on the normalized composite degradation factor, Euclidean distance analysis is performed on the standard degradation trajectory curves in the standard degradation trajectory library to obtain the trajectory similarity distance value of the cable to be evaluated.

[0155] The minimum distance among the trajectory similarity distance values ​​is selected for optimal retrieval to obtain the deterioration trajectory curve of the cable to be evaluated;

[0156] Based on the normalized composite degradation factor, the degradation trajectory curve is projected and inverted to locate the time axis points of the cable to be evaluated.

[0157] Based on the time axis points, the stage attribution of the degradation trajectory curve is identified to obtain the current aging stage identifier of the cable to be evaluated.

[0158] The feature parameter dimension space of the preset standard degradation trajectory library is set to a unified range of 0 to 1 based on the extreme value of the composite degradation factor during the entire life cycle of the cable. The extreme value is obtained from the full life cycle test data of the same type of cable. The difference between all values ​​of the composite degradation factor of the cable to be evaluated and the minimum value of the extreme value is calculated. Then, the ratio of the calculated difference to the difference between the maximum and minimum values ​​of the extreme value is calculated. In this way, all values ​​of the composite degradation factor are converted to the range of 0 to 1. The feature parameter set obtained after this conversion is the normalized composite degradation factor of the cable to be evaluated.

[0159] The pre-set standard degradation trajectory library stores multiple standard degradation trajectory curves for cables of the same type. Each curve corresponds to a normalized feature parameter sequence in the dimension space of 0 to 1. The normalized composite degradation factor of the cable to be evaluated is used as an independent feature parameter sequence and is matched point by point with the normalized feature parameter sequence of each standard degradation trajectory curve in the library. The difference between the values ​​of each set of corresponding points is calculated and the difference is squared. All the squared values ​​are accumulated and the square root of the accumulated result is taken to obtain the distance value of a single standard curve. The distance values ​​corresponding to all standard curves in the library are integrated in the order of curve number, and the resulting set of values ​​is the trajectory similarity distance value of the cable to be evaluated.

[0160] All values ​​of the trajectory similarity distance values ​​of the cable to be evaluated are arranged in ascending order. The value at the top of the arrangement is selected as the minimum distance value. The corresponding standard deterioration trajectory curve is accurately retrieved from the preset standard deterioration trajectory library through the standard curve number corresponding to the minimum distance value. The retrieved standard deterioration trajectory curve is the deterioration trajectory curve of the cable to be evaluated.

[0161] The degradation trajectory curve of the cable to be evaluated is constructed as a two-dimensional coordinate curve with time as the horizontal axis and the normalized composite degradation factor as the vertical axis. First, the comprehensive characteristic value of the normalized composite degradation factor of the cable to be evaluated is calculated. The position point corresponding to the comprehensive characteristic value is accurately marked on the vertical axis of the degradation trajectory curve. A horizontal projection line perpendicular to the vertical axis is drawn from this position point to the degradation trajectory curve. The intersection of the horizontal projection line and the degradation trajectory curve yields a unique projection intersection point. A vertical line perpendicular to the horizontal axis is drawn from this projection intersection point to the horizontal axis of the degradation trajectory curve. The unique intersection point obtained by the vertical line and the horizontal axis is the time axis point of the cable to be evaluated.

[0162] The horizontal axis of the degradation trajectory curve of the cable to be evaluated is pre-divided into multiple continuous and non-overlapping fixed time intervals according to the aging process of the cable's entire life cycle. Each time interval is assigned a unique aging stage identifier consisting of a combination of text and numbers. The division of each interval is based on the aging stage data of the full life cycle test of similar cables. The specific coordinate position of the time axis point of the cable to be evaluated on the horizontal axis of the degradation trajectory curve is precisely matched with all the preset aging stage time intervals to determine the unique time interval to which the time axis point belongs. The unique aging stage identifier corresponding to the time interval is extracted, and this identifier is the current aging stage identifier of the cable to be evaluated.

[0163] Pt.6. Based on the historical operating condition data of the cable to be evaluated, the current aging stage identifier is corrected for service conditions to obtain the estimated remaining service life of the cable to be evaluated.

[0164] In this embodiment of the invention, the step of correcting the current aging stage identifier based on the historical operating condition data of the cable to be evaluated to obtain the estimated remaining service life of the cable to be evaluated includes:

[0165] Extract load fluctuation characteristic parameters, cumulative ambient temperature characteristic parameters, and humidity change characteristic parameters from the historical operating data of the cable to be evaluated;

[0166] The load fluctuation characteristic parameter, the ambient temperature cumulative characteristic parameter, and the humidity change characteristic parameter are registered with operating condition influence weights to obtain the comprehensive operating condition influence factor of the cable to be evaluated.

[0167] Based on the preset aging stage-life benchmark mapping table, the current aging stage identifier is mapped to a stage benchmark value to obtain the benchmark life mapping trajectory point of the cable to be evaluated.

[0168] The working condition correction amount is evaluated by comparing the comprehensive working condition influence factor with the baseline life mapping trajectory point to obtain the working condition disturbance offset of the cable to be evaluated.

[0169] Based on the operating condition disturbance offset, the trajectory offset of the reference life mapping trajectory point is corrected to obtain the estimated remaining operating life of the cable to be evaluated.

[0170] Real-time load values ​​throughout the entire service life of the cable under evaluation are extracted from historical operating data. Using a fixed statistical period of 24 hours, the difference between the maximum and minimum real-time load values ​​in each period is calculated. This difference is then compared to the cable's rated load. The ratios from all statistical periods are integrated chronologically to form an ordered set of values, which is the load fluctuation characteristic parameter. Simultaneously, real-time ambient temperature values ​​throughout the entire service life are extracted, with 25℃ as the baseline ambient temperature for normal cable operation. The duration of each temperature exceeding the baseline value is multiplied by the temperature exceeding the baseline value, and all products are summed to obtain the cumulative ambient temperature characteristic parameter. Additionally, real-time ambient humidity values ​​throughout the entire service life are extracted, with 60%RH as the baseline ambient humidity for normal cable operation. Using a fixed statistical period of 30 days, the average percentage deviation of ambient humidity from the baseline value in each period is calculated. The average values ​​from all statistical periods are integrated chronologically to form an ordered set of values, which is the humidity change characteristic parameter.

[0171] Based on the aging test data of similar cable models, fixed influence weights of 40%, 40%, and 20% are assigned to the load fluctuation characteristic parameter, the ambient temperature cumulative characteristic parameter, and the humidity change characteristic parameter, respectively. First, all values ​​of the three characteristic parameters are calculated with their respective extreme values ​​and mapped to a unified numerical range of 0 to 1 to complete the normalization of all characteristic parameters. Then, the normalized value of each characteristic parameter is multiplied with its corresponding fixed influence weight, and the cumulative value of the three product results is calculated. This cumulative value is the comprehensive operating condition influence factor of the cable to be evaluated.

[0172] The preset aging stage-life benchmark mapping table is a data table that establishes a one-to-one correspondence between aging stage identifiers and remaining life benchmark values ​​for cables of the same type under standard operating conditions. Each unique aging stage identifier in the table corresponds to a definite remaining life benchmark value, and this benchmark value corresponds to a unique trajectory point coordinate in the life trajectory coordinate system. The current aging stage identifier of the cable to be evaluated is precisely matched with the aging stage identifier in the mapping table, and the trajectory point coordinates in the life trajectory coordinate system corresponding to the successfully matched identifier are retrieved. The trajectory point corresponding to this coordinate is the benchmark life mapping trajectory point of the cable to be evaluated.

[0173] Extract the corresponding remaining life reference value under standard operating conditions, i.e., the reference life mapping trajectory point, from the reference life mapping trajectory point of the cable to be evaluated. Set the reference value of the comprehensive operating condition influence factor under standard operating conditions to 0. Calculate the difference between the comprehensive operating condition influence factor of the cable to be evaluated and the reference value. Based on the operating condition aging test data of similar cable models, construct an operating condition aging coefficient table. Calculate the specific offset value of the reference life mapping trajectory point caused by the actual operating conditions based on the specific value of the difference. At the same time, determine the coordinate axis offset direction of the offset value in the life trajectory coordinate system by combining the positive and negative signs of the difference. The trajectory offset formed by combining the specific offset value with the clear offset direction is the operating condition disturbance offset of the cable to be evaluated.

[0174] Using the baseline life-mapped trajectory point of the cable to be evaluated as the original point in the life trajectory coordinate system, and according to the coordinate axis offset direction and specific offset value determined by the operating condition disturbance offset, the original point is precisely offset in the horizontal and vertical directions in the life trajectory coordinate system to obtain the new trajectory point after offset correction. The specific value of the remaining life corresponding to the new trajectory point in the life trajectory coordinate system is retrieved, and this specific value is the estimated remaining operating life of the cable to be evaluated.

[0175] like Figure 2 The diagram shown is a functional block diagram of a cable service life assessment system based on high-frequency pulse sequence analysis provided in an embodiment of the present invention.

[0176] The cable service life assessment system based on high-frequency pulse sequence analysis described in this invention can be installed in electronic devices. Depending on the functions implemented, the cable service life assessment system based on high-frequency pulse sequence analysis may include a pulse filtering module, a source tracing and clustering module, a time series mapping module, a degradation coupling module, a trajectory matching module, and a service life prediction module. The module described in this invention can also be called a unit, which refers to a series of computer program segments that can be executed by the processor of an electronic device and can perform a fixed function, stored in the memory of the electronic device.

[0177] In this embodiment, the functions of each module / unit are as follows:

[0178] The pulse filtering module is used to perform bandpass filtering on the high-frequency pulse signal of the cable to be evaluated to obtain the original pulse sequence data of the cable to be evaluated.

[0179] The source tracing clustering module is used to perform multi-constraint clustering tracing on the pulse point set in the original pulse sequence data based on the leading edge steepness and pulse width of the original pulse sequence data, so as to obtain the defect pulse sequence of the cable to be evaluated.

[0180] The time-series graph module is used to group continuous pulses with the same evolution characteristics in the defect pulse sequence into pulse groups based on the time interval fluctuation pattern between adjacent pulses in the defect pulse sequence and the monotonicity trend of the pulse amplitude sequence, and to project the pulse groups onto the time-series axis to obtain the defect evolution time-series graph of the cable to be evaluated.

[0181] The degradation coupling module is used to perform multi-dimensional feature stripping on the defect evolution time series map and to nonlinearly couple the degradation process acceleration and critical breakdown approximation of the stripped feature to obtain the composite degradation factor of the cable to be evaluated.

[0182] The trajectory matching module is used to perform trajectory similarity matching on a preset standard degradation trajectory library based on the composite degradation factor, and to perform time-series inversion on the registered degradation trajectory curves to obtain the current aging stage identifier of the cable to be evaluated.

[0183] The lifespan estimation module is used to correct the current aging stage identifier based on the historical operating condition data of the cable to be evaluated, so as to obtain the estimated remaining operating life of the cable to be evaluated.

[0184] In the several embodiments provided by this invention, it should be understood that the disclosed methods and systems can be implemented in other ways. For example, the system embodiments described above are merely illustrative; for instance, the division of modules is only a logical functional division, and other division methods may be used in actual implementation.

[0185] The modules described as separate components may or may not be physically separate. The components shown as modules may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs.

[0186] Furthermore, the functional modules in the various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or in the form of hardware plus software functional modules.

[0187] It will be apparent to those skilled in the art that the present invention is not limited to the details of the exemplary embodiments described above, and that the present invention can be implemented in other specific forms without departing from the spirit or essential characteristics of the present invention.

[0188] This application embodiment can acquire and process relevant data based on artificial intelligence technology. Artificial intelligence is the theory, method, technology, and application system that uses digital computers or machines controlled by digital computers to simulate, extend, and expand human intelligence, perceive the environment, acquire knowledge, and use that knowledge to obtain optimal results.

[0189] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention.

Claims

1. A method for assessing cable service life based on high-frequency pulse sequence analysis, characterized in that, The method includes: Pt.

1. Bandpass filtering is performed on the high-frequency pulse signal of the cable to be evaluated to obtain the original pulse sequence data of the cable to be evaluated; Pt.

2. Based on the leading edge steepness and pulse width of the original pulse sequence data, perform multi-constraint clustering to trace the pulse point set in the original pulse sequence data to obtain the defect pulse sequence of the cable to be evaluated. Pt.

3. Based on the time interval fluctuation pattern between adjacent pulses in the defect pulse sequence and the monotonicity trend of the pulse amplitude sequence, continuous pulses with the same evolution characteristics in the defect pulse sequence are grouped into pulse groups, and the pulse groups are projected onto the time axis to obtain the defect evolution time sequence map of the cable to be evaluated. Pt.

4. Perform multi-dimensional feature stripping on the defect evolution time series map, and nonlinearly couple the degradation process acceleration and critical breakdown approximation of the stripped feature to obtain the composite degradation factor of the cable to be evaluated. Pt.

5. Based on the composite degradation factor, perform trajectory similarity matching on the preset standard degradation trajectory library, and perform time-series inversion on the registered degradation trajectory curve to obtain the current aging stage identifier of the cable to be evaluated. Pt.

6. Based on the historical operating condition data of the cable to be evaluated, the current aging stage identifier is corrected for service conditions to obtain the estimated remaining service life of the cable to be evaluated.

2. The cable service life assessment method based on high-frequency pulse sequence analysis as described in claim 1, characterized in that, The high-frequency pulse signal of the cable to be evaluated is bandpass filtered to obtain the original pulse sequence data of the cable to be evaluated, including: Baseline correction is performed on the high-frequency pulse signal of the cable to be evaluated to obtain the baseline drift of the cable to be evaluated; Based on the baseline drift, dynamic baseline compensation is performed on the high-frequency pulse signal to obtain the pulse signal of the cable to be evaluated; The frequency domain energy main lobe range of the cable to be evaluated is obtained by performing spectral feature localization on the pulse signal. Based on the frequency domain energy main lobe interval, the pulse signal is adaptively truncated to obtain the original pulse sequence data of the cable to be evaluated.

3. The cable service life assessment method based on high-frequency pulse sequence analysis as described in claim 1, characterized in that, The defect pulse sequence of the cable to be evaluated is obtained by performing multi-constraint clustering on the pulse point set in the original pulse sequence data based on the leading edge steepness and pulse width of the original pulse sequence data, including: Waveform edge detection is performed on the original pulse sequence data to obtain the leading edge steepness and pulse width of the cable to be evaluated; Based on the leading edge steepness and the pulse width, the pulse points in the original pulse sequence data are subjected to dual threshold morphology screening to obtain the candidate pulse sequence of the cable to be evaluated; The candidate pulse sequences are matched for morphological similarity to obtain the pulse waveform cluster of the cable to be evaluated; The physical causes of the pulse waveform clusters are determined to obtain the defect pulse sequence of the cable to be evaluated.

4. The cable service life assessment method based on high-frequency pulse sequence analysis as described in claim 1, characterized in that, Based on the fluctuation pattern of the time interval between adjacent pulses in the defect pulse sequence and the monotonicity trend of the pulse amplitude sequence, continuous pulses with the same evolution characteristics in the defect pulse sequence are grouped into pulse groups, and the pulse groups are projected onto the time axis to obtain the defect evolution time series map of the cable to be evaluated, including: Based on the pulse interval fluctuation spectrum of the defect pulse sequence, the defect pulse sequence is divided into evolution stages to obtain the evolution stage pulse sub-sequence of the cable to be evaluated. Monotonicity direction identification is performed on the amplitude sequence of the pulse sub-sequence in the evolution stage to obtain the sequence reversal point of the cable to be evaluated; Based on the sequence reversal point, the evolution stage pulse subsequence is divided into sub-stages to obtain the evolution stage pulse fragments of the cable to be evaluated. The pulse amplitude range of the pulse segments in the evolution sub-stage is located to obtain the pulse amplitude cluster of the cable to be evaluated; The pulse amplitude clusters are screened using pulse density parameters to obtain the pulse groups of the cable to be evaluated; The start and end times of the pulse group on the time axis are mapped to the time domain projection interval of the cable to be evaluated. The amplitude envelope of the pulse amplitude sequence of the pulse group is fitted to obtain the envelope curve of the cable to be evaluated; Using the time-domain projection interval as the horizontal axis span and the envelope curve as the vertical axis amplitude trajectory, a time series map of the defect evolution of the cable to be evaluated is constructed.

5. The cable service life assessment method based on high-frequency pulse sequence analysis as described in claim 1, characterized in that, The process involves multi-dimensional feature stripping of the defect evolution timeline and nonlinear coupling of the stripped degradation process acceleration with the critical breakdown approach to obtain the composite degradation factor of the cable under evaluation, including: The defect evolution time series map is deconstructed to obtain the time interval sequence and envelope curve sequence of the cable to be evaluated. The time interval sequence is stripped of the interval span parameter to obtain the interval span value of the cable to be evaluated; An envelope curve curvature evolution analysis is performed on the envelope curve sequence to obtain the slope change rate sequence of the cable to be evaluated; Based on the interval span value and the slope change rate sequence, the degradation process parameters of the defect evolution time series are stripped to obtain the degradation process acceleration of the cable to be evaluated. Based on the peak and valley amplitudes of the envelope curve sequence, parametric extraction is performed on the defect evolution time series map to obtain the critical breakdown approximation of the cable to be evaluated. The composite degradation factor of the cable to be evaluated is obtained by parametrically fusing and mapping the degradation process acceleration with the critical breakdown approximation.

6. The cable service life assessment method based on high-frequency pulse sequence analysis as described in claim 5, characterized in that, The step of performing envelope curve curvature evolution analysis on the envelope curve sequence to obtain the slope change rate sequence of the cable to be evaluated includes: The envelope curve sequence is resampled using curve arc length parameterization to obtain a sequence of equal arc length curve segments of the cable to be evaluated; The curvature evolution state of the equal arc length curve segment sequence is traced to obtain the curvature evolution trajectory curve of the cable to be evaluated; The curvature abrupt change points are detected on the curvature evolution trajectory curve to obtain the curvature abrupt change point set of the cable to be evaluated; Using the set of curvature abrupt change points as the dividing points, the sequence of equal arc length curve segments is divided into the deterioration sub-stage curve segments of the cable to be evaluated; The curvature change rate of the curve segment of the degradation sub-stage is calculated to obtain the slope change rate sequence of the cable to be evaluated.

7. The cable service life assessment method based on high-frequency pulse sequence analysis as described in claim 6, characterized in that, The formula for calculating the composite degradation factor is as follows: ； In the formula, The composite degradation factor, To accelerate the degradation process, The critical breakdown approximation is given. The frequency of curvature abrupt changes in the set of curvature abrupt change points. The preset reference time interval span, The interval span value, The peak amplitude of the envelope curve sequence is... The valley amplitude of the envelope curve sequence. The preset curvature change gain coefficient, This is a correction factor for the preset time interval span. The preset amplitude ratio correction factor, For natural functions, It is the natural logarithm function.

8. The cable service life assessment method based on high-frequency pulse sequence analysis as described in claim 1, characterized in that, Based on the composite degradation factor, trajectory similarity matching is performed on a preset standard degradation trajectory library, and time-series inversion is performed on the registered degradation trajectory curves to obtain the current aging stage identifier of the cable to be evaluated, including: The composite degradation factor is mapped to the feature parameter dimension space in the preset standard degradation trajectory library to obtain the normalized composite degradation factor of the cable to be evaluated. Based on the normalized composite degradation factor, Euclidean distance analysis is performed on the standard degradation trajectory curves in the standard degradation trajectory library to obtain the trajectory similarity distance value of the cable to be evaluated. The minimum distance among the trajectory similarity distance values ​​is selected for optimal retrieval to obtain the deterioration trajectory curve of the cable to be evaluated; Based on the normalized composite degradation factor, the degradation trajectory curve is projected and inverted to locate the time axis points of the cable to be evaluated. Based on the time axis points, the stage attribution of the degradation trajectory curve is identified to obtain the current aging stage identifier of the cable to be evaluated.

9. The cable service life assessment method based on high-frequency pulse sequence analysis as described in claim 1, characterized in that, The process of correcting the current aging stage identifier based on the historical operating data of the cable under evaluation to obtain the estimated remaining service life of the cable under evaluation includes: Extract load fluctuation characteristic parameters, cumulative ambient temperature characteristic parameters, and humidity change characteristic parameters from the historical operating data of the cable to be evaluated; The load fluctuation characteristic parameter, the ambient temperature cumulative characteristic parameter, and the humidity change characteristic parameter are registered with operating condition influence weights to obtain the comprehensive operating condition influence factor of the cable to be evaluated. Based on the preset aging stage-life benchmark mapping table, the current aging stage identifier is mapped to a stage benchmark value to obtain the benchmark life mapping trajectory point of the cable to be evaluated. The working condition correction amount is evaluated by comparing the comprehensive working condition influence factor with the baseline life mapping trajectory point to obtain the working condition disturbance offset of the cable to be evaluated. Based on the operating condition disturbance offset, the trajectory offset of the reference life mapping trajectory point is corrected to obtain the estimated remaining operating life of the cable to be evaluated.

10. A cable service life assessment system based on high-frequency pulse sequence analysis, characterized in that, The system for implementing the cable service life assessment method based on high-frequency pulse sequence analysis as described in claim 1 includes: The pulse filtering module is used to perform bandpass filtering on the high-frequency pulse signal of the cable to be evaluated to obtain the original pulse sequence data of the cable to be evaluated. The source tracing clustering module is used to perform multi-constraint clustering tracing on the pulse point set in the original pulse sequence data based on the leading edge steepness and pulse width of the original pulse sequence data, so as to obtain the defect pulse sequence of the cable to be evaluated. The time-series graph module is used to group continuous pulses with the same evolution characteristics in the defect pulse sequence into pulse groups based on the time interval fluctuation pattern between adjacent pulses in the defect pulse sequence and the monotonicity trend of the pulse amplitude sequence, and to project the pulse groups onto the time-series axis to obtain the defect evolution time-series graph of the cable to be evaluated. The degradation coupling module is used to perform multi-dimensional feature stripping on the defect evolution time series map and to nonlinearly couple the degradation process acceleration and critical breakdown approximation of the stripped feature to obtain the composite degradation factor of the cable to be evaluated. The trajectory matching module is used to perform trajectory similarity matching on a preset standard degradation trajectory library based on the composite degradation factor, and to perform time-series inversion on the registered degradation trajectory curves to obtain the current aging stage identifier of the cable to be evaluated. The lifespan prediction module is used to correct the current aging stage identifier based on the historical operating condition data of the cable to be evaluated, and obtain the estimated remaining operating life of the cable to be evaluated.

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