A cable defect detection method and system based on two-path coupled frequency domain reflection

Abstract

The application discloses a kind of cable defect detection method and system based on two-way coupling frequency domain reflection, comprising: by signal generator, the two groups of associated sine sweep signals generated, i.e.test signal S1 and reference signal S2;S1 is injected into cable head, and reflection signal R1 is collected;Two-way signal comparison device is used to extract the amplitude, phase difference frequency spectrum characteristics of R1, S1 and S2 respectively, comprehensive judgment is carried out, and the reflection spectrum characteristics of R1 are determined;Optimization processing is carried out on the reflection coefficient spectrum by window function, and signal characteristics are obtained;The optimized spectrum is converted into time domain reflection waveform, and reflection peak time information is extracted;The defect position is calculated in combination with electromagnetic wave propagation speed.The application uses the above-mentioned cable defect detection method and system based on two-way coupling frequency domain reflection, realizes the high-precision detection of long-distance cable;Two-way coupling signal is introduced for comparison, the accuracy of measurement phase is improved, and an efficient nondestructive testing scheme is provided for power grid operation and maintenance.

Description

Technical Field

[0001] This invention relates to the field of power cable testing technology, and in particular to a cable defect detection method and system based on dual-path coupling frequency domain reflection. Background Technology

[0002] In the ongoing modernization of infrastructure, power cables have become a crucial component of modern power transmission and distribution networks. However, throughout the entire lifecycle of cable manufacturing, laying, and operation and maintenance, numerous challenges arise: improper construction practices, mechanical impacts, and complex external environments can easily damage the cable insulation layer. These potential defects can evolve into partial discharges and ultimately lead to insulation breakdown accidents. Therefore, accurately locating localized defects in power cables is not only a key technology for preventing line faults but also a vital technical support for ensuring the stable operation of the power grid.

[0003] Existing methods for locating cable defects include impedance methods, partial discharge methods, and traveling wave methods. Among these, the traveling wave method stands out due to its ease of operation and lack of complex hardware requirements. Its core principle involves injecting a unipolar low-voltage pulse wave into the cable end. The defect is located by utilizing the reflected wave generated when the pulse signal encounters a defect or impedance mismatch during propagation within the cable. By measuring the time difference between the incident and reflected waves and combining this with the propagation speed of electromagnetic waves in the cable, the defect location is calculated.

[0004] However, the traveling wave method has significant limitations: single-pulse signals have low energy, and the reflected signal attenuates rapidly when encountering large or multiple defects, leading to a decrease in positioning accuracy; single pulses have weak anti-interference capabilities, and in complex electromagnetic environments, noise can easily mask the effective signal, affecting accuracy; high-frequency pulses attenuate severely when propagating in long-distance cables, making it difficult to detect micron-level insulation defects; and the signal reflection superposition phenomenon in multi-branch cable networks can easily cause aliasing interference, further amplifying the positioning error. Overall, its applicability is limited to short-distance, single-fault-type scenarios, making it difficult to meet the needs of modern power systems for high-precision, complex-environment detection.

[0005] Furthermore, using single-channel frequency domain reflection to determine defect location also has significant limitations. Due to the non-uniqueness of the reflected signal phase, it is often impossible to accurately determine the true phase of the reflected signal. This means that relying solely on a single signal cannot uniquely determine the phase of the reflected signal, leading to phase ambiguity and affecting the accuracy of defect location.

[0006] Based on the above problems, there is an urgent need to research and develop new and more effective methods for cable defect detection to meet the growing reliability and stability requirements of modern power systems. Summary of the Invention

[0007] The purpose of this invention is to provide a cable defect detection method and system based on dual-path coupled frequency domain reflection. Through reasonable design, it overcomes the limitations of traditional time-domain reflection methods, such as rapid signal attenuation, and achieves high-precision detection of long-distance cables.

[0008] To achieve the above objectives, this invention provides a cable defect detection method based on dual-path coupled frequency domain reflection, comprising the following steps:

[0009] Step S1: Generate two sets of associated sinusoidal sweep signals, namely test signal S1 and reference signal S2, through a signal generator; inject test signal S1 into the cable head end and collect reflected signal R1;

[0010] Step S2: Use coupler-1 to separate the test signal S1 from the reflected signal R1 from the cable, and coupler-2 to transmit the reference signal S2 to the signal comparator-2.

[0011] Step S3: Extract the spectral characteristics of the amplitude and phase difference between the reflected signal R1 and the test signal S1 and the reference signal S2 through signal comparator-1 and signal comparator-2 respectively. Make a comprehensive judgment on the amplitude and phase characteristics of R1 and S1 and S2 to determine the reflection spectral characteristics of R1.

[0012] Step S4: Optimize the reflection coefficient spectrum using a window function to remove interference and improve signal resolution, thereby obtaining more accurate signal characteristics; convert the optimized spectrum into a time-domain reflection waveform using inverse Fourier transform to extract reflection peak time information.

[0013] Step S5: Calculate the defect location by measuring the time difference of the time-domain reflection peak and combining it with the electromagnetic wave propagation speed.

[0014] Preferably, in step S3, the amplitude and phase difference spectral characteristics of the reflected signal R1, the test signal S1, and the reference signal S2 are extracted by signal comparator-1 and signal comparator-2 respectively. The amplitude and phase characteristics of R1 and S1 and S2 are then comprehensively judged to determine the reflection spectral characteristics of R1. The specific process is as follows:

[0015] Step S31: Decompose the reflected signal R1 along the direction of the test signal S1 to obtain the real and imaginary parts of the reflected signal R1, as shown below:

[0016] Real part:

[0017] Virtual part:

[0018] in, and These represent the phases of the reflected signal R1 and the test signal S1, respectively; the specific amplitude of the reflected signal R1 is obtained by the magnitude of the real and imaginary components and the phase difference.

[0019] Step S32: Introduce reference signal S2 to uniquely determine the spectral characteristics of the reflected signal phase;

[0020] Step S321: Introduce reference signal S2 to ensure that there is a predetermined phase difference Δθ between test signal S1 and reference signal S2, as shown below:

[0021]

[0022] Step S322: Decompose the same reflected signal R1 along the direction of the reference signal S2 to obtain the real and imaginary parts of the same reflected signal R1, as shown below:

[0023] Real part:

[0024] Virtual part:

[0025] in, Represents the phase of the reference signal S2;

[0026] Step S323: Measure the first phase difference Δθ1 between S1 and R1, i.e., the test path phase difference, and the second phase difference Δθ2 between S2 and R1, i.e., the reference path phase difference, as shown below:

[0027] Test path phase difference

[0028] Reference path phase difference

[0029] Based on the known phase difference Δθ between S1 and S2, the following relationship exists, as shown below:

[0030] Δθ2=Δθ1+Δθ;

[0031] This relationship allows for mutual verification using a dual-signal comparison method. The precise value eliminates the phase ambiguity caused by the non-uniqueness of the cosine function resulting from single-path measurement, ensuring that the phase information of the reflected signal R1 has unique certainty;

[0032] Step S33: By cross-comparing the phase relationship between the first phase difference and the second phase difference, and combining the amplitude spectrum characteristics, the accurate determination of the amplitude and phase characteristics of R1 is finally achieved.

[0033] Preferably, based on accurate measurements of amplitude and phase, the following data processing method is adopted to further improve the reliability and accuracy of the detection results:

[0034] A. For amplitude, the average value of the two signals is used for optimization; if the amplitude measured by the two signals is significantly different, the measurement result is discarded and the measurement is repeated.

[0035] B. For phase, the quality of phase data is judged by the range utilization rate and corresponding processing strategies are adopted.

[0036] Preferably, range utilization is introduced to perform quality screening of amplitude and phase data. The screening rules are applicable to scenarios including but not limited to amplitude-only and phase-only, amplitude-only and phase-only, amplitude-only and phase-only, and amplitude-only and phase-only. The specific screening rules are as follows:

[0037] First, let β be the distribution range of the phase measurement value within its range, and set two scaling factors α1 and α2, where 0 < α1 < α2, to evaluate the quality of the data. The specific evaluation index is as follows:

[0038] When β < α1 or β > 1 - α1, the data quality is low;

[0039] When α1≤β<α2 or 1-α2<β≤1-α1, the data quality is moderate.

[0040] When α²≤β≤1-α², the data quality is high;

[0041] Then, when the data qualities corresponding to the two measured phase values ​​are β1 and β2 respectively, the phase data is processed as follows:

[0042] (1) When the data quality β1 is in the low quality range β1<α1∪β1>1-α1, the data of that path is unreliable. In this case, the measurement result of that path is completely discarded, and only the measurement result of the other path is used as the final phase value. Similarly, if the data quality β2 is in the low quality range β2<α1∪β2>1-α1, only the measurement result of the other path is used as the final phase value.

[0043] (2) When both β1 and β2 are in the high-quality data range α2≤β1≤1-α2∩α2≤β2≤1-α2, both data are reliable, and the arithmetic mean of the two measurement results is used as the final phase value.

[0044] (3) In other cases, when both paths are in the medium quality range of data α1≤β1,β2<α2∪1-α2<β1,β2≤1-α1, or when one path is in the high quality range and the other is in the medium quality range, a weighted average is performed based on the specific values ​​of β1 and β2, and a larger weight is assigned to the high quality path to obtain the final phase value.

[0045] Preferably, in step S4, the reflection coefficient spectrum is optimized using a window function to remove interference and improve signal resolution, thereby obtaining more accurate signal characteristics; the optimized spectrum is then converted into a time-domain reflection waveform using an inverse Fourier transform to extract the reflection peak time information. The specific process is as follows:

[0046] Step S41: Optimize using a Gaussian pulse window function, as shown below:

[0047]

[0048] Where W(f) is the Gaussian impulse function; f is the frequency of the electromagnetic wave; f0 is the center frequency; and σ is the window width control parameter.

[0049] Step S42: Convert the frequency domain signal to the time domain signal using Inverse Fourier Transform (IFFT) to obtain the time domain information h(t) of the cable reflection, as shown below:

[0050] h(t) = IFFT[K(f)·W(f)];

[0051] Where K(f) is the reflection coefficient.

[0052] Preferably, the time-domain reflection waveform can display the time delay of the reflected signal, that is, the time required for the signal to reflect from the defect and return; by extracting the time information of the reflection peak, the specific location of the defect in the cable can be calculated; the core of this process is to convert the frequency characteristics in the frequency domain into the time characteristics in the time domain, and to calculate the location of the defect by the time difference.

[0053] Preferably, in step S5, the defect location is calculated by measuring the time difference of the time-domain reflection peak and combining it with the electromagnetic wave propagation speed. The specific process is as follows:

[0054] The distance L from the cable defect to the cable start point defect The calculation method is as follows:

[0055]

[0056] Where Δt is the time difference between the reflection peak and the incident peak; v is the electromagnetic wave propagation speed, which is calculated as follows:

[0057]

[0058] Where f is the frequency of the electromagnetic wave; β is the phase constant; ω is the angular frequency; L is the inductance per unit length of the cable; C is the capacitance per unit length of the cable; ε r c is the relative permittivity of the cable insulation material; c0 is the wave velocity of electromagnetic waves in vacuum; μ rdenoted as , where is the relative permeability of the cable insulation material.

[0059] A cable defect detection system based on dual-path coupled frequency domain reflection includes a hardware detection module for signal generation, coupling and acquisition, and a signal processing module for reflection coefficient calculation and defect feature extraction. The system injects multi-band steady-state sinusoidal signals into the cable and analyzes the cable impedance changes in combination with frequency domain reflection characteristics to achieve non-destructive location of defects and severity assessment.

[0060] Preferably, the hardware detection module includes a central control module, a signal generator, coupler-1, coupler-2, signal comparator-1, and signal comparator-2.

[0061] Therefore, the cable defect detection method and system based on dual-path coupling frequency domain reflection described above have the following advantages:

[0062] (1) This invention, through reasonable design, utilizes the change in reflection coefficient caused by impedance mismatch at the defect location to achieve non-destructive testing of cable defects, overcoming the problems of fast signal attenuation and short positioning distance in the traditional time-domain reflection method;

[0063] (2) The present invention designs an architecture combining a signal coupling module and a signal comparison module to achieve precise separation and synchronous acquisition of injected and reflected signals, avoid single-channel signal aliasing interference, and significantly improve the detection sensitivity of minute defects.

[0064] (3) By introducing dual-path coupling signals, cross-comparing the two data paths and combining amplitude information, this invention can accurately determine the true amplitude and phase characteristics of the reflected signal, overcome the phase ambiguity problem that exists only by relying on a single path, improve the detection accuracy of small amplitude and small phase change signals, and significantly enhance the overall anti-interference performance of the system.

[0065] The technical solution of the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. Attached Figure Description

[0066] Figure 1 This is a hardware structure diagram of a cable defect detection system based on dual-path coupling frequency domain reflection according to the present invention;

[0067] Figure 2 This is a flowchart of a cable defect detection method based on dual-path coupling frequency domain reflection according to the present invention;

[0068] Figure 3 This is a schematic diagram illustrating the principle of the present invention, which uses dual-path coupled signals to accurately reflect signals. Detailed Implementation

[0069] The technical solution of the present invention will be further described below with reference to the accompanying drawings and embodiments.

[0070] This invention discloses a cable defect detection method based on dual-path coupled frequency domain reflection, comprising the following steps:

[0071] Step S1: Generate two sets of associated sinusoidal sweep signals, namely test signal S1 and reference signal S2, through a signal generator; inject test signal S1 into the cable head end and collect reflected signal R1;

[0072] Step S2: Use coupler-1 to separate the test signal S1 from the reflected signal R1 from the cable, and coupler-2 to transmit the reference signal S2 to the signal comparator-2.

[0073] Step S3: Extract the spectral characteristics of the amplitude and phase difference between the reflected signal R1 and the test signal S1 and the reference signal S2 through signal comparator-1 and signal comparator-2 respectively. Make a comprehensive judgment on the amplitude and phase characteristics of R1 and S1 and S2 to determine the reflection spectral characteristics of R1.

[0074] Step S4: Optimize the reflection coefficient spectrum using a window function to remove interference and improve signal resolution, thereby obtaining more accurate signal characteristics; convert the optimized spectrum into a time-domain reflection waveform using inverse Fourier transform to extract reflection peak time information.

[0075] Step S5: Calculate the defect location by measuring the time difference of the time-domain reflection peak and combining it with the electromagnetic wave propagation speed.

[0076] Example

[0077] like Figure 1 As shown, a cable defect detection system based on dual-channel coupled frequency domain reflection includes a hardware detection module for signal generation, coupling and acquisition, and a signal processing module for reflection coefficient calculation and defect feature extraction. This system injects multi-band steady-state sinusoidal signals into the cable and analyzes cable impedance changes based on frequency domain reflection characteristics to achieve non-destructive location and severity assessment of defects. The hardware detection module includes a central control module, a signal generator, coupler-1, coupler-2, signal comparator-1, and signal comparator-2.

[0078] Based on the above system, such as Figure 2 The present invention provides a cable defect detection method based on dual-path coupled frequency domain reflection, comprising the following steps:

[0079] Step S1: Generate two sets of associated sinusoidal sweep signals, namely test signal S1 and reference signal S2, through a signal generator; inject test signal S1 into the cable head end and collect reflected signal R1.

[0080] Step S2: Use coupler-1 to separate the test signal S1 from the reflected signal R1 from the cable, and coupler-2 to transmit the reference signal S2 to the signal comparator-2.

[0081] Step S3: Extract the amplitude and phase difference spectrum characteristics of the reflected signal R1, the test signal S1, and the reference signal S2 through signal comparator-1 and signal comparator-2 respectively. Make a comprehensive judgment on the amplitude and phase characteristics of R1, S1, and S2 to determine the reflection spectrum characteristics of R1.

[0082] Since there is no one-to-one mapping between phase output and signal gain—that is, when the phase outputs are opposites, the signal gain may have the same value—this invention introduces a reference signal S2 to uniquely determine the spectral characteristics of the reflected signal phase in order to resolve the resulting phase ambiguity. By introducing dual signals for comparison, the amplitude and phase of the cable reflected signal R1 can be accurately calculated using both the test signal S1 and the reference signal S2.

[0083] Step S31: Decompose the reflected signal R1 along the direction of the test signal S1, such as... Figure 3 As shown, the real and imaginary parts are obtained as follows:

[0084] Real part:

[0085] Virtual part:

[0086] in, and These represent the phases of the reflected signal R1 and the test signal S1, respectively. The specific amplitude of the reflected signal R1 is obtained by comparing the magnitudes of the real and imaginary components with the phase difference.

[0087] Step S32: Introduce reference signal S2 to uniquely determine the spectral characteristics of the reflected signal phase.

[0088] Step S321: Due to the periodicity and symmetry of the cosine function, relying solely on the comparison of S1 and R1 easily leads to phase non-uniqueness, making it impossible to accurately determine the true phase difference between R1 and S1. To solve the above phase ambiguity problem, a reference signal S2 is introduced, ensuring that there is a predetermined phase difference between the test signal S1 and the reference signal S2, as shown below:

[0089]

[0090] Step S322: Decompose the same reflected signal R1 along the direction of the reference signal S2 to obtain the real and imaginary parts, as shown below:

[0091] Real part:

[0092] Virtual part:

[0093] in, This represents the phase of the reference signal S2.

[0094] Step S323: Measure the first phase difference Δθ1 between S1 and R1, i.e., the test path phase difference, and the second phase difference Δθ2 between S2 and R1, i.e., the reference path phase difference, as shown below:

[0095] Test path phase difference

[0096] Reference path phase difference

[0097] Based on the known phase difference Δθ between S1 and S2, the following relationship exists, as shown below:

[0098] Δθ2=Δθ1+Δθ;

[0099] This relationship allows for mutual verification using a dual-signal comparison method to obtain the result. The precise value eliminates phase ambiguity caused by the non-uniqueness of the cosine function resulting from single-path measurement, ensuring that the phase information of the reflected signal R1 has unique determinism.

[0100] Step S33: By cross-comparing the phase relationship between the first phase difference and the second phase difference, and combining the amplitude spectrum characteristics, the accurate determination of the amplitude and phase characteristics of R1 is finally achieved.

[0101] Based on the precise measurement of amplitude and phase, the following data processing method is adopted to further improve the reliability and accuracy of the detection results:

[0102] A. For amplitude, the average of the two signals is used for optimization. If the amplitudes measured by the two signals differ significantly, the measurement result is discarded and the measurement is repeated.

[0103] B. For phase, the quality of phase data is judged by the range utilization rate, and different processing strategies are adopted.

[0104] As mentioned above, the present invention generates a signal with a preset phase difference using a dual-channel coupled signal generator. The test signal S1 and reference signal S2 are injected into the cable and transmitted to signal comparator-2 via coupler-1 and coupler-2 respectively. Signal comparator-1 outputs... Signal comparator-2 output The master control module performs phase verification by using Δθ2 = Δθ1 + Δθ to eliminate phase ambiguity in single-channel measurements.

[0105] However, in practical applications, factors such as environmental noise and hardware drift may cause fluctuations in measurement data. To further improve the reliability of the detection results, this invention introduces range utilization analysis to screen the amplitude and phase data for quality. The screening rules are applicable to scenarios including, but not limited to, one amplitude and one phase path, one amplitude and two phase paths, two amplitude and one phase path, and two amplitude and two phase paths.

[0106] The following example uses one path for amplitude and two paths for phase as a typical scenario, such as... Figure 1 As shown, the specific filtering rules are as follows:

[0107] Let β be the distribution range of the phase measurement value within its range. Two scaling factors α1 and α2 are set, where 0 < α1 < α2, to evaluate the quality of the data. The specific evaluation index is as follows:

[0108] When β < α1 or β > 1 - α1, the data quality is low;

[0109] When α1≤β<α2 or 1-α2<β≤1-α1, the data quality is moderate.

[0110] When α²≤β≤1-α², the data quality is high;

[0111] Let the data quality corresponding to the two measured phase values ​​be β1 and β2, respectively, and then process the phase data:

[0112] (1) When the data quality β1 is in the low data quality range, i.e. β1<α1 or β1>1-α1, the data of that channel is considered unreliable and the measurement result of that channel is completely discarded. Only the measurement result of the other channel is used as the final phase value. Similarly, if the data quality β2 is in the low quality range, only the measurement result of the other channel is used as the final phase value.

[0113] (2) When both β1 and β2 are in the range of high data quality, i.e. α2≤β1≤1-α2 and α2≤β2≤1-α2, the two data are considered to be reliable, and the arithmetic mean of the two measurement results is used as the final phase value.

[0114] (3) In other cases, such as when both paths are in the range of medium data quality, i.e. α1≤β1,β2<α2∪1-α2<β1,β2≤1-α1, or when one path is in the range of high quality and the other is in the range of medium quality, a weighted average can be performed based on the specific values ​​of β1 and β2, and a larger weight can be assigned to the path with higher quality to obtain the final phase value.

[0115] Based on the above filtering rules, scenarios with one amplitude channel and one phase channel, two amplitude channels and one phase channel, and two amplitude channels and two phase channels can be adapted accordingly. The quality judgment criteria and processing principles for single / multi-channel amplitude / phase are completely reused, with only the number of channels adjusted. After discarding low-quality channels, high-quality channel results are retained first, and redundancy verification is triggered when multiple channels are of low quality.

[0116] Step S4: Optimize the reflection coefficient spectrum using a window function to remove interference and improve signal resolution, thereby obtaining more accurate signal characteristics; convert the optimized spectrum into a time-domain reflection waveform using inverse Fourier transform to extract reflection peak time information.

[0117] Due to potential noise and signal leakage during spectral analysis, windowing techniques can effectively suppress these problems. Windowing optimization typically uses Gaussian window functions, which reduce spectral leakage effects while improving spectral resolution, enabling the system to more accurately capture subtle changes caused by defects.

[0118] Step S41: Optimize using a Gaussian pulse window function, as shown below:

[0119]

[0120] Where f0 is the center frequency, f is the frequency of the electromagnetic wave, and σ is the window width control parameter.

[0121] Step S42: Convert the frequency domain signal into a time domain signal using inverse Fourier transform (IFFT) to obtain the time domain information of the cable reflection.

[0122] Time-domain reflection waveforms can display the time delay of the reflected signal, that is, the time required for the signal to reflect from the defect and return. By extracting the time information of the reflection peak, the specific location of the defect in the cable can be accurately calculated. The core of this step lies in converting the "frequency characteristics" in the frequency domain into "time characteristics" in the time domain, and calculating the location of the defect using the time difference.

[0123] The time-domain reflection signal is calculated using IFFT, as shown below:

[0124] h(t) = IFFT[K(f)·W(f)];

[0125] Where K(f) is the reflection coefficient and W(f) is the Gaussian impulse function.

[0126] Step S5: Calculate the defect location by measuring the time difference of the time-domain reflection peak and combining it with the electromagnetic wave propagation speed.

[0127] The distance from a cable defect to the beginning of the cable is calculated as follows:

[0128]

[0129] Where Δt is the time difference between the reflection peak and the incident peak; v is the electromagnetic wave propagation speed, which is calculated as follows:

[0130]

[0131] Where f is the frequency of the electromagnetic wave; β is the phase constant; ω is the angular frequency; L is the inductance per unit length of the cable; C is the capacitance per unit length of the cable; ε r Let c be the relative permittivity of the cable insulation material, c0 be the wave velocity of electromagnetic waves in vacuum, and μ be the relative permittivity of the cable insulation material. r denoted as , where is the relative permeability of the cable insulation material.

[0132] Therefore, this invention employs a cable defect detection method based on dual-path coupling frequency domain reflection. Through reasonable design, it utilizes the change in reflection coefficient caused by impedance mismatch at the defect location to achieve non-destructive testing of cable defects, overcoming the problems of fast signal attenuation and short positioning distance in traditional time-domain reflection methods. The design incorporates a signal coupling module and a signal comparison module to achieve precise separation and synchronous acquisition of the injected and reflected signals, avoiding single-path signal aliasing interference and significantly improving the detection sensitivity of minute defects. By introducing dual-path coupling signals, cross-comparing the two data streams and combining amplitude information, the true amplitude and phase characteristics of the reflected signal are accurately determined, overcoming the phase ambiguity problem inherent in relying solely on a single path. This also improves the detection accuracy for signals with small amplitude and minute phase changes and significantly enhances the overall anti-interference performance of the system.

[0133] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit them. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can still be made to the technical solutions of the present invention, and these modifications or equivalent substitutions cannot cause the modified technical solutions to deviate from the spirit and scope of the technical solutions of the present invention.

Claims

1. A cable defect detection method based on dual-path coupled frequency domain reflection, characterized in that, Includes the following steps: Step S1: The two sets of correlated sinusoidal sweep signals generated by the signal generator are used as test signals. and reference signal Test signal Injected into the cable end to collect reflected signals ; Step S2: Use coupler 1 to transmit the test signal. With reflected signals from the cable To separate, coupler 2 will use the reference signal. Transmitted to signal comparator 2; Step S3: Extract the reflected signal using signal comparator 1 and signal comparator 2 respectively. With test signal Reference signal The spectral characteristics of amplitude and phase difference will and , The amplitude and phase characteristics are comprehensively judged to determine The reflection spectrum characteristics are as follows: Step S31: Reflect the signal Along the test signal The direction is decomposed to obtain the reflected signal. The real and imaginary parts are shown below: Real part: ; Virtual part: ; in, and Representing the reflected signals respectively and test signals The phase; by using the magnitude of the real and imaginary components and the phase difference, the reflected signal is obtained. The specific amplitude; Step S32: Introduce reference signal Used to uniquely determine the spectral characteristics of the phase of the reflected signal; Step S321: Introduce reference signal Ensure test signal With reference signal There is a predetermined phase difference between them. As shown below: ； Step S322: For the same reflected signal Along the reference signal Decompose the direction to obtain the same reflected signal. The real and imaginary parts are shown below: Real part: Virtual part: in, Representative reference signal The phase; Step S323, measure separately and The first phase difference between That is, the phase difference of the test path, and and The second phase difference between That is, the reference path phase difference, as shown below: Test path phase difference : ; Reference path phase difference : ; According to known and phase difference between The following relationships are shown below: ； This relationship allows for mutual verification using a dual-signal comparison method. Precise values ​​eliminate phase ambiguity caused by the non-uniqueness of the cosine function resulting from single-path measurements, ensuring accurate reflected signals. The phase information is uniquely deterministic; Step S33: By cross-comparing the phase relationship between the first phase difference and the second phase difference, and combining it with the amplitude spectrum characteristics, the final result is achieved. Accurate determination of amplitude and phase characteristics; Step S4: Optimize the reflection coefficient spectrum using a window function to remove interference and improve signal resolution, thereby obtaining signal characteristics; convert the optimized spectrum into a time-domain reflection waveform using inverse Fourier transform to extract reflection peak time information. Step S5: Calculate the defect location by measuring the time difference of the time-domain reflection peak and combining it with the electromagnetic wave propagation speed.

2. The cable defect detection method based on dual-path coupled frequency domain reflection according to claim 1, characterized in that, Based on the precise measurement of amplitude and phase, the following data processing method is adopted to further improve the reliability and accuracy of the detection results: A. For amplitude, the average value of the two signals is used for optimization; if the amplitude measured by the two signals is large, the measurement result is discarded and the measurement is repeated. B. For phase, the quality of phase data is judged by the range utilization rate and corresponding processing strategies are adopted.

3. The cable defect detection method based on dual-path coupled frequency domain reflection according to claim 2, characterized in that, Range utilization is introduced to filter the quality of amplitude and phase data. The filtering rules are applicable to scenarios including amplitude-only and phase-only, amplitude-only and phase-only, amplitude-only and phase-only, and amplitude-only and phase-only. The specific filtering rules are as follows: First, let's set Two scaling factors are set for the distribution range of phase measurements within their range. and ,in To assess the quality of the data, the specific evaluation indicators are as follows: when or At that time, the data quality was low; when or At that time, the data quality was moderate; when At that time, the data quality was high; Then, when the data quality corresponding to the phase values ​​measured by the two channels are respectively and At that time, the phase data is processed: (1) When data quality In the low quality range of the data If the data from one channel is unreliable, then that channel's measurement result is completely discarded, and only the measurement result from another channel is used as the final phase value; similarly, if the data quality... In the low quality range of the data In this case, only the measurement result from the other path is used as the final phase value; (2) When both roads and All are within the high-quality range of the data. When both data streams are reliable, the arithmetic mean of the two measurement results is used as the final phase value. (3) In other cases, i.e. when both streams are in the medium quality range of the data. When, or when there is a high quality interval and a medium quality interval, according to and The specific values ​​are weighted and averaged, with higher weights assigned to high-quality pathways to obtain the final phase value.

4. The cable defect detection method based on dual-path coupled frequency domain reflection according to claim 1, characterized in that, In step S4, the reflection coefficient spectrum is optimized using a window function to remove interference and improve signal resolution, thereby obtaining signal characteristics. The optimized spectrum is then converted into a time-domain reflection waveform using an inverse Fourier transform to extract the reflection peak time information. The specific process is as follows: Step S41: Optimize using a Gaussian pulse window function, as shown below: ； in, It is a Gaussian impulse function; The frequency of electromagnetic waves; σ is the center frequency; σ is the window width control parameter. Step S42: Convert the frequency domain signal into a time domain signal using Inverse Fourier Transform (IFFT) to obtain the time domain information of the cable reflection. As shown below: ； in, It is the reflection coefficient.

5. The cable defect detection method based on dual-path coupled frequency domain reflection according to claim 4, characterized in that, Time-domain reflection waveforms can display the time delay of the reflected signal, that is, the time required for the signal to reflect from the defect and return. By extracting the time information of the reflection peak, the specific location of the defect in the cable can be calculated. The core of this process is to convert the frequency characteristics in the frequency domain into the time characteristics in the time domain, and to calculate the location of the defect by the time difference.

6. The cable defect detection method based on dual-path coupled frequency domain reflection according to claim 1, characterized in that, In step S5, the defect location is calculated by measuring the time difference of the time-domain reflection peak and combining it with the electromagnetic wave propagation speed. The specific process is as follows: Distance of cable defect from cable start point The calculation method is as follows: ； Where Δt is the time difference between the reflection peak and the incident peak; The speed of electromagnetic wave propagation is calculated using the following formula: ； in, The frequency of electromagnetic waves; It is the phase constant; Angular frequency; The inductance per unit length of the cable; Capacitance per unit length of cable; The relative permittivity of the cable insulation material; The wave speed of electromagnetic waves in a vacuum; denoted as , where is the relative permeability of the cable insulation material.

7. A cable defect detection system based on dual-path coupling frequency domain reflection, used to implement the cable defect detection method based on dual-path coupling frequency domain reflection as described in any one of claims 1-6, characterized in that, The system includes a hardware detection module for signal generation, coupling and acquisition, and a signal processing module for reflection coefficient calculation and defect feature extraction. By injecting multi-band steady-state sinusoidal signals into the cable and combining the frequency domain reflection characteristics to analyze the cable impedance changes, the system can achieve non-destructive location of defects and severity assessment.

8. A cable defect detection system based on dual-path coupled frequency domain reflection according to claim 7, characterized in that, The hardware detection module includes a central control module, a signal generator, coupler 1, coupler 2, signal comparator 1, and signal comparator 2.

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