Cable insulation fault detection method

Abstract

The invention relates to the technical field of electrical measurement and power system monitoring, in particular to a cable insulation fault detection method. The method comprises the following steps: measuring an electric field signal and constructing an electric field distribution model in a cable to obtain a signal mapping result of a cable insulation state; the signal mapping result of the cable insulation state is mapped to a frequency domain, smoothing processing is carried out, multi-scale analysis is carried out on the signal after smoothing processing, fault features of the cable are extracted, the insulation state of the cable is quantified, the probability that the cable has an insulation fault is calculated, and a basis is provided for fault early warning and maintenance. The problems that most of traditional insulation fault detection methods depend on single electrical or spectral characteristic detection, so that detection information is incomplete; the stability is poor, and misjudgment or missed judgment is easily caused; in some methods, power failure or direct contact with a cable is needed for measurement, and continuous operation of the cable is affected. And complex electric field distribution and dynamic change thereof in the cable are difficult to accurately describe, and the fault development trend is difficult to predict.

Description

Technical Field

[0001] The present invention relates to the technical field of electrical measurement and power system monitoring, and particularly to a method for detecting cable insulation faults. Background Art

[0002] In modern power systems, industrial control, and communication networks, as the core transmission medium, the safe and stable operation of cables is directly related to the reliability and economy of the systems. With the increase in the service time of cables, the insulation layer will gradually deteriorate due to long-term exposure to electrical stress, environmental factors, mechanical damage, etc., which may lead to cable breakdown, short circuit, or other forms of failures, and then cause equipment damage, power supply interruption, and even serious safety accidents. Therefore, how to efficiently and accurately evaluate the insulation state of cables and timely predict potential faults has become a highly concerned issue in the power system and related industries.

[0003] During the entire life cycle of a cable, its insulation state is affected by multiple factors, including electrical aging, environmental humidity, temperature changes, electromagnetic interference, and mechanical stress, etc. These factors may cause phenomena such as increased dielectric loss, partial discharge, changes in dielectric constant, and electric field distortion inside the cable, resulting in a decline in the cable's insulation performance and affecting its normal operation. Therefore, accurately analyzing the electric field distribution inside the cable, extracting the frequency response characteristics of the cable, constructing topological electric field features, and combining multi-dimensional health index evaluation methods to conduct real-time monitoring and fault prediction of the cable insulation state have important theoretical and practical significance.

[0004] However, the traditional insulation fault detection methods have the following technical problems: Most rely on single electrical or spectral characteristic detection, unable to comprehensively reflect the comprehensive state of cable insulation in different frequencies, spatial positions, and time dimensions, resulting in incomplete detection information; Poor stability under complex working conditions, prone to false judgment or missed judgment; Some methods require power outage or direct contact with the cable for measurement, without the ability of online real-time monitoring, affecting the continuous operation of the cable; Most are based on simple mathematical models, difficult to accurately describe the complex electric field distribution inside the cable and its dynamic changes, unable to accurately locate the local insulation deterioration area, and also difficult to predict the future fault development trend. Summary of the Invention

[0005] The present invention provides a method for detecting cable insulation faults, aiming to solve the problems that most traditional insulation fault detection methods rely on single electrical or spectral characteristic detection, unable to comprehensively reflect the comprehensive state of cable insulation in different frequencies, spatial positions and time dimensions, resulting in incomplete detection information; poor stability under complex working conditions, prone to misjudgment or missed judgment; some methods require power outage or direct contact with the cable for measurement, without the ability of on-line real-time monitoring, affecting the continuous operation of the cable; and most are based on simple mathematical models, difficult to accurately describe the complex electric field distribution inside the cable and its dynamic changes, unable to accurately locate the local insulation deterioration area, and also difficult to predict the future fault development trend.

[0006] A method for detecting cable insulation faults of the present invention specifically includes the following technical solutions: A method for detecting cable insulation faults includes the following steps: S1. Measure the electric field signal, construct the electric field distribution model inside the cable, and obtain the signal mapping result of the cable insulation state; convert the signal mapping result of the cable insulation state from the time domain signal to the frequency domain signal, and perform smoothing processing to obtain the smoothed signal. S2. Perform multi-scale analysis on the smoothed signal, extract the fault characteristics of the cable, and quantify the insulation state of the cable to obtain the cable health index; based on the cable health index, calculate the probability of the cable occurring insulation faults, providing a basis for fault early warning and maintenance.

[0007] Preferably, the S1 specifically includes: Perform data interpolation, Fourier transform and error correction on the electric field signals at different positions and times inside the cable to obtain the electric field distribution data, and fit the electric field distribution model inside the cable by the least square method to obtain the electric field distribution inside the cable.

[0008] Preferably, the S1 specifically includes: Based on the influence of time, space and frequency on the electric field distribution, introduce a non-linear modulation factor, construct the kernel function of signal propagation, and combine with the electric field distribution inside the cable to obtain the signal mapping result of the cable insulation state.

[0009] Preferably, the S1 specifically includes: Through Fourier transform, map the signal mapping result of the cable insulation state to the frequency domain to obtain the Fourier transform result; perform Laplace transform on the Fourier transform result to obtain the smoothed signal.

[0010] Preferably, the S2 specifically includes: Discretize the smoothed signal into spatial, temporal, and frequency dimensions to generate a third-order signal matrix; based on the third-order signal matrix, introduce a dynamic time window to construct a fourth-order tensor; perform tensor decomposition on the fourth-order tensor to extract the fault characteristics of the cable.

[0011] Preferably, the S2 specifically includes: Based on the fault characteristics of the cable, introduce a normalization factor and a topological integral normalization factor to obtain a normalized electric field topological mapping.

[0012] Preferably, the S2 specifically includes: Based on the normalized electric field topological mapping, quantify the insulation state of the cable by integrating signal characteristics, topological electric field parameters, and frequency response to obtain a cable health index; the comprehensive signal characteristics are the distribution of the electric field signal along different positions and times of the cable and its attenuation characteristics over time; the topological electric field parameters refer to the topological changes of the electric field inside the cable.

[0013] Preferably, the S2 specifically includes: Integrate the cable health index and introduce exponential decay to calculate the probability of the cable having an insulation fault; when the insulation condition in the cable area deteriorates, the cable health index in the corresponding area increases, and the probability value of the cable having an insulation fault rises, triggering an alarm.

[0014] The beneficial effects of the technical solution of the present invention are: 1. The present invention not only performs time-domain analysis on the collected electric field signals, but also maps the electric field signals to the frequency domain through Fourier transform to eliminate unnecessary time-domain interference, ensuring that the insulation response characteristics at different frequencies can be extracted; further, through multi-scale analysis technology, the signals are dynamically adjusted to ensure that the change trends of the signals within different time windows can be accurately modeled, thus comprehensively reflecting the evolution process of the cable insulation state.

[0015] 2. Since the cable operates in a complex environment and is easily affected by external electromagnetic interference and background noise, the present invention uses Laplace transform for smoothing processing, effectively reducing the influence of high-frequency noise and making the calculation results more stable.

[0016] 3. The present invention constructs an electric field topological mapping to extract the topological structure changes of the cable insulation state; by integrating signal characteristics, topological electric field parameters, and frequency response data, a cable health index model is constructed, enabling the cable health state to be quantified, and predicting possible future faults of the cable through the change trend of the cable health index; the calculation method of the cable health index takes into account the non-linear attenuation, spatial distribution, and dynamic characteristics of the electric field signal, making the evaluation result of the cable insulation state more valuable for practical engineering applications.

[0017] 4. The insulation fault probability calculation method of the present invention is based on the integral calculation of the cable health index and adopts an exponential decay form to ensure the numerical stability of the calculation result. At the same time, it can accurately reflect the health status of the entire cable length. Once the insulation status in a certain area deteriorates severely, the insulation fault probability value will increase rapidly, so as to issue a warning signal in time, enabling maintenance personnel to carry out maintenance in advance and avoiding cable damage or power interruption caused by sudden insulation faults. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] Figure 1 It is a flowchart of a method for detecting cable insulation faults according to the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0019] In order to further elaborate on the technical means and effects adopted by the present invention to achieve the predetermined invention purpose, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0020] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by those of ordinary skill in the technical field to which the present invention belongs.

[0021] The following specifically describes the specific solution of a method for detecting cable insulation faults provided by the present invention in conjunction with the drawings.

[0022] Refer to the attached Figure 1 , which shows a flowchart of a method for detecting cable insulation faults provided by an embodiment of the present invention. The method includes the following steps: S1. Measure the electric field signal, construct an electric field distribution model inside the cable, and obtain the signal mapping result of the cable insulation status; convert the signal mapping result of the cable insulation status from the time domain signal to the frequency domain signal and perform smoothing processing to obtain the smoothed signal; In order to obtain the initial state of the cable insulation medium, it is necessary to measure the electrical variables inside the cable to construct a complete signal mapping model. Specifically, first, a specific pulse current signal is applied at the input end of the cable, and the electric field signals are collected at multiple spatial positions; the electric field signal is the external manifestation of the action of electrical variables (potential, current density, polarization charge, etc.) in the dielectric environment. The measurement process depends on the electric field sensor array, and its arrangement method needs to ensure that different insulation areas of the cable can be covered, so as to capture the electric field distribution along the length of the cable.

[0023] Since the insulation layer of the cable exhibits different dielectric properties at different frequencies, the collected electric field signal not only contains the instantaneous electric field response of the insulation layer, but also implicitly includes the attenuation characteristics of the insulation layer at different frequencies. To ensure the stability and accuracy of the electric field signal acquisition, at each sampling point, the electric field signal is measured multiple times and the average value is calculated to reduce the influence of external noise and random interference.

[0024] Since there may be local deterioration areas in the insulation layer of the cable, which can cause attenuation or distortion of the electric field during propagation. To accurately describe the electric field response inside the cable, a mathematical model is constructed to characterize the propagation characteristics of the electric field in the insulation layer. The electric field distribution inside the cable is not only affected by the applied electrical signal, but also modulated by factors such as the inhomogeneity of the cable insulation material itself, local charge accumulation, and material aging. The spatial propagation of the electric field involves the transmission and reflection of the electric field at different positions, and the time variation is mainly determined by the polarization effect and charge accumulation effect of the cable medium. In addition, the frequency components of the signal also affect the propagation characteristics of the electric field, especially at high frequencies, where the loss of the insulation material increases. Therefore, through capacitance coupling measurement, high-frequency pulse injection, partial discharge electromagnetic wave detection, and external magnetic field measurement, the electric field strength at different positions and times inside the cable is obtained; through data interpolation, Fourier transform, and error correction, the electric field distribution data is obtained, and a continuous surface model, that is, the electric field distribution model inside the cable, is fitted by the least squares method to describe the electric field distribution inside the cable. Considering the influence of time, space, and frequency on the electric field distribution, the signal mapping result of the cable insulation state is obtained; the data interpolation, Fourier transform, error correction, and least squares method are all well-known technical means to those skilled in the art and will not be elaborated here; the specific formula for the signal mapping result of the cable insulation state is as follows: , , where, represents the signal mapping result of the cable insulation state and is constructed based on the existing convolution integral theory; is the kernel function of signal propagation, and its role is to characterize the diffusion and transmission mode of the electric field inside the medium; is the position coordinate along the length direction of the cable; is the time variable; is the angular frequency, representing the frequency characteristics of the electric field signal; is the total length of the cable; is the total time window of measurement; is the electric field distribution inside the cable, used to describe the electric field strength at different positions and times inside the cable; and are the integral variables of position and time respectively; It represents the frequency response of the electric field signal over time, which is a standard wave propagation theory and a well-known technical means to those skilled in the art, and will not be elaborated here. is the attenuation factor of the medium, which is experimentally determined from the dielectric constant and conductivity of the insulating material, and its value range is ; represents the inhomogeneity of the insulating layer, which is obtained by measuring the tangent value of the dielectric loss angle in different regions, and its value range is ; is the medium charge storage factor, which is used to describe the charge storage effect of the medium and is determined by the dielectric polarization test, and its value range is ; is the time rate-of-change factor, which is used to describe the rate of change of the electric field signal over time and is obtained by measuring the rate of change of the electric field signal over time, and its value range is ; Since the inhomogeneity of the medium (such as local losses in the insulating layer) will cause non-linear attenuation characteristics of the electric field propagation, a non-linear modulation factor is introduced, where is used to represent the non-linear effect of the electric field during propagation.

[0025] After obtaining the signal mapping result of the cable insulation state, further transformation is required to extract the characteristics at different frequency components; since the insulation state of the cable will affect the propagation characteristics of the electric field signal at different frequencies, directly analyzing the cable insulation situation in the time domain may be interfered by other factors, such as power supply noise, environmental interference, etc. To more effectively analyze the frequency distribution of the electric field signal, through Fourier transform, the signal mapping result of the cable insulation state is mapped to the frequency domain to achieve the conversion from the time-domain signal to the frequency-domain signal, so that different frequency components can be clearly separated, and then analyze how the cable insulation state affects the response of the electric field signal at each frequency; The time variable is converted to the frequency variable through Fourier transform, so that each frequency component of the electric field signal can be extracted, thereby analyzing the influence of the cable insulation state on signals at different frequencies.

[0026] Since the electric field signal is often interfered by high-frequency noise during measurement, which will cause fluctuations in the high-frequency components of the Fourier transform result and make it difficult to extract the fault characteristics; to improve the stability of the calculation and suppress the influence of noise on the frequency-domain analysis, the Fourier transform result is subjected to Laplace transform to obtain the signal after Laplace transform, that is, the signal after smoothing processing; The above-mentioned Fourier transform and Laplace transform are well-known technical means to those skilled in the art and will not be elaborated here.

[0027] S2. Perform multi-scale analysis on the smoothed signal, extract the fault characteristics of the cable, quantify the insulation state of the cable, and obtain the cable health index; based on the cable health index, calculate the probability of the cable insulation failure to provide a basis for fault warning and maintenance.

[0028] Perform multi-scale analysis on the smoothed signal to further extract the fault characteristics of the cable; since the change in the cable insulation state not only affects the spatial distribution of the electric field signal but also causes the non-linear attenuation of the electric field signal in time, and at the same time, the response to signals of different frequencies will also be different, it is necessary to construct a third-order signal matrix that can simultaneously contain spatial, temporal, and frequency information; each dimension of the third-order signal matrix corresponds to the spatial sampling points along the length of the cable, the temporal sampling points, and the frequency channels respectively, so that the characteristics of the electric field signal at different positions, different times, and different frequencies can be comprehensively captured. Specifically, discretize the spatial, temporal, and frequency dimensions into a finite number of sampling points to generate a third-order signal matrix , and the specific definition formula is as follows: , where, is the third-order signal matrix for storing the signal after Laplace transform represents the signal intensity at the \(m\)th spatial sampling point , the \(n\)th temporal sampling point , and the \(f\)th frequency channel ; represents the real number field; is the number of spatial sampling points, representing the number of sampling points along the length of the cable, which is set according to the actual requirements of the cable length and the required measurement accuracy; is the number of temporal sampling points, which is determined by the sampling rate and the duration of the entire sampling window; is the number of frequency channels, which is determined by the spectral range and frequency resolution of the signal. Subsequently, in order to introduce the time dynamic characteristics, a dynamic time window dimension is added to the third-order signal matrix to define a fourth-order tensor: , where, is the fourth-order tensor; is the signal attenuation factor, which is used to simulate the attenuation rate of the signal over time and is obtained through experiments, and its value range is determined according to factors such as the dielectric characteristics of the cable insulation material and the environment; It is a dynamic time window index, representing the variation of the electric field signal with the time window, and the value range depends on the number of time windows. A fourth-order tensor is used to store signal data at different scales. CP decomposition or Tucker decomposition is used to perform tensor decomposition on the fourth-order tensor to extract key features and obtain the fault characteristics of the cable. Both the CP decomposition and Tucker decomposition are well-known technical means in the art and will not be elaborated here. To further analyze the insulation state of the cable, based on the fault characteristics of the cable, through the classical electric field integral theory, and introducing a normalization factor and a topological integral normalization factor, a normalized electric field topology mapping is obtained to acquire the electric field distribution of the cable under different states. The formula for the normalized electric field topology mapping is as follows: , where, is the normalized electric field topology mapping, used to depict the topological changes in the cable insulation fault area; is the normalization factor, obtained through experimental fitting to ensure dimension matching, and the value range is ; is the topological integral normalization factor, used to adjust the scale of the topological integral , obtained through experiments, and the value range is ; represents a closed path of electric field change, obtained through experiments; is the infinitesimal increment on the integration path, obtained through electromagnetic field theory and numerical calculation methods.

[0029] To further analyze the health state of the cable, by integrating signal characteristics, topological electric field parameters, and frequency response, a health index model is constructed to quantify the cable insulation state and calculate the cable health index. The comprehensive signal characteristics refer to the distribution of the electric field signal along different positions and times of the cable and its attenuation characteristics over time. The topological electric field parameters refer to the topological changes in the internal electric field of the cable. Specifically, each term in the formula represents the response of the electric field at different positions, times, and frequencies, including the attenuation effect of the amplitude of the signal component, the change effect of the frequency, and the influence brought by the change of the electric field phase. By calculating the cable health index, the insulation state of the cable is comprehensively evaluated, and then the possible fault areas of the cable can be inferred. The specific formula for the health index model is as follows: , where, is the cable health index, representing the health state of the cable at position , time and frequency ; is derived from the classical oscillatory signal description and attenuation model, represents the comprehensive signal characteristics, represents the frequency response; represents the electric field topology characteristics of the cable. Considering that there may be local defects and inhomogeneities in the cable insulation layer, it is necessary to combine the distribution of the electric field inside the cable and the topology characteristics of local faults. is a logarithmic function used to smooth the influence of the electric field topology; is from the amplitude of the signal component extracted from, representing the signal intensity at the th spatial sampling point and the th time sampling point; is the time decay coefficient, which is the signal decay factor at the th spatial sampling point and the th time sampling point, obtained through experiments, and the value range is ; is at the th spatial sampling point and the th time sampling point of the signal angular frequency; is the phase offset, which is the phase angle at the th spatial sampling point and the th time sampling point, obtained through Fourier transform, and the value range is ; represents the change rate of the electric field signal; is the normalization factor, used to ensure dimensional consistency, obtained through experiments, and the value range is ; is the normalized voltage factor, which is the reference voltage set according to the expert experience method, matching the amplitude of the electric field signal component, and the value range is ; is the normalized length factor, which is the reference length set according to the expert experience method, and the value range is , matching the spatial distribution of the electric field signal; represents the electric field strength.

[0030] By integrating the cable health index, calculate the probability of the cable insulation failure, covering the health status of the entire cable length, and ensure its numerical stability through the exponential decay form, while reflecting the contribution of different regions to the overall insulation failure risk. The calculation formula of the probability of the cable insulation failure is as follows: , where, represents the probability of the cable insulation failure, and the numerical range is between [0,1]. represents completely healthy, represents extremely high failure risk; is the normalization scale factor, obtained through experimental fitting to ensure that the exponential function parameters are dimensionless, with a value range of ; represents the cumulative calculation of the cable health index along the entire length of the cable, ensuring that the health status of the entire cable can be comprehensively considered, so that the impact of local damage on the whole can be accurately evaluated.

[0031] When the insulation condition of a certain area of the cable deteriorates sharply, the value of the cable health index in the corresponding area will increase, causing the probability value of the cable insulation failure to rise rapidly, thereby triggering an early warning, ensuring that the cable insulation state can be accurately reflected in practical applications and providing a reliable reference for preventive maintenance.

[0032] In summary, a method for detecting cable insulation faults has been completed.

[0033] The sequence of the invention embodiments is only for description and does not represent the superiority or inferiority of the embodiments. The processes depicted in the drawings do not necessarily require the specific order or continuous order shown to achieve the desired result. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0034] Each embodiment in this specification is described in a progressive manner. For the same or similar parts between the embodiments, reference can be made to each other. Each embodiment focuses on the differences from other embodiments.

[0035] The above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that they can still modify the technical solutions recorded in the foregoing embodiments, or perform equivalent replacements for some of the technical features; and these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention, and should all be included in the protection scope of the present invention.

Claims

1. A method for detecting cable insulation faults, characterized in that, It includes the following steps: S1. Measure the electric field signal, construct the electric field distribution model inside the cable, and obtain the signal mapping result of the cable insulation state; Convert the signal mapping result of the cable insulation state from the time domain signal to the frequency domain signal, and perform smoothing processing to obtain the smoothed signal; S2. Perform multi-scale analysis on the smoothed signal, extract the fault characteristics of the cable, and quantify the insulation state of the cable to obtain the cable health index; Based on the cable health index, calculate the probability of the cable insulation fault, providing a basis for fault warning and maintenance.

2. The detection method of a cable insulation fault according to claim 1, wherein The specific content of S1 includes: Perform data interpolation, Fourier transform and error correction on the electric field signals at different positions and times inside the cable to obtain the electric field distribution data, and fit the electric field distribution model inside the cable by the least square method to obtain the electric field distribution inside the cable.

3. The detection method for cable insulation faults according to claim 2, characterized in that, The specific content of S1 includes: Based on the influence of time, space and frequency on the electric field distribution, introduce a non-linear modulation factor, construct the kernel function of signal propagation, and combine with the electric field distribution inside the cable to obtain the signal mapping result of the cable insulation state.

4. The detection method for a cable insulation fault according to claim 3, characterized in that, The specific content of S1 includes: Map the signal mapping result of the cable insulation state to the frequency domain through Fourier transform to obtain the Fourier transform result; perform Laplace transform on the Fourier transform result to obtain the smoothed signal.

5. A method for detecting a cable insulation fault according to claim 1, characterized in that, The specific content of S2 includes: Discretize the smoothed signal into spatial, temporal and frequency dimensions to generate a third-order signal matrix; based on the third-order signal matrix, introduce a dynamic time window to construct a fourth-order tensor; perform tensor decomposition on the fourth-order tensor to extract the fault characteristics of the cable.

6. The detection method for cable insulation faults according to claim 5, characterized in that, The specific content of S2 includes: Based on the fault characteristics of the cable, introduce a normalization factor and a topological integral normalization factor to obtain the normalized electric field topology mapping.

7. The detection method of a cable insulation fault according to claim 6, characterized in that, The specific content of S2 includes: Based on the normalized electric field topology mapping, quantify the insulation state of the cable by integrating the signal characteristics, topological electric field parameters and frequency response to obtain the cable health index; the comprehensive signal characteristics are the electric field signal distributions along different positions and times of the cable and their attenuation characteristics over time; the topological electric field parameters refer to the topological changes of the electric field inside the cable.

8. The detection method for a cable insulation fault according to claim 7, characterized in that, The specific content of S2 includes: Integrate the cable health index and introduce exponential decay to calculate the probability of the cable insulation fault; when the insulation condition of the cable area deteriorates, the cable health index of the corresponding area increases, and the probability value of the cable insulation fault rises, triggering a warning.

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