A cable insulation defect detection method based on reflection coefficient and impedance spectrum

Abstract

The invention discloses a cable insulation defect detection method based on reflection coefficient and impedance spectrum, which relates to the field of cable insulation defect detection, including: analyzing the reflection coefficient change of the cable within a window period, and evaluating the reflection coefficient impedance matching change trend; based on the frequency corresponding to the worst reflection coefficient, analyzing the return loss waveform fluctuation within the window period at the frequency; analyzing the impedance change characteristics under different frequency bands of the impedance spectrum, and evaluating the impedance abnormality level based on the abnormal expression of the divided low-frequency segment, medium-frequency segment and high-frequency segment in the impedance spectrum; comprehensively analyzing the reflection coefficient matching change trend, the return loss waveform fluctuation and the impedance abnormality level, continuously evaluating and warning the abnormal situation of the cable insulation defect, and ensuring the safety and reliability of the cable during operation.

Description

Technical Field

[0001] The invention relates to the field of cable insulation defect detection, and in particular to a cable insulation defect detection method based on reflection coefficient and impedance spectrum. Background Art

[0002] The cable insulation layer is an important component of the cable and plays a vital role in the cable. The main function of the insulation layer is to protect the conductor inside the cable and prevent current leakage and external interference. Defects in the cable insulation layer may cause problems such as partial discharge of the cable, reduced resistance, and increased electromagnetic interference.

[0003] The insulation capacity of the cable is closely related to its reflection coefficient and impedance. When there is a problem with the insulation capacity, the reflection coefficient and impedance spectrum of the cable will show obvious and typical abnormal characteristics in different signal frequency bands. Therefore, by analyzing the abnormal performance of the reflection coefficient and impedance of the cable in each frequency segment, a method for detecting and evaluating the insulation defects of the cable based on the reflection coefficient and impedance spectrum can be implemented, and timely early warning of the insulation defects of the cable can be given, thereby ensuring the normal operation and safe use of the cable. Summary of the invention

[0004] In order to solve the above technical problems, a cable insulation defect detection method based on reflection coefficient and impedance spectrum is provided. This technical solution solves the problems raised in the above background technology.

[0005] In order to achieve the above purpose, the technical solution adopted by the present invention is:

[0006] A cable insulation defect detection method based on reflection coefficient and impedance spectrum, comprising:

[0007] Analyze the change of cable reflection coefficient within the window period and evaluate the change trend of reflection coefficient impedance matching;

[0008] Based on the frequency corresponding to the worst reflection coefficient, analyze the return loss waveform fluctuation within the window period at this frequency;

[0009] Analyze the impedance variation characteristics at different frequency bands of the impedance spectrum and evaluate the impedance abnormality level;

[0010] Comprehensively analyze the reflection coefficient matching change trend, return loss waveform fluctuation and impedance abnormality level to evaluate and warn of abnormal cable insulation defects.

[0011] Preferably, analyzing the change of the reflection coefficient of the cable within the window period and evaluating the change trend of the impedance matching of the reflection coefficient specifically includes:

[0012] Set the length of the cable detection cycle, and mark the set number of cycles before the current detection cycle as the detection window cycle;

[0013] Analyze the change of reflection coefficient corresponding to the signal frequency in a single cycle in the window period, calculate the mean reflection coefficient corresponding to the signal frequency of the detection period, sort according to the cumulative value of the mean reflection coefficients of the same frequency in all detection periods, obtain the reflection coefficient with the largest cumulative value, and mark it as the worst reflection coefficient;

[0014] Get the frequency corresponding to the minimum mean value of the reflection coefficient in the first detection cycle in the window period, and mark the minimum frequency of frequency dependence;

[0015] Obtain the reflection coefficient of all detection cycles within the window period at the minimum frequency of frequency dependence. According to the change of reflection coefficient in adjacent periods, calculate the reflection coefficient impedance matching change trend evaluation value of the cable within the window period. The specific expression is:

[0016] ;

[0017] in It is the evaluation value of the reflection coefficient impedance matching change trend of the cable. is the reflection coefficient corresponding to the minimum frequency of the frequency dependence of the ith period, and n is the window size that sets the window period.

[0018] Preferably, the analyzing the return loss waveform fluctuation within the window period at the frequency corresponding to the worst reflection coefficient specifically includes:

[0019] Set a fixed time interval T0, and set adjacent monitoring points every T0 time within the detection period;

[0020] Get the frequency corresponding to the worst reflection coefficient, get the reflection coefficient time dimension change curve corresponding to the frequency in the window period, and collect the reflection coefficient according to the set monitoring point to establish the reflection coefficient array , A r f = [ a 1 ⋯ a j ⋯ a m ] ,in is the reflection coefficient value of the jth monitoring point;

[0021] Calculate reflection coefficient array The return loss value corresponding to the reflection coefficient establishes the return loss array , B e c = [ b 1 ⋯ b j ⋯ b m ] ,in is the return loss value of the jth monitoring point, The calculation method is: ;

[0022] According to the array The return loss value in is used to calculate the return loss waveform fluctuation index. The specific expression is:

[0023] ;

[0024] In the formula, It is the return loss waveform fluctuation index.

[0025] Preferably, analyzing the impedance variation characteristics of the impedance spectrum at different frequency bands and evaluating the impedance abnormality level specifically includes:

[0026] Obtain the latest impedance spectrum of the cable currently detected, mark it as real-time impedance spectrum, and divide the real-time impedance spectrum into low-frequency area, medium-frequency area and high-frequency area according to the set frequency distinction points;

[0027] The window with the smallest cumulative impedance change corresponding to each frequency in the impedance spectrum in the historical detection window period is selected as the most stable window period, and the mean value of all frequencies corresponding to each period in the most stable window period is used as the impedance value for the impedance spectrum standard control to establish a standard impedance spectrum;

[0028] The standard impedance spectrum is divided into low-frequency region, medium-frequency region and high-frequency region according to the same scale as the real-time impedance spectrum. The spectral similarity between the standard impedance spectrum and the real-time impedance spectrum in the low-frequency region, medium-frequency region and high-frequency region is calculated respectively. The calculation method is:

[0029] ;

[0030] In the formula, is the starting frequency of the kth frequency interval, is the size of the division area of ​​the kth frequency interval, are the impedance values ​​corresponding to the standard impedance spectrum and the real-time impedance spectrum corresponding to the i-th frequency in the k-th frequency interval;

[0031] Substitute the set low-frequency, medium-frequency, and high-frequency distinction points into the spectral similarity expression, calculate and obtain the spectral similarity of the low-frequency area, medium-frequency area, and high-frequency area, and mark them as ;

[0032] The impedance change characteristics of the real-time impedance spectrum in the low-frequency region, medium-frequency region and high-frequency region are evaluated for abnormality, and the impedance anomaly index is calculated by combining the spectral similarity between the real-time impedance spectrum and the standard impedance spectrum.

[0033] Preferably, the abnormal evaluation of the impedance change characteristics of the real-time impedance spectrum in the low-frequency region, the medium-frequency region and the high-frequency region is performed respectively, and the impedance abnormality index is calculated by combining the spectral similarity between the real-time impedance spectrum and the standard impedance spectrum, and specifically includes:

[0034] The impedance rise ratio of the real-time impedance spectrum in the low-frequency region and the spectral shape similarity of the standard impedance spectrum in the low-frequency region are analyzed, and the abnormal evaluation value of the impedance spectrum in the low-frequency region is calculated as follows:

[0035] Calculate the impedance deviation ratio of the real-time impedance spectrum in the low-frequency region relative to the standard impedance spectrum at the same frequency, accumulate the impedance deviation ratios corresponding to all frequencies in the low-frequency region, and calculate the overall mean, which is marked as the overall impedance deviation ratio ,when When it is a negative value, the default value is 0;

[0036] Get the spectral similarity of the low-frequency region , the impedance overall deviation ratio and The ratio of is used as the abnormal evaluation value of impedance spectrum in low frequency area;

[0037] The impedance change stability of the real-time impedance spectrum in the medium-frequency region is analyzed, and the spectrum shape similarity of the standard impedance spectrum in the medium-frequency region is analyzed. The abnormal evaluation value of the impedance spectrum in the medium-frequency region is calculated as follows:

[0038] Obtain the impedance value of the real-time impedance spectrum in the intermediate frequency region and calculate the variance of the impedance value change in the intermediate frequency region. express;

[0039] Get the spectral similarity in the mid-frequency region , the impedance value variance in the mid-frequency region and The inverse of the product is used as the abnormal evaluation value of the impedance spectrum in the mid-frequency region;

[0040] The impedance characteristic peak frequency of the real-time impedance spectrum in the high-frequency area is analyzed, and the similarity of the spectrum shape of the standard impedance spectrum in the high-frequency area is analyzed. The abnormal evaluation value of the impedance spectrum in the high-frequency area is calculated as follows:

[0041] Calculate the impedance mean of the real-time impedance spectrum in the high-frequency area, set the upper and lower limits of the impedance mean deviation ratio, mark the signal frequency corresponding to the impedance value that exceeds the set deviation ratio range as the impedance peak signal frequency, calculate the ratio of the number of impedance peak signal frequencies to the set high-frequency area size, mark it as the impedance peak occurrence frequency, and use express;

[0042] Get the spectral similarity of high-frequency area , the impedance peak frequency in the high-frequency region and The ratio of is used as the abnormal evaluation value of impedance spectrum in high-frequency area;

[0043] The real-time impedance spectrum anomaly evaluation values ​​in the low-frequency area, medium-frequency area, and high-frequency area are weighted and comprehensively calculated to calculate the impedance anomaly index. The specific expression is:

[0044] ;

[0045] In the formula, is the impedance anomaly index, are the weight coefficients of the real-time impedance spectrum anomaly assessment values ​​in the low-frequency area, medium-frequency area, and high-frequency area, respectively.

[0046] Preferably, the comprehensive analysis of the reflection coefficient matching change trend, return loss waveform fluctuation and impedance abnormality level to evaluate and warn of abnormal cable insulation defects specifically includes:

[0047] The cable's reflection coefficient impedance matching change trend evaluation value, return loss waveform fluctuation index, and impedance anomaly index are comprehensively calculated to calculate the cable's insulation defect anomaly index. The insulation defect anomaly index is calculated as follows:

[0048] ;

[0049] In the formula, is the insulation defect abnormality index of the cable, They are The weight scaling factor of ;

[0050] Set the insulation defect abnormality index threshold. When the insulation defect abnormality index calculation result is greater than or equal to the insulation defect abnormality index threshold, a cable insulation defect abnormality warning is issued. Conversely, when the insulation defect abnormality index calculation result is less than the insulation defect abnormality index threshold, the cable insulation performance is judged to be normal and no processing is performed.

[0051] Compared with the prior art, the present invention has the following beneficial effects:

[0052] Analyzing the changes in the reflection coefficient of the cable within the window period and evaluating the trend of the reflection coefficient impedance matching will help understand the overall trend of the reflection coefficient impedance matching during the detection process. Based on the frequency corresponding to the worst reflection coefficient, analyzing the return loss waveform fluctuation within the window period at this frequency will help evaluate the stability of the cable impedance matching. Analyzing the impedance change characteristics in different frequency bands of the impedance spectrum will help increase the pertinence of impedance anomaly analysis by analyzing the impedance characteristics in different frequency bands. Evaluating the impedance anomaly level, comprehensively analyzing the reflection coefficient matching trend, return loss waveform fluctuation, and impedance anomaly level, and evaluating and warning of abnormal cable insulation defects.

[0053] Based on the above process, non-contact continuous detection, evaluation and timely warning of abnormal insulation defects during cable operation are achieved, ensuring the normal operation and safe use of the cable. BRIEF DESCRIPTION OF THE DRAWINGS

[0054] Figure 1 A flow chart of a cable insulation defect detection method based on reflection coefficient and impedance spectrum of the present invention;

[0055] Figure 2 A flow chart of the reflection coefficient change of the cable within the analysis window period of the present invention and the evaluation of the reflection coefficient impedance matching change trend;

[0056] Figure 3 This is a flow chart of analyzing the return loss waveform fluctuation within a window period at a frequency corresponding to the worst reflection coefficient according to the present invention;

[0057] Figure 4 This is a flow chart for analyzing impedance variation characteristics at different frequency bands of the impedance spectrum and evaluating the abnormal impedance level of the present invention;

[0058] Figure 5 The present invention is to evaluate the impedance change characteristics of the real-time impedance spectrum in the low-frequency region, the medium-frequency region and the high-frequency region respectively, and calculate the impedance anomaly index flow chart by combining the spectrum similarity between the real-time impedance spectrum and the standard impedance spectrum;

[0059] Figure 6 The present invention comprehensively analyzes the reflection coefficient matching change trend, return loss waveform fluctuation and impedance abnormality level, and evaluates and warns the abnormal situation of cable insulation defects. DETAILED DESCRIPTION

[0060] The following description is used to disclose the present invention so that those skilled in the art can implement the present invention. The preferred embodiments described below are only examples, and those skilled in the art may think of other obvious variations.

[0061] Reference Figure 1 As shown, a cable insulation defect detection method based on reflection coefficient and impedance spectrum includes:

[0062] Analyze the change of cable reflection coefficient within the window period and evaluate the change trend of reflection coefficient impedance matching;

[0063] Based on the frequency corresponding to the worst reflection coefficient, analyze the return loss waveform fluctuation within the window period at this frequency;

[0064] Analyze the impedance variation characteristics at different frequency bands of the impedance spectrum and evaluate the impedance abnormality level;

[0065] Comprehensively analyze the reflection coefficient matching change trend, return loss waveform fluctuation and impedance abnormality level to evaluate and warn of abnormal cable insulation defects.

[0066] Reference Figure 2 As shown in the figure, the reflection coefficient change of the cable within the window period is analyzed, and the reflection coefficient impedance matching change trend is evaluated, including:

[0067] Set the length of the cable detection cycle, and mark the set number of cycles before the current detection cycle as the detection window cycle;

[0068] Analyze the change of reflection coefficient corresponding to the signal frequency in a single cycle in the window period, calculate the mean reflection coefficient corresponding to the signal frequency of the detection period, sort according to the cumulative value of the mean reflection coefficients of the same frequency in all detection periods, obtain the reflection coefficient with the largest cumulative value, and mark it as the worst reflection coefficient;

[0069] Get the frequency corresponding to the minimum mean value of the reflection coefficient in the first detection cycle in the window period, and mark the minimum frequency of frequency dependence;

[0070] As the frequency changes, the load impedance of the cable may also change, resulting in frequency dependence of the reflection coefficient at different frequencies. Selecting the frequency with the lowest frequency dependence for reflection coefficient trend evaluation helps reduce the impedance matching judgment error caused by the normal impedance change of the cable itself.

[0071] Obtain the reflection coefficient of all detection cycles within the window period at the minimum frequency of frequency dependence. According to the change of reflection coefficient in adjacent periods, calculate the reflection coefficient impedance matching change trend evaluation value of the cable within the window period. The specific expression is:

[0072] ;

[0073] in It is the evaluation value of the reflection coefficient impedance matching change trend of the cable. is the reflection coefficient corresponding to the minimum frequency of the frequency dependence of the ith period, and n is the window size that sets the window period.

[0074] When the cable is in good insulation and in normal operation, the reflection coefficient is small and close to 0, which means that most of the cable signals are transmitted correctly and there are few reflected waves. When there are defects in the insulation layer of the cable, its reflection coefficient usually increases. Considering that partial discharge caused by insulation defects may cause fluctuations in the reflection coefficient, evaluating the overall change trend of the reflection coefficient is an intuitive way to judge the defects of the insulation layer. A positive value indicates that the overall reflection coefficient increases, which indicates that the risk of insulation layer defects is greater. When it is a negative value or 0, it indicates that the risk of defects in the insulation layer is relatively small.

[0075] Reference Figure 3 As shown in the figure, based on the frequency corresponding to the worst reflection coefficient, the analysis of the return loss waveform fluctuation within the window period at this frequency specifically includes:

[0076] Set a fixed time interval T0, and set adjacent monitoring points every T0 time within the detection period;

[0077] Get the frequency corresponding to the worst reflection coefficient, get the reflection coefficient time dimension change curve corresponding to the frequency in the window period, and collect the reflection coefficient according to the set monitoring point to establish the reflection coefficient array , A r f = [ a 1 ⋯ a j ⋯ a m ] ,in is the reflection coefficient value of the jth monitoring point;

[0078] Calculate reflection coefficient array The return loss value corresponding to the reflection coefficient establishes the return loss array , B e c = [ b 1 ⋯ b j ⋯ b m ] ,in is the return loss value of the jth monitoring point, The calculation method is: ;

[0079] According to the array The return loss value in is used to calculate the return loss waveform fluctuation index. The specific expression is:

[0080] ;

[0081] In the formula, It is the return loss waveform fluctuation index.

[0082] By obtaining the frequency corresponding to the worst reflection coefficient, it is shown that the risk of insulation layer defects is the greatest at this frequency. Taking into account the reflection coefficient fluctuation caused by insulation layer defects, the possibility of insulation layer defects at this time can be determined by evaluating the return loss waveform fluctuation at this frequency. The principles of using reflection coefficient fluctuation and return loss fluctuation for analysis and evaluation are consistent here. Since the value range of return loss is between 0db and positive infinity, it has better calculation discrimination than the reflection coefficient value range between 0 and 1, so the return loss fluctuation is selected for evaluation.

[0083] Reference Figure 4 As shown in the figure, the impedance change characteristics under different frequency bands of the impedance spectrum are analyzed, and the impedance abnormality level is evaluated, including:

[0084] Obtain the latest impedance spectrum of the cable currently detected, mark it as real-time impedance spectrum, and divide the real-time impedance spectrum into low-frequency area, medium-frequency area and high-frequency area according to the set frequency distinction points;

[0085] When the cable is healthy, its impedance has a high degree of constancy within each frequency. By selecting an impedance spectrum with stable impedance as the standard impedance spectrum, it can be used as a control for abnormal impedance spectrum mutations detected in real time.

[0086] The window with the smallest cumulative impedance change corresponding to each frequency in the impedance spectrum in the historical detection window period is selected as the most stable window period, and the mean value of all frequencies corresponding to each period in the most stable window period is used as the impedance value for the impedance spectrum standard control to establish a standard impedance spectrum;

[0087] The standard impedance spectrum is divided into low-frequency region, medium-frequency region and high-frequency region according to the same scale as the real-time impedance spectrum. The spectral similarity between the standard impedance spectrum and the real-time impedance spectrum in the low-frequency region, medium-frequency region and high-frequency region is calculated respectively. The calculation method is:

[0088] ;

[0089] In the formula, is the starting frequency of the kth frequency interval, is the size of the division area of ​​the kth frequency interval, are the impedance values ​​corresponding to the standard impedance spectrum and the real-time impedance spectrum corresponding to the i-th frequency in the k-th frequency interval;

[0090] Substitute the set low-frequency, medium-frequency, and high-frequency distinction points into the spectral similarity expression, calculate and obtain the spectral similarity of the low-frequency area, medium-frequency area, and high-frequency area, and mark them as ;

[0091] The impedance change characteristics of the real-time impedance spectrum in the low-frequency region, medium-frequency region and high-frequency region are evaluated for abnormality, and the impedance anomaly index is calculated by combining the spectral similarity between the real-time impedance spectrum and the standard impedance spectrum.

[0092] When defects occur in the insulation layer, the impedance spectrum will have different characteristics in the low-frequency, medium-frequency and high-frequency regions. Due to the deterioration of the capacitance of the insulation layer, the low-frequency region typically shows an increase in impedance. The low-frequency impedance anomaly can be evaluated based on the real-time impedance increase ratio in the low-frequency region and the similarity between the low-frequency impedance spectrum and the standard impedance spectrum. In the medium-frequency region, the insulation layer's impedance is abnormally expressed due to changes in capacitance, inductance and parasitic effects caused by defects, which is shown as obvious irregular fluctuations in impedance. The medium-frequency impedance anomaly is evaluated based on the real-time impedance fluctuations in the medium-frequency region and the similarity between the medium-frequency impedance spectrum and the standard impedance spectrum. In the high-frequency region, due to the electrical noise and inductance effect changes caused by the failure of the insulation material, it will produce an abnormal expression of impedance reduction and frequent spikes in the impedance spectrum. Therefore, the high-frequency impedance anomaly can be evaluated based on the real-time impedance peak generation frequency in the high-frequency region and the similarity between the high-frequency impedance spectrum and the standard impedance spectrum.

[0093] By performing abnormality evaluation on the impedance spectra in the low, medium and high frequency regions respectively, the comprehensiveness and accuracy of impedance abnormality evaluation can be improved.

[0094] Reference Figure 5 As shown, the impedance change characteristics of the real-time impedance spectrum in the low-frequency area, the medium-frequency area, and the high-frequency area are evaluated for abnormality, and the impedance abnormality index is calculated by combining the spectral similarity between the real-time impedance spectrum and the standard impedance spectrum. Specifically, it includes:

[0095] The impedance rise ratio of the real-time impedance spectrum in the low-frequency region and the spectral shape similarity of the standard impedance spectrum in the low-frequency region are analyzed, and the abnormal evaluation value of the impedance spectrum in the low-frequency region is calculated as follows:

[0096] Calculate the impedance deviation ratio of the real-time impedance spectrum in the low-frequency region relative to the standard impedance spectrum at the same frequency, accumulate the impedance deviation ratios corresponding to all frequencies in the low-frequency region, and calculate the overall mean, which is marked as the overall impedance deviation ratio ,when When it is a negative value, the default value is 0;

[0097] Get the spectral similarity of the low-frequency region , the impedance overall deviation ratio and The ratio of is used as the abnormal evaluation value of impedance spectrum in low frequency area;

[0098] The impedance change stability of the real-time impedance spectrum in the medium-frequency region is analyzed, and the spectrum shape similarity of the standard impedance spectrum in the medium-frequency region is analyzed. The abnormal evaluation value of the impedance spectrum in the medium-frequency region is calculated as follows:

[0099] Obtain the impedance value of the real-time impedance spectrum in the intermediate frequency region and calculate the variance of the impedance value change in the intermediate frequency region. express;

[0100] Get the spectral similarity in the mid-frequency region , the impedance value variance in the mid-frequency region and The inverse of the product is used as the abnormal evaluation value of the impedance spectrum in the mid-frequency region;

[0101] The impedance characteristic peak frequency of the real-time impedance spectrum in the high-frequency area is analyzed, and the similarity of the spectrum shape of the standard impedance spectrum in the high-frequency area is analyzed. The abnormal evaluation value of the impedance spectrum in the high-frequency area is calculated as follows:

[0102] Calculate the impedance mean of the real-time impedance spectrum in the high-frequency area, set the upper and lower limits of the impedance mean deviation ratio, mark the signal frequency corresponding to the impedance value that exceeds the set deviation ratio range as the impedance peak signal frequency, calculate the ratio of the number of impedance peak signal frequencies to the set high-frequency area size, mark it as the impedance peak occurrence frequency, and use express;

[0103] Get the spectral similarity of high-frequency area , the impedance peak frequency in the high-frequency region and The ratio of is used as the abnormal evaluation value of impedance spectrum in high-frequency area;

[0104] The real-time impedance spectrum anomaly evaluation values ​​in the low-frequency area, medium-frequency area, and high-frequency area are weighted and comprehensively calculated to calculate the impedance anomaly index. The specific expression is:

[0105] ;

[0106] In the formula, is the impedance anomaly index, are the weight coefficients of the real-time impedance spectrum anomaly assessment values ​​in the low-frequency area, medium-frequency area, and high-frequency area, respectively.

[0107] Reference Figure 6 As shown in the figure, the reflection coefficient matching trend, return loss waveform fluctuation and impedance abnormality level are comprehensively analyzed to evaluate and warn of abnormal cable insulation defects. Specifically, the following are included:

[0108] The cable's reflection coefficient impedance matching change trend evaluation value, return loss waveform fluctuation index, and impedance anomaly index are comprehensively calculated to calculate the cable's insulation defect anomaly index. The insulation defect anomaly index is calculated as follows:

[0109] ;

[0110] In the formula, is the insulation defect abnormality index of the cable, They are The weight scaling factor of ;

[0111] Set the insulation defect abnormality index threshold. When the insulation defect abnormality index calculation result is greater than or equal to the insulation defect abnormality index threshold, a cable insulation defect abnormality warning is issued. Conversely, when the insulation defect abnormality index calculation result is less than the insulation defect abnormality index threshold, the cable insulation performance is judged to be normal and no processing is performed.

[0112] The insulation defect abnormality index threshold is set by professionals in this field based on the specific calculation results and change scale of the insulation defect abnormality index, combined with the actual operation of the cable and safety specifications and standards, and will not be repeated here.

[0113] The cable insulation defect abnormality detection can be continuously evaluated and tested according to the set detection cycle, so as to realize the timely warning of cable insulation abnormality and ensure the safety and stability of cable operation.

[0114] Furthermore, the present solution also proposes a storage medium for a cable insulation defect detection method based on reflection coefficient and impedance spectrum, on which a computer-readable program is stored. When the computer-readable program is called, the above-mentioned cable insulation defect detection method based on reflection coefficient and impedance spectrum is executed.

[0115] It is understandable that the storage medium may be a magnetic medium, such as a floppy disk, a hard disk, or a magnetic tape; an optical medium, such as a DVD; or a semiconductor medium, such as a solid state drive (SSD).

[0116] The above shows and describes the basic principles, main features and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited to the above embodiments. The above embodiments and descriptions only describe the principles of the present invention. The present invention may be subject to various changes and improvements without departing from the spirit and scope of the present invention. These changes and improvements fall within the scope of the present invention. The scope of protection claimed by the present invention is defined by the attached claims and their equivalents.

Claims

1. A cable insulation defect detection method based on reflection coefficient and impedance spectrum, characterized in that: include: Analyze the change of cable reflection coefficient within the window period and evaluate the change trend of reflection coefficient impedance matching; Based on the frequency corresponding to the worst reflection coefficient, analyze the return loss waveform fluctuation within the window period at this frequency; Analyze the impedance variation characteristics at different frequency bands of the impedance spectrum and evaluate the impedance abnormality level; Comprehensively analyze the reflection coefficient matching trend, return loss waveform fluctuation and impedance abnormality level, and evaluate and warn of abnormal cable insulation defects; in, The analysis of the change in reflection coefficient of the cable within the window period and the evaluation of the change trend of impedance matching of the reflection coefficient specifically include: Set the length of the cable detection cycle, and mark the set number of cycles before the current detection cycle as the detection window cycle; Analyze the change of reflection coefficient corresponding to the signal frequency in a single cycle in the window period, calculate the mean reflection coefficient corresponding to the signal frequency of the detection period, sort according to the cumulative value of the mean reflection coefficients of the same frequency in all detection periods, obtain the reflection coefficient with the largest cumulative value, and mark it as the worst reflection coefficient; Get the frequency corresponding to the minimum mean value of the reflection coefficient in the first detection cycle in the window period, and mark the minimum frequency of frequency dependence; Obtain the reflection coefficient of all detection cycles within the window period at the minimum frequency of frequency dependence. According to the change of reflection coefficient in adjacent periods, calculate the reflection coefficient impedance matching change trend evaluation value of the cable within the window period. The specific expression is: ； in, It is the evaluation value of the reflection coefficient impedance matching change trend of the cable. is the reflection coefficient corresponding to the frequency-dependent minimum frequency of the ith period, and n is the window size that sets the window period; in, The analysis of the return loss waveform fluctuation within the window period at the frequency corresponding to the worst reflection coefficient specifically includes: Set a fixed time interval T0, and set adjacent monitoring points every T0 time within the detection period; Get the frequency corresponding to the worst reflection coefficient, get the reflection coefficient time dimension change curve corresponding to the frequency in the window period, and collect the reflection coefficient according to the set monitoring point to establish the reflection coefficient array , ,in is the reflection coefficient value of the jth monitoring point; Calculate reflection coefficient array The return loss value corresponding to the reflection coefficient establishes the return loss array , ,in is the return loss value of the jth monitoring point, The calculation method is: ; According to the array The return loss value in is used to calculate the return loss waveform fluctuation index. The specific expression is: ； In the formula, is the return loss waveform fluctuation index; in, The analysis of impedance change characteristics at different frequency bands of the impedance spectrum and the evaluation of impedance abnormality levels specifically include: Obtain the latest impedance spectrum of the cable currently detected, mark it as real-time impedance spectrum, and divide the real-time impedance spectrum into low-frequency area, medium-frequency area and high-frequency area according to the set frequency distinction points; The window with the smallest cumulative impedance change corresponding to each frequency in the impedance spectrum in the historical detection window period is selected as the most stable window period, and the mean value of all frequencies corresponding to each period in the most stable window period is used as the impedance value for the impedance spectrum standard control to establish a standard impedance spectrum; The standard impedance spectrum is divided into low-frequency region, medium-frequency region and high-frequency region according to the same scale as the real-time impedance spectrum. The spectral similarity between the standard impedance spectrum and the real-time impedance spectrum in the low-frequency region, medium-frequency region and high-frequency region is calculated respectively. The calculation method is: ； In the formula, is the starting frequency of the kth frequency interval, is the size of the division area of ​​the kth frequency interval, are the impedance values ​​corresponding to the standard impedance spectrum and the real-time impedance spectrum corresponding to the i-th frequency in the k-th frequency interval; Substitute the set low-frequency, medium-frequency, and high-frequency distinction points into the spectral similarity expression, calculate and obtain the spectral similarity of the low-frequency area, medium-frequency area, and high-frequency area, and mark them as ; The impedance change characteristics of the real-time impedance spectrum in the low-frequency area, the medium-frequency area, and the high-frequency area are evaluated for abnormality, and the impedance abnormality index is calculated by combining the spectral similarity between the real-time impedance spectrum and the standard impedance spectrum; in, The abnormal evaluation of the impedance change characteristics of the real-time impedance spectrum in the low-frequency region, the medium-frequency region and the high-frequency region is performed respectively, and the impedance abnormality index is calculated by combining the spectrum similarity between the real-time impedance spectrum and the standard impedance spectrum. Specifically, the calculation includes: The impedance rise ratio of the real-time impedance spectrum in the low-frequency region and the spectral shape similarity of the standard impedance spectrum in the low-frequency region are analyzed, and the abnormal evaluation value of the impedance spectrum in the low-frequency region is calculated as follows: Calculate the impedance deviation ratio of the real-time impedance spectrum in the low-frequency region relative to the standard impedance spectrum at the same frequency, accumulate the impedance deviation ratios corresponding to all frequencies in the low-frequency region, and calculate the overall mean, which is marked as the overall impedance deviation ratio ,when When it is a negative value, the default value is 0; Get the spectral similarity of the low-frequency region , the impedance overall deviation ratio and The ratio of is used as the abnormal evaluation value of impedance spectrum in low frequency area; The impedance change stability of the real-time impedance spectrum in the medium-frequency region is analyzed, and the spectrum shape similarity of the standard impedance spectrum in the medium-frequency region is analyzed. The abnormal evaluation value of the impedance spectrum in the medium-frequency region is calculated as follows: Obtain the impedance value of the real-time impedance spectrum in the intermediate frequency region and calculate the variance of the impedance value change in the intermediate frequency region. express; Get the spectral similarity in the mid-frequency region , the impedance value variance in the mid-frequency region and The inverse of the product is used as the abnormal evaluation value of the impedance spectrum in the mid-frequency region; The impedance characteristic peak frequency of the real-time impedance spectrum in the high-frequency area is analyzed, and the similarity of the spectrum shape of the standard impedance spectrum in the high-frequency area is analyzed. The abnormal evaluation value of the impedance spectrum in the high-frequency area is calculated as follows: Calculate the impedance mean of the real-time impedance spectrum in the high-frequency area, set the upper and lower limits of the impedance mean deviation ratio, mark the signal frequency corresponding to the impedance value that exceeds the set deviation ratio range as the impedance peak signal frequency, calculate the ratio of the number of impedance peak signal frequencies to the set high-frequency area size, mark it as the impedance peak occurrence frequency, and use express; Get the spectral similarity of high-frequency area , the impedance peak frequency in the high-frequency region and The ratio of is used as the abnormal evaluation value of impedance spectrum in high-frequency area; The real-time impedance spectrum anomaly evaluation values ​​in the low-frequency area, medium-frequency area, and high-frequency area are weighted and comprehensively calculated to calculate the impedance anomaly index. The specific expression is: ； In the formula, is the impedance anomaly index, are the weight coefficients of the real-time impedance spectrum anomaly assessment values ​​in the low-frequency region, the medium-frequency region, and the high-frequency region, respectively; in, The comprehensive analysis of the reflection coefficient matching change trend, return loss waveform fluctuation and impedance abnormality level, and the evaluation and early warning of abnormal cable insulation defects specifically include: The cable's reflection coefficient impedance matching change trend evaluation value, return loss waveform fluctuation index, and impedance anomaly index are comprehensively calculated to calculate the cable's insulation defect anomaly index. The insulation defect anomaly index is calculated as follows: ； In the formula, is the insulation defect abnormality index of the cable, They are The weight scaling factor of ; Set the insulation defect abnormality index threshold. When the insulation defect abnormality index calculation result is greater than or equal to the insulation defect abnormality index threshold, a cable insulation defect abnormality warning is issued. Conversely, when the insulation defect abnormality index calculation result is less than the insulation defect abnormality index threshold, the cable insulation performance is judged to be normal and no processing is performed.

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