Cable broadband impedance and defect evaluation method based on cluster pulse and temperature variation tracking

Abstract

The present application relates to a kind of cable broadband impedance and defect evaluation method based on cluster pulse and temperature change tracking, comprising: cluster pulse signal is injected to the cable to be measured for excitation, time-domain waveform sequence and relaxation waveform during excitation are synchronously collected;The time-domain waveform sequence is jointly processed, broadband complex impedance spectrum is calculated, and dynamic parameter is extracted based on relaxation waveform or the micro-change response of pulse interval;Broadband complex impedance spectrum is subjected to fast fourier transform and obtains initial impedance-length spectrum, and combined with dynamic parameter and defect characteristic filter group, depth screening and feature enhancement are carried out, and multidimensional defect feature atlas is generated;Call cable geometric electrical correlation model, according to characteristic impedance deviation, the equivalent volume parameter of defect is calculated, and the broadband impedance and defect evaluation result of the cable to be measured is generated.Compared with prior art, the present application realizes the accurate evaluation of cable medium stability, the accurate positioning of hidden danger point and the preliminary quantification of physical parameter.

Description

Technical Field

[0001] This invention relates to the field of cable testing technology, and in particular to a method for evaluating cable broadband impedance and defects based on clustered pulses and temperature change tracking. Background Technology

[0002] During long-term operation, the insulation of cables gradually deteriorates due to manufacturing defects, mechanical stress, localized overheating, or electrochemical corrosion, leading to localized defects. These defects pose potential risks that can cause cable failures or even serious accidents. Therefore, accurate condition assessment and early warning of potential hazards are crucial for cables.

[0003] Currently, mainstream cable testing technologies include time-domain reflectometry, frequency-domain reflectometry, and dielectric loss spectrum analysis.

[0004] However, existing technologies generally suffer from the following bottlenecks: 1. The contradiction between sensitivity and immunity: Traditional TDR (Time Domain Reflectometry) uses a single high-energy pulse, which is insufficiently sensitive to defects with slight impedance changes, while increasing the pulse energy can easily cause damage to the cable itself. Although swept-frequency FDR (Frequency Domain Reflectometry) can obtain spectral information, it is usually a continuous or stepped frequency sweep, with dispersed energy, and its ability to excite and detect small dielectric fluctuations (especially non-reflective defects) is limited.

[0005] 2. Limited Diagnostic Dimensions: Most existing methods rely on single parameters such as the amplitude / delay information of the reflected signal or the tangent of the dielectric loss angle, lacking multi-dimensional and correlational analysis of the physical properties of defects (such as defect type, severity, and development trend). For example, FFT analysis can only provide spectral peak values, but defects with different physical mechanisms (such as bubbles, moisture dendrites, and semiconductor layer protrusions) may produce similar resonance peaks, making it difficult to distinguish them based on peak values ​​alone.

[0006] 3. Lack of dynamic process tracking: The characteristics of cable defects (especially impedance) fluctuate dynamically with temperature changes, which is a key indicator reflecting the activity and stability of defects. Existing static testing methods cannot capture this dynamic process, thus missing crucial information for assessing defect "activity".

[0007] 4. Qualitative rather than quantitative: Current technologies mostly focus on location and qualitative analysis (such as whether there are defects), making it difficult to quantitatively estimate the physical dimensions of defects (such as equivalent air gap volume and moisture-affected area), which limits the precision of condition assessment and the accuracy of life prediction.

[0008] To overcome the above shortcomings, there is an urgent need for a comprehensive evaluation method that can integrate multi-physics excitation, multi-dimensional information analysis, and dynamic process tracking. Summary of the Invention

[0009] The purpose of this invention is to overcome the shortcomings of the existing technology by providing a cable broadband impedance and defect assessment method based on cluster pulse and temperature change tracking. Through innovative cluster pulse excitation and multi-dimensional signal processing algorithms, it can achieve accurate assessment of cable dielectric stability, accurate location of potential hazards, and preliminary quantification of their physical parameters.

[0010] The objective of this invention can be achieved through the following technical solutions: A method for evaluating broadband impedance and defects in cables based on clustered pulses and temperature variation tracking includes the following steps: A preset cluster pulse signal is injected into the cable under test for excitation. The time-domain waveform sequence of voltage and current at the input end of the cable under test during the excitation period is collected simultaneously, as well as the relaxation waveform of voltage and current during the preset relaxation time after the excitation stops. The time-domain waveform sequences of the collected voltage and current are jointly processed to calculate the broadband complex impedance spectrum of the cable under test. Based on the micro-variable response of the relaxation waveform or pulse interval, the dynamic parameters characterizing the change of the cable dielectric impedance with micro heat input are extracted by the tracking algorithm. The broadband complex impedance spectrum is subjected to fast Fourier transform to obtain the initial impedance-length spectrum. Combined with the dynamic parameters and the preset defect feature filter bank, deep screening and feature enhancement are performed to generate a multi-dimensional defect feature map containing defect type identification, location, activity intensity and frequency feature distribution. Based on the defect type identifier and location, the cable geometry-electrical association model corresponding to the defect type identifier is invoked, and the equivalent volume or equivalent size parameter of the defect is calculated based on the characteristic impedance deviation of the defect location obtained based on the broadband complex impedance spectrum. By integrating the multidimensional defect feature map and equivalent volume or equivalent size parameters, broadband impedance and defect assessment results of the cable under test are generated.

[0011] Furthermore, the cluster pulse signal consists of N sub-pulses with a specific carrier frequency distribution and extremely narrow pulse width, and the corresponding mathematical expression is: In the formula, It is a cluster pulse signal. For amplitude, For frequency, For pulse width, For time delay, This is the initial phase.

[0012] Furthermore, the specific distribution satisfies: the frequency interval between adjacent sub-pulses The pulse sequence is varied according to a preset function so that its envelope in the time domain approximates that of Dirac. The function has an impact effect, and at the same time achieves optimized energy coverage within the target frequency band in the frequency domain; the preset function is a square-law or exponential-law distribution.

[0013] Furthermore, the frequency interval of the adjacent sub-pulses The expression is: In the formula, and The upper and lower limits of the target frequency band, The disturbance amplitude coefficient, , The disturbance period coefficient, The total number of sub-pulses. This is the sequence number of the sub-pulse.

[0014] Furthermore, the tracking algorithm compares the impedance response within adjacent pulse periods or at different relaxation times after the same pulse excitation, and uses a differential or least squares fitting algorithm to track the rate of change of impedance with equivalent temperature rise, thereby obtaining dynamic parameters characterizing the change of cable dielectric impedance with micro-heat input. ; The dynamic parameters The calculation expression is: In the formula, and Let be the complex impedance at two different times. For normalized cumulative heat work, The overall thermal resistance coefficient of the cable material; The dynamic parameters A positive value indicates that the impedance at the current point increases with increasing temperature, while a negative value indicates that the impedance at the current point decreases with increasing temperature.

[0015] Furthermore, the defect feature filter bank includes frequency response templates corresponding to various typical defects. The depth screening includes: determining the fault location of the cable under test based on the peak characteristics of the initial impedance-length spectrum; Calculate the broadband complex impedance spectrum of the cable under test at the fault location. Frequency response templates for each typical defect Based on the matching degree, select the frequency response template with the highest matching degree. The sign and value of the dynamic parameters at the corresponding frequency point are determined to identify the corresponding defect type.

[0016] Furthermore, the typical defects include localized air gaps, surface discharge at the interface, and conductive impurities; If the broadband complex impedance spectrum of the cable under test at a certain location If the frequency response template corresponding to the local air gap has the highest matching degree and the dynamic parameter of the corresponding frequency point at that location is a moderately negative value, then it is determined to be a local air gap defect. If the broadband complex impedance spectrum of the cable under test at a certain location If the frequency response template corresponding to the conductive impurity has the highest matching degree and the dynamic parameter of the corresponding frequency point is strongly positive, then it is determined to be a conductive impurity defect. If the broadband complex impedance spectrum of the cable under test at a certain location If the frequency response template corresponding to the surface discharge at the interface has the highest matching degree and the dynamic parameter of the corresponding frequency point at that location is a weakly positive value, then it is determined to be a surface discharge defect at the interface.

[0017] Furthermore, the model equations for the cable geometry-electrical correlation model corresponding to the local air gap defect are as follows: In the formula, This represents the equivalent impedance change at the defect location. This represents the change in the propagation constant at the defect location. The characteristic impedance of a uniform cable is given. For the dielectric constant of a perfect dielectric, Let be the equivalent dielectric constant of the defect to be solved. Let be the equivalent length of the defect to be solved. For wavelength, This is a shape factor function related to the geometry of the cable cross-section.

[0018] Furthermore, if the defect is an air gap, then the expression for calculating the equivalent volume of the defect is: In the formula, Let be the equivalent volume of the defect. This represents the effective cross-sectional area of ​​the cable insulation layer at the defect location.

[0019] Furthermore, the broadband impedance and defect assessment results of the tested cable include the cable's overall impedance uniformity assessment, defect location list, defect type and activity classification, quantitative values ​​of key defect sizes, and trend prediction results.

[0020] Compared with the prior art, the present invention has the following advantages: (1) The present invention employs a uniquely designed cluster pulse, which consists of N sub-pulses with a specific carrier frequency distribution and extremely narrow pulse width. The frequency interval between adjacent sub-pulses is not constant, but varies according to a preset function, so that the envelope of the pulse sequence in the time domain approximates Dirac. The function's impact effect, while simultaneously achieving optimized energy coverage within the target frequency band in the frequency domain. This non-uniform frequency spacing effectively breaks the periodic picket fence effect caused by traditional uniform frequency sweep, making it easier to obtain sharp main peaks in time-domain synthesis and improving the time-domain resolution of defect points.

[0021] The resulting cluster pulses possess both wide bandwidth coverage and excellent temporal focusing capability, much like a precise probe array, significantly improving the detection sensitivity and spatial resolution for minute impedance discontinuities and weak medium fluctuations.

[0022] (2) This invention is the first to track the dynamic parameters of impedance change with micro-heating. , A positive value indicates that the impedance at that point increases with temperature rise, such as in some semiconductor layer anomalies; a negative value indicates that it decreases with temperature rise, such as in moisture defects. The absolute value reflects the thermal sensitivity or activity intensity of the defect, which can effectively distinguish between stable defects and active defects (potential hazards that are developing), providing a key priority judgment basis for preventive maintenance.

[0023] (3) This invention breaks through the limitation of traditional FFT relying only on amplitude peak value by multi-dimensional feature depth screening. By calculating the matching degree between the broadband complex impedance spectrum of the cable under test at the fault location and the frequency response template of each typical defect, and judging the sign and value of the dynamic parameters at the corresponding frequency point, the corresponding defect type is determined, thus realizing the effective differentiation of the physical type of defect and greatly reducing the misjudgment rate.

[0024] (4) By establishing a cable geometry-electrical correlation model, this invention links electrical measurements with the physical dimensions of defects, achieving a leap from qualitative detection to quantitative assessment, and providing more accurate input parameters for predicting the remaining life of cables.

[0025] (5) The present invention can obtain the impedance uniformity spectrum, defect distribution map and quantitative parameters of key defects of the entire cable length in one test, thus achieving the dual purpose of evaluation and prediction. Attached Figure Description

[0026] Figure 1 This is a flowchart illustrating a cable broadband impedance and defect assessment method based on clustered pulses and temperature variation tracking provided in an embodiment of the present invention. Figure 2 This is a time-frequency domain comparison diagram of a traditional uniform frequency sweep pulse and the non-uniform cluster pulse of the present invention provided in an embodiment of the present invention; Figure 3 This invention provides a different type of defect in an embodiment of the invention. Feature diagram (positive and negative value areas); Figure 4This is a flowchart of a defect feature depth screening logic provided in an embodiment of the present invention; Figure 5 This is a schematic diagram of the geometric-electrical correlation model of a local air gap defect in a cable provided in an embodiment of the present invention; Figure 6 This is a comparison chart of the test results of the method of the present invention and the traditional TDR / FDR method on the same simulated defective cable provided in an embodiment of the present invention. Detailed Implementation

[0027] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. The components of the embodiments of the present invention described and shown in the accompanying drawings can generally be arranged and designed in various different configurations.

[0028] Therefore, the following detailed description of the embodiments of the invention provided in the accompanying drawings is not intended to limit the scope of the claimed invention, but merely to illustrate selected embodiments of the invention. All other embodiments obtained by those skilled in the art based on the embodiments of the invention without inventive effort are within the scope of protection of the invention.

[0029] It should be noted that similar labels and letters in the following figures indicate similar items. Therefore, once an item is defined in one figure, it does not need to be further defined and explained in subsequent figures.

[0030] Example 1 like Figure 1 As shown, this embodiment provides a cable broadband impedance and defect assessment method based on clustered pulse and temperature change tracking, including the following steps: S1: Inject a preset cluster pulse signal into the cable under test for excitation, and simultaneously acquire the time-domain waveform sequence of voltage and current at the input end of the cable under test during the excitation period, as well as the relaxation waveform of voltage and current during the preset relaxation time after the excitation stops. S2: The time-domain waveform sequences of the collected voltage and current are jointly processed to calculate the broadband complex impedance spectrum of the cable under test. Based on the micro-variable response of the relaxation waveform or pulse interval, the dynamic parameters characterizing the change of the cable dielectric impedance with micro heat input are extracted by the tracking algorithm. S3: Perform a fast Fourier transform on the broadband complex impedance spectrum to obtain the initial impedance-length spectrum, and combine it with dynamic parameters and a preset defect feature filter bank to perform in-depth screening and feature enhancement, generating a multi-dimensional defect feature map containing defect type identification, location, activity intensity and frequency feature distribution. S4: Based on the defect type identifier and location, call the cable geometry-electrical association model corresponding to the defect type identifier, and calculate the equivalent volume or equivalent size parameters of the defect based on the characteristic impedance deviation of the defect location obtained based on broadband complex impedance spectrum. S5: Integrate multi-dimensional defect feature maps and equivalent volume or equivalent size parameters to generate broadband impedance and defect assessment results for the cable under test.

[0031] Specifically, in step S1, the cluster pulse signal consists of N sub-pulses with a specific carrier frequency distribution and extremely narrow pulse width, and the corresponding mathematical expression is: In the formula, It is a cluster pulse signal. For amplitude, For frequency, For pulse width, For time delay, This is the initial phase.

[0032] A specific distribution satisfies the following: the frequency interval between adjacent sub-pulses. It is not constant, but varies according to a preset function, such as a square law or exponential law distribution, so that the envelope of the pulse sequence in the time domain approximates Dirac. The function aims to achieve a powerful impact while simultaneously optimizing energy coverage within the target frequency band in the frequency domain. Its design principle is to minimize the main lobe width and side lobes of the autocorrelation function of the pulse sequence.

[0033] A preferred frequency configuration follows the formula below to achieve "quasi-" for broadband media. "Shock" incentives: in, , The upper and lower limits of the target frequency band, The disturbance amplitude coefficient ( ), This is the perturbation period coefficient. This non-uniform frequency spacing can effectively break the periodic picket fence effect caused by traditional uniform frequency sweep, making it easier to obtain a sharp main peak in time-domain synthesis and improving the time-domain resolution of defect points.

[0034] In step S2, the time-domain waveforms acquired in step S1 are jointly processed to calculate the broadband complex impedance spectrum of the cable. Based on the micro-variable response of the relaxation waveform or pulse interval, a tracking algorithm is used to extract dynamic parameters characterizing the change of cable dielectric impedance with micro-heat input. .

[0035] Dynamic parameters The extraction is achieved through the following tracking algorithm: The rapid micro-area heating effect of clustered pulses causes transient changes in the local temperature at defect points (either rising or falling, depending on the defect's power dissipation characteristics). By comparing the impedance response within adjacent pulse cycles or at different relaxation times after the same pulse excitation, a difference or least-squares fitting algorithm is used to track the rate of change of impedance with equivalent temperature rise. The algorithm model is as follows: in, and Let be the complex impedance at two different moments (e.g., before the pulse is applied and at some moment after thermal relaxation), and let the denominator be the normalized cumulative heat work. This is the overall thermal resistance coefficient of the cable material (which can be obtained through calibration). A positive value indicates that the impedance at that point increases with temperature rise, such as in some semiconductor layer anomalies; a negative value indicates that it decreases with temperature rise, such as in moisture defects; the absolute value reflects the "thermal sensitivity" or activity intensity of the defect.

[0036] In step S3, the result obtained in S2 The initial impedance-length spectrum is obtained by performing a Fast Fourier Transform (FFT), and based on this, combined with... The system uses a pre-defined defect feature filter bank to perform in-depth screening and feature enhancement, generating a multi-dimensional defect feature map that includes defect type identification, location, activity intensity, and frequency feature distribution.

[0037] The defect feature filter bank contains frequency response templates corresponding to various typical defects. In-depth screening includes: determining the fault location of the cable under test based on the peak characteristics of the initial impedance-length spectrum; Calculate the broadband complex impedance spectrum of the cable under test at the fault location. Frequency response templates for each typical defect Based on the matching degree, select the frequency response template with the highest matching degree. The sign and value of the dynamic parameters at the corresponding frequency point are determined to identify the corresponding defect type.

[0038] Optionally, a characteristic filter bank containing various typical defects can be established. Among them, A-local air gap, B-interface surface discharge, C-conductive impurities, and D-moisture-induced dendrites; each filter is a frequency response template obtained from physical model simulation or training with a large amount of experimental data based on this type of defect. For the measured... Perform the following processing: 1. Calculate the matching degree with each defective filter. .

[0039] 2. Extraction Inflection point characteristics of the phase spectrum and group delay distortion characteristics.

[0040] 3. Associate with corresponding frequency points Symbols and values.

[0041] The selection logic is as follows: if a peak appears at a certain position in the FFT length spectrum, but its phase characteristics, group delay, and filter... The highest matching degree, and this point If the value is moderately negative, it is classified as a Class A defect (local air gap), and its activity level is marked. Conversely, if the phase characteristics match... ,and If the value is strongly positive, it is classified as a Class C defect (conductive impurity). This process expands the single amplitude peak feature into a multi-dimensional feature vector that includes amplitude, phase, group delay, temperature variability, and matching degree, thereby achieving a more in-depth description of the defect properties.

[0042] In step S4, based on the defect location and type identifier located in S3, the corresponding cable geometry-electrical connection model is invoked to calculate the characteristic impedance deviation at the defect location. and dynamic parameters Substitute the parameters into the model equations to calculate the equivalent volume or equivalent size parameters of the defect.

[0043] Taking the most common local air gap defect as an example, the model is established as follows: Approximating the defect as a segment of length... The equivalent dielectric constant is The dielectric is inserted into a uniform cable (characteristic impedance) propagation constant The reflection coefficient caused by this defect segment is... and transmission coefficient It can be calculated. The equivalent impedance change at the measured defect location. (From S3) and the change in the propagation constant at that point (This can be deduced from the phase spectrum) and then a system of equations can be established: in, For the dielectric constant of a perfect dielectric, For wavelength, This is a shape factor function related to the cable cross-sectional geometry (coaxial, sector-shaped, etc.). By solving a simultaneous equation, the equivalent length of the defect can be determined. and equivalent dielectric constant If we assume the defect is an air gap ( Then its equivalent volume can be further estimated. ,in This represents the effective cross-sectional area of ​​the cable insulation layer at this location.

[0044] In step S5, the results of S3 and S4 are integrated to generate a comprehensive evaluation report that includes an assessment of the impedance uniformity of the entire cable length, a list of defects, a classification of defect types and activity levels, quantitative values ​​of key defect sizes, and trend predictions.

[0045] The following is a specific implementation example of the above solution: Cluster pulse generation and injection: This step details the generation of cluster pulses. Using an arbitrary waveform generator, a set of parameters is configured according to the non-uniform frequency interval formula in the claims: Generate 20 sub-pulses, each with a pulse width of... Set to 2 carrier cycles, amplitude Hanning window weighting is used to reduce frequency domain sidelobes. This is achieved by calculating a synthesized pulse sequence. The time-domain waveform and autocorrelation function (e.g.) Figure 2 As shown in b), its main peak is sharp, and the side lobe level is higher than that of a traditional uniformly spaced sweep pulse (as shown in b). Figure 2 a) A reduction of approximately 12 dB demonstrates its superior class performance. Impact characteristics. This pulse sequence is amplified by a power amplifier and then injected into the space between the shield and the core of a 110kV cross-linked polyethylene cable through a high-voltage coupling unit.

[0046] Implementation of the tracking algorithm for dynamic temperature change parameters ΔZ / ΔT: After injecting cluster pulses, the high-speed data acquisition card synchronously records voltage and current at a high sampling rate. To extract... A double-pulse comparison method was employed: two identical cluster pulse sequences were injected within a short time (e.g., 100ms interval). Due to the slight thermal effect of the first pulse, the local temperature at the defect point had already risen slightly by the time the second pulse arrived. The impedance spectra corresponding to the responses of the two pulses were calculated separately. and Using the thermal time constant model of the cable (known through calibration), the equivalent temperature rise at the defect point within this time interval is estimated. .but . Figure 3 The results were shown at simulated moisture defects and semiconductor layer protrusion defects. The spectrum shows that the former exhibits significant negative values ​​in the characteristic frequency band, while the latter exhibits significant positive values, consistent with theoretical predictions.

[0047] Defect feature depth screening process: Obtain test data of a 10kV cable with multiple simulated defects. Figure 4 The in-depth screening process is demonstrated. First, for... FFT was performed to obtain the length-reflectance spectrum, which showed reflection peaks at 5.2m, 12.7m, and 20.1m. Traditional methods can only report anomalies at these three locations.

[0048] Enter deep filtering: For the anomaly at 5.2m, extract its frequency domain impedance. The phase curves were analyzed, revealing a significant hysteresis jump in the 1-5MHz range; the matching degree with each characteristic filter was calculated, showing a match with the "interface surface discharge" filter. The matching degree reached 85%; the ΔZ / ΔT ratio at this point was checked and found to be weakly positive. The overall assessment was "Class B defect: surface discharge at the interface, moderate activity".

[0049] The anomaly at 12.7m exhibits a flat amplitude-frequency response with a wideband dip and a gradual phase change, matching the "conductive impurity" filter H_C by 78%; ΔZ / ΔT is a strongly positive value. It is classified as a "Class C defect: conductive impurity, highly active".

[0050] The anomaly at 20.1m exhibits a distinct narrowband resonance peak, with the phase flipping at the resonance point, achieving a 92% match with the "local air gap" filter H_A; ΔZ / ΔT is a moderately negative value. It is classified as "Class A defect: local air gap, moderate activity".

[0051] This process assigns a clear physical property description to each defect point.

[0052] Quantitative Calculation of Defect Volume (Taking Air Gap as an Example): A quantitative calculation is performed for an air gap defect at a location of 20.1m. The cable is known to be a sector-shaped conductor with a cross-sectional area of... The feature of this point was extracted from the measurement data: at the center frequency of 10MHz, (Relative to characteristic impedance Z0 = 50Ω), the phase change is calculated as follows Substituting the values ​​into the system of simultaneous equations and calling the shape factor functions F1 and F2 for this type of cable (obtained beforehand through simulation), the solution is obtained as follows: , .because The value is close to 1, confirming it as an air gap. Calculate the equivalent volume. The report indicates that a tiny air gap of approximately 22.5 cubic millimeters exists at this location.

[0053] Comparative testing with traditional methods: To verify the advantages of this invention, a section known to contain three types of artificial defects (0.5mm) was selected. 3 Coaxial cable samples (with air gaps, moisture points, and semiconductor bumps) were tested using conventional high-voltage TDR equipment, commercial frequency domain reflectometers (FDR), and the method of this invention. The test results are compared in Table 1. Table 1. Performance Comparison of the Method of the Invention with Existing Technologies like Figure 6 As shown, traditional TDR can only clearly see the large reflections from the air gap and semiconductor protrusions, but it has no response to the moisture-affected points (where impedance changes are gradual). FDR can detect three anomalies, but its spectral characteristics have low distinguishability. The method of this invention not only clearly locates the three points, but its multidimensional feature spectrum can also clearly distinguish the three, and provides an estimated volume value of the air gap (0.62 mm). 3 The important conclusions are: high activity at the moisture point (with an error of 24%) and moderate activity at the semiconductor bump.

[0054] Application in on-site cable assessment: This invention was integrated into a portable tester to conduct an on-site assessment of a suspected aging 35kV cable (850 meters long) at a substation. The test took approximately 15 minutes. The system generated a full-length impedance uniformity curve and identified four potential hazard points. The report detailed a 15mm hazard at 23m. 3 The air gap at 407m (historical manufacturing defect, low activity, observation recommended); signs of moisture at 407m (high activity, re-inspection and treatment recommended as soon as possible); slight degradation of the semiconductor layer at 620m, moderate activity. This assessment provides maintenance personnel with clear, quantifiable, and prioritized decision-making criteria, avoiding indiscriminate replacement or blind continuation of operation.

[0055] The preferred embodiments of the present invention have been described in detail above. It should be understood that those skilled in the art can make numerous modifications and variations based on the concept of the present invention without creative effort. Therefore, all technical solutions that can be obtained by those skilled in the art based on the concept of the present invention through logical analysis, reasoning, or limited experimentation on the basis of existing technology should be within the scope of protection defined by the claims.

Claims

1. A method for evaluating broadband impedance and defects of cables based on clustered pulses and temperature variation tracking, characterized in that, Includes the following steps: A preset cluster pulse signal is injected into the cable under test for excitation. The time-domain waveform sequence of voltage and current at the input end of the cable under test during the excitation period is collected simultaneously, as well as the relaxation waveform of voltage and current during the preset relaxation time after the excitation stops. The time-domain waveform sequences of the collected voltage and current are jointly processed to calculate the broadband complex impedance spectrum of the cable under test. Based on the micro-variable response of the relaxation waveform or pulse interval, the dynamic parameters characterizing the change of the cable dielectric impedance with micro heat input are extracted by the tracking algorithm. The broadband complex impedance spectrum is subjected to fast Fourier transform to obtain the initial impedance-length spectrum. Combined with the dynamic parameters and the preset defect feature filter bank, deep screening and feature enhancement are performed to generate a multi-dimensional defect feature map containing defect type identification, location, activity intensity and frequency feature distribution. Based on the defect type identifier and location, the cable geometry-electrical association model corresponding to the defect type identifier is invoked, and the equivalent volume or equivalent size parameter of the defect is calculated based on the characteristic impedance deviation of the defect location obtained based on the broadband complex impedance spectrum. By integrating the multidimensional defect feature map and equivalent volume or equivalent size parameters, broadband impedance and defect assessment results of the cable under test are generated.

2. The cable broadband impedance and defect assessment method based on clustered pulse and temperature variation tracking according to claim 1, characterized in that, The cluster pulse signal consists of N sub-pulses with a specific carrier frequency distribution and extremely narrow pulse width, and the corresponding mathematical expression is: In the formula, It is a cluster pulse signal. For amplitude, For frequency, For pulse width, For time delay, This is the initial phase.

3. The cable broadband impedance and defect assessment method based on clustered pulse and temperature variation tracking according to claim 2, characterized in that, The specific distribution satisfies the following: the frequency interval between adjacent sub-pulses The pulse sequence is varied according to a preset function so that its envelope in the time domain approximates that of Dirac. The function has an impact effect, and at the same time achieves optimized energy coverage within the target frequency band in the frequency domain; the preset function is a square-law or exponential-law distribution.

4. The cable broadband impedance and defect assessment method based on clustered pulse and temperature variation tracking according to claim 3, characterized in that, The frequency interval of adjacent sub-pulses The expression is: In the formula, and The upper and lower limits of the target frequency band, The disturbance amplitude coefficient, , The disturbance period coefficient, The total number of sub-pulses. This is the sequence number of the sub-pulse.

5. The cable broadband impedance and defect assessment method based on clustered pulse and temperature variation tracking according to claim 1, characterized in that, The tracking algorithm compares the impedance response within adjacent pulse periods or at different relaxation times after the same pulse excitation. Using a difference or least squares fitting algorithm, it tracks the rate of change of impedance with equivalent temperature rise, thus obtaining dynamic parameters characterizing the change of cable dielectric impedance with micro-heat input. ; The dynamic parameters The calculation expression is: In the formula, and Let be the complex impedance at two different times. For normalized cumulative heat work, The overall thermal resistance coefficient of the cable material; The dynamic parameters A positive value indicates that the impedance at the current point increases with increasing temperature, while a negative value indicates that the impedance at the current point decreases with increasing temperature.

6. The cable broadband impedance and defect assessment method based on clustered pulse and temperature variation tracking according to claim 1, characterized in that, The defect feature filter bank contains frequency response templates corresponding to various typical defects. The depth screening includes: determining the fault location of the cable under test based on the peak characteristics of the initial impedance-length spectrum; Calculate the broadband complex impedance spectrum of the cable under test at the fault location. Frequency response templates for each typical defect Based on the matching degree, select the frequency response template with the highest matching degree. The sign and value of the dynamic parameters at the corresponding frequency point are determined to identify the corresponding defect type.

7. The cable broadband impedance and defect assessment method based on clustered pulse and temperature variation tracking according to claim 6, characterized in that, The typical defects include local air gaps, surface discharge at the interface, and conductive impurities. If the broadband complex impedance spectrum of the cable under test at a certain location If the frequency response template corresponding to the local air gap has the highest matching degree and the dynamic parameter of the corresponding frequency point at that location is a moderately negative value, then it is determined to be a local air gap defect. If the broadband complex impedance spectrum of the cable under test at a certain location If the frequency response template corresponding to the conductive impurity has the highest matching degree and the dynamic parameter of the corresponding frequency point is strongly positive, then it is determined to be a conductive impurity defect. If the broadband complex impedance spectrum of the cable under test at a certain location If the frequency response template corresponding to the surface discharge at the interface has the highest matching degree and the dynamic parameter of the corresponding frequency point at that location is a weakly positive value, then it is determined to be a surface discharge defect at the interface.

8. The cable broadband impedance and defect assessment method based on clustered pulse and temperature variation tracking according to claim 1, characterized in that, The model equations for the cable geometry-electrical correlation model corresponding to local air gap defects are as follows: In the formula, This represents the equivalent impedance change at the defect location. This represents the change in the propagation constant at the defect location. The characteristic impedance of a uniform cable is given. For the dielectric constant of a perfect dielectric, Let be the equivalent dielectric constant of the defect to be solved. Let be the equivalent length of the defect to be solved. For wavelength, This is a shape factor function related to the geometry of the cable cross-section.

9. The cable broadband impedance and defect assessment method based on clustered pulse and temperature variation tracking according to claim 8, characterized in that, If the defect is an air gap, then the expression for calculating the equivalent volume of the defect is: In the formula, Let be the equivalent volume of the defect. This represents the effective cross-sectional area of ​​the cable insulation layer at the defect location.

10. The cable broadband impedance and defect assessment method based on clustered pulse and temperature variation tracking according to claim 1, characterized in that, The broadband impedance and defect assessment results of the tested cable include the cable's overall impedance uniformity assessment, defect location list, defect type and activity classification, quantitative values ​​of key defect sizes, and trend prediction results.

Images