Cable defect detection method and system based on double-path coupling frequency domain reflection

Abstract

The invention discloses a cable defect detection method and system based on double-path coupling frequency domain reflection, and the method comprises the steps: enabling a signal generator to generate two groups of correlated sine frequency sweeping signals, namely a test signal S1 and a reference signal S2; s1 is injected into the head end of the cable, and a reflected signal R1 is collected; respectively extracting the spectrum characteristics of the amplitudes and the phase differences of the R1, the S1 and the S2 by adopting a double-path signal comparison device, carrying out comprehensive judgment, and determining the reflection spectrum characteristic of the R1; the reflection coefficient spectrum is optimized through a window function, and signal features are obtained; converting the optimized frequency spectrum into a time domain reflection waveform, and extracting reflection peak time information; and calculating defect positions by combining electromagnetic wave propagation velocity. According to the cable defect detection method and system based on double-path coupling frequency domain reflection, high-precision detection of a long-distance cable is realized; and two paths of coupling signals are introduced for comparison, so that the accuracy of phase measurement is improved, and an efficient nondestructive detection scheme is provided for power grid operation and maintenance and the like.

Description

Technical Field

[0001] The present invention relates to the technical field of power cable detection, and in particular to a cable defect detection method and system based on dual-path coupled frequency domain reflection. Background Art

[0002] As infrastructure modernization continues, power cables have become a vital component of modern power transmission and distribution networks. However, cable manufacturing, installation, operation, and maintenance present numerous challenges throughout their lifecycle. Factors such as non-standard construction, mechanical impact, and complex external environments can easily damage cable insulation. These potential defects can lead to partial discharge and ultimately insulation breakdown. Therefore, accurately locating local defects in power cables is not only a key technology for preventing line failures but also a crucial technical support for ensuring stable grid operation.

[0003] Existing cable defect location methods include impedance, partial discharge, and traveling wave methods. The traveling wave method stands out among these methods due to its ease of use and lack of complex hardware. Its core principle is to inject a unipolar, low-voltage pulse wave into the cable headend. The pulse signal propagates through the cable and generates a reflected wave, which is then reflected from defects or impedance mismatches. 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 can be calculated.

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

[0005] Furthermore, using a single-path frequency domain reflectometry to determine defect locations 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. Consequently, 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 cable defect detection methods to meet the growing reliability and stability requirements of modern power systems. Summary of the Invention

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

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

[0009] Step S1: Use a signal generator to generate two sets of correlated sinusoidal swept frequency signals, namely, a test signal S1 and a reference signal S2; inject the test signal S1 into the head end of the cable and collect the reflected signal R1;

[0010] Step S2: Coupler-1 is used to separate the test signal S1 from the reflected signal R1 from the cable, and coupler-2 transmits the reference signal S2 to signal comparator-2;

[0011] Step S3: extract the spectrum characteristics of the amplitude and phase difference between the reflected signal R1 and the test signal S1 and the reference signal S2 respectively through the signal comparator-1 and the signal comparator-2, and make a comprehensive judgment on the amplitude and phase characteristics of R1, S1 and S2 to determine the reflection spectrum 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 through an inverse Fourier transform to extract the reflection peak time information;

[0013] Step S5: Calculate the defect position 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 spectrum characteristics of the amplitude and phase difference between the reflected signal R1 and the test signal S1 and the reference signal S2 are extracted by the signal comparator-1 and the signal comparator-2, and the amplitude and phase characteristics of R1, S1 and S2 are comprehensively judged to determine the reflection spectrum 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 part and the imaginary part of the reflected signal R1, as shown below:

[0016] Real part:

[0017] Imaginary part:

[0018] in, and Represent the phases of the reflected signal R1 and the test signal S1 respectively; the specific amplitude of the reflected signal R1 is obtained through the size and phase difference of the real and imaginary parts;

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

[0020] Step S321: Introduce the reference signal S2 to ensure that there is a predetermined phase difference Δθ between the test signal S1 and the 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 part and the imaginary part of the same reflected signal R1, as shown below:

[0023] Real part:

[0024] Imaginary 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, respectively, as shown below:

[0027] Test channel 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] Among them, this relationship allows the two-way signal comparison method to be used for mutual verification to obtain Accurate value, eliminating the phase ambiguity caused by the non-uniqueness of the cosine function generated by single path measurement, ensuring that the phase information of the reflected signal R1 is unique and deterministic;

[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, an accurate determination of the amplitude-phase characteristics of R1 is finally achieved.

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

[0034] A. For amplitude, the average value of the two signals is used for optimization. If the amplitudes of the two signals are significantly different, the measurement result is discarded and remeasured.

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

[0036] Preferably, the range utilization is introduced to perform quality screening on the amplitude and phase data, wherein the applicable scenarios of the screening rules include but are not limited to amplitude one channel and phase one channel, amplitude one channel and phase two channels, amplitude two channels and phase one channel, and amplitude two channels and phase two channels. The specific screening rules are as follows:

[0037] First, let β be the distribution interval of the phase measurement value within its range, and set two proportional coefficients α1 and α2, where 0<α1<α2, to evaluate the quality of the data. The specific evaluation indicators are:

[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 medium;

[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:

[0042] (1) When the data quality β1 is in the low-quality interval β1<α1∪β1>1-α1, the data of this channel is unreliable, and the measurement result of this channel is completely discarded, and 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 interval β2<α1∪β2>1-α1, only the measurement result of the other channel is used as the final phase value;

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

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

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

[0046] Step S41: Use the Gaussian pulse window function to perform optimization processing, as shown below:

[0047]

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

[0049] Step S42: Convert the frequency domain signal into a time domain signal through 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 is calculated; the core of this process is to convert the frequency characteristics in the frequency domain into time characteristics in the time domain, and calculate the location of the defect by the time difference.

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

[0054] The distance L between the cable defect and the first section of the cable defect The calculation is as follows:

[0055]

[0056] Where Δt is the time difference between the reflection peak and the incident peak; v is the propagation speed of the electromagnetic wave, 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 is the relative dielectric constant of the cable insulation material; c0 is the speed of electromagnetic waves in vacuum; μ ris the relative magnetic permeability of the cable insulation material.

[0059] 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. The system injects multi-band steady-state sinusoidal signals into the cable and analyzes cable impedance changes in combination with frequency domain reflection characteristics to achieve non-destructive defect location and severity judgment.

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

[0061] Therefore, the present invention adopts the above-mentioned cable defect detection method and system based on dual-path coupled frequency domain reflection, and the beneficial effects are as follows:

[0062] (1) The present invention realizes nondestructive detection of cable defects through reasonable design and utilization of the change in reflection coefficient caused by impedance mismatch at the defect location, overcoming the problems of fast signal attenuation and short positioning distance of 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 the injection signal and the reflected signal, avoiding single-channel signal aliasing interference and significantly improving the detection sensitivity of small defects;

[0064] (3) The present invention introduces a dual-path coupling signal, cross-compares the two-path data and combines the amplitude information to accurately determine the true amplitude and phase characteristics of the reflected signal, thereby overcoming the phase ambiguity problem that exists when relying solely on a single path. At the same time, it also improves the detection accuracy of signals with small amplitudes and slight phase changes, and significantly enhances the overall anti-interference performance of the system.

[0065] The technical solution of the present invention is further described in detail below through the accompanying drawings and embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

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

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

[0068] Figure 3 It is a schematic diagram of the principle of the present invention using dual-path coupled signals to accurately reflect signals. DETAILED DESCRIPTION

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

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

[0071] Step S1: Use a signal generator to generate two sets of correlated sinusoidal swept frequency signals, namely, a test signal S1 and a reference signal S2; inject the test signal S1 into the head end of the cable and collect the reflected signal R1;

[0072] Step S2: Coupler-1 is used to separate the test signal S1 from the reflected signal R1 from the cable, and coupler-2 transmits the reference signal S2 to signal comparator-2;

[0073] Step S3: extract the spectrum characteristics of the amplitude and phase difference between the reflected signal R1 and the test signal S1 and the reference signal S2 respectively through the signal comparator-1 and the signal comparator-2, and make a comprehensive judgment on the amplitude and phase characteristics of R1, S1 and S2 to determine the reflection spectrum 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 through an inverse Fourier transform to extract the reflection peak time information;

[0075] Step S5: Calculate the defect position 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 The system, shown in Figure 1, uses dual-channel coupled frequency-domain reflectometry to detect cable defects. It 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 cable impedance changes using frequency-domain reflectometry characteristics, enabling non-destructive defect location and severity assessment. The hardware detection module includes a master control module, a signal generator, couplers 1 and 2, and signal comparators 1 and 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 correlated sinusoidal swept frequency signals, namely, a test signal S1 and a reference signal S2, through a signal generator; inject the test signal S1 into the head end of the cable and collect the 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 transmits the reference signal S2 to signal comparator-2.

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

[0082] Given that there's no one-to-one mapping between phase output and signal gain—that is, when the phase outputs are opposite, the signal gains may be identical—to resolve this phase ambiguity, the present invention introduces a reference signal S2 to uniquely determine the spectral characteristics of the reflected signal phase. By introducing a dual-path signal for comparison, the amplitude and phase of the cable reflection signal R1 can be precisely 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, as shown in FIG. Figure 3 As shown, the real and imaginary parts are obtained as follows:

[0084] Real part:

[0085] Imaginary part:

[0086] in, and Represent the phases of the reflected signal R1 and the test signal S1 respectively. The specific amplitude of the reflected signal R1 is obtained through the size and phase difference of the real and imaginary parts.

[0087] Step S32: introducing a reference signal S2 to uniquely determine the frequency spectrum 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 can easily lead to phase non-uniqueness and fail to accurately determine the true phase difference between R1 and S1. To resolve the phase ambiguity issue, a reference signal S2 is introduced to ensure 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 in the direction of the reference signal S2 to obtain the real part and the imaginary part, as shown below:

[0091] Real part:

[0092] Imaginary part:

[0093] in, 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, respectively, as shown below:

[0095] Test channel 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 the two-way signal comparison method to be used to verify each other. The precise value eliminates the phase ambiguity caused by the non-uniqueness of the cosine function generated by the single path measurement, ensuring that the phase information of the reflected signal R1 is unique and deterministic.

[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, an accurate determination of the amplitude-phase characteristics of R1 is finally achieved.

[0101] On the basis of accurate measurement of amplitude and phase, in order to further improve the reliability and accuracy of the detection results, the following data processing method is adopted:

[0102] A. For amplitude, use the average value of the two signals for optimization. If the amplitudes of the two signals are significantly different, discard the measurement result and re-measure.

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

[0104] As mentioned above, the present invention generates a dual-path coupled signal generator with a preset phase difference The test signal S1 and reference signal S2 are injected into the cable and transmitted to the signal comparator-2 through coupler-1 and coupler-2 respectively. The output of signal comparator-1 is Signal Comparator-2 Output The master control module completes phase calibration through Δθ2=Δθ1+Δθ to eliminate phase ambiguity in single-channel measurement.

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

[0106] The following is a typical scenario with one path for amplitude and two paths for phase. Figure 1 The specific screening rules are as follows:

[0107] Let β be the distribution interval of the phase measurement value within its range, and set two proportional coefficients α1 and α2, where 0<α1<α2, to evaluate the quality of the data. The specific evaluation indicators are:

[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 medium;

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

[0111] The data qualities corresponding to the two measured phase values are recorded as β1 and β2 respectively, and then the phase data is processed:

[0112] (1) When the data quality β1 is in the low data quality range, that is, β1 < α1 or β1 > 1-α1, the data of this channel is considered unreliable and the measurement result of this 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, that is, α2≤β1≤1-α2 and α2≤β2≤1-α2, both data are considered reliable and the arithmetic mean of the two measurement results is used as the final phase value;

[0114] (3) In other cases, if both channels are in the medium data quality range, that is, α1≤β1, β2<α2∪1-α2<β1, β2≤1-α1, or one channel is in the high quality range and the other channel is in the medium quality range, a weighted average can be performed based on the specific values of β1 and β2, and a larger weight can be assigned to the channel 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 logically adapted accordingly. The quality judgment criteria and processing principles for single-channel and multi-channel amplitude / phase are fully reused, with only the number of channels adjusted. Low-quality channels are discarded, prioritizing high-quality channels. Redundancy checks are triggered when multiple channels have low quality.

[0116] Step S4: Optimize the reflection coefficient spectrum through 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 through inverse Fourier transform to extract the reflection peak time information.

[0117] Because noise and signal leakage may exist during spectrum analysis, windowing techniques can effectively suppress these issues. Windowing optimization typically uses a Gaussian window function, which reduces spectrum leakage and improves spectral resolution, enabling the system to more accurately capture subtle changes in defects.

[0118] Step S41: Use the Gaussian pulse window function to perform optimization processing, 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 through inverse Fourier transform (IFFT) to obtain time domain information of the cable reflection.

[0122] The time-domain reflectometry waveform displays the time delay of the reflected signal—the time it takes for the signal to reflect from the defect and return. By extracting the timing information of the reflection peak, the specific location of the defect in the cable can be accurately calculated. This step involves converting the "frequency characteristics" in the frequency domain into "time characteristics" in the time domain, allowing the defect location to be calculated based on the time difference.

[0123] The IFFT is used to calculate the time domain reflection signal 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 pulse function.

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

[0127] The distance between the cable defect and the first section 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 propagation speed of the electromagnetic wave, 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 is the relative dielectric constant of the cable insulation material, c0 is the speed of electromagnetic waves in vacuum, μ r is the relative magnetic permeability of the cable insulation material.

[0132] Therefore, the present invention adopts the above-mentioned cable defect detection method based on dual-path coupled frequency domain reflection. Through reasonable design, the reflection coefficient change caused by the impedance mismatch at the defect position is utilized to realize non-destructive detection of cable defects, overcoming the problems of fast signal attenuation and short positioning distance of the traditional time domain reflection method; the architecture of the combination of signal coupling module and signal comparison module is designed to realize the precise separation and synchronous acquisition of injection signal and reflection signal, avoid the aliasing interference of single-path signal, and significantly improve the detection sensitivity of tiny defects; by introducing dual-path coupled signal, cross-comparing the two-path data and combining the amplitude information, the true amplitude and phase characteristics of the reflected signal are accurately judged, overcoming the phase ambiguity problem that only relies on a single path, while also improving the detection accuracy of small-amplitude and small-phase change signals, and significantly improving 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 rather than to limit the same. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that they can still modify or replace the technical solutions of the present invention with equivalents, and these modifications or equivalent replacements 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 reflectometry, characterized in that: The following steps are involved: Step S1: Use a signal generator to generate two sets of correlated sinusoidal swept frequency signals, namely, a test signal S1 and a reference signal S2; inject the test signal S1 into the head end of the cable and collect the reflected signal R1; Step S2: Coupler-1 is used to separate the test signal S1 from the reflected signal R1 from the cable, and coupler-2 transmits the reference signal S2 to signal comparator-2; Step S3: extract the spectrum characteristics of the amplitude and phase difference between the reflected signal R1 and the test signal S1 and the reference signal S2 respectively through the signal comparator-1 and the signal comparator-2, and make a comprehensive judgment on the amplitude and phase characteristics of R1, S1 and S2 to determine the reflection spectrum characteristics of R1; 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 through inverse Fourier transform to extract reflection peak time information; Step S5: Calculate the defect position 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 reflectometry according to claim 1, characterized in that: In step S3, the spectrum characteristics of the amplitude and phase difference between the reflected signal R1 and 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 are comprehensively judged with those of S1 and S2 to determine the reflected spectrum characteristics of R1. The specific process is as follows: Step S31: Decompose the reflected signal R1 along the direction of the test signal S1 to obtain the real part and the imaginary part of the reflected signal R1, as shown below: Real part: Imaginary part: in, and Represent the phases of the reflected signal R1 and the test signal S1 respectively; the specific amplitude of the reflected signal R1 is obtained through the size and phase difference of the real and imaginary parts; Step S32: introducing a reference signal S2 to uniquely determine the spectral characteristics of the reflected signal phase; Step S321: Introduce the reference signal S2 to ensure that there is a predetermined phase difference Δθ between the test signal S1 and the reference signal S2, as shown below: Step S322: Decompose the same reflected signal R1 along the direction of the reference signal S2 to obtain the real part and the imaginary part of the same reflected signal R1, as shown below: Real part: Imaginary part: in, represents the phase of the reference signal S2; 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, respectively, as shown below: Test channel phase difference Δθ1: Reference path phase difference Δθ2: Based on the known phase difference Δθ between S1 and S2, the following relationship exists, as shown below: Δθ2=Δθ1+Δθ; Among them, this relationship allows the two-way signal comparison method to be used for mutual verification to obtain Accurate value, eliminating the phase ambiguity caused by the non-uniqueness of the cosine function generated by single path measurement, ensuring that the phase information of the reflected signal R1 is unique and deterministic; Step S33 : By cross-comparing the phase relationship between the first phase difference and the second phase difference and combining the amplitude spectrum characteristics, an accurate determination of the amplitude-phase characteristics of R1 is finally achieved.

3. The cable defect detection method based on dual-path coupled frequency domain reflectometry according to claim 2, characterized in that: On the basis of accurate measurement of amplitude and phase, in order to further improve the reliability and accuracy of the detection results, the following data processing method is adopted: A. For amplitude, the average value of the two signals is used for optimization. If the amplitudes of the two signals differ significantly, the measurement result is discarded and remeasured. B. For phase, the quality of phase data is judged by range utilization and corresponding processing strategies are adopted.

4. The cable defect detection method based on dual-path coupled frequency domain reflectometry according to claim 3, characterized in that: Range utilization is introduced to perform quality screening on amplitude and phase data. The applicable scenarios of the screening rules include but are not limited to amplitude-only, phase-only, amplitude-only, phase-only, amplitude-only, phase-only, amplitude-only, phase-only, and amplitude-only. The specific screening rules are as follows: First, let β be the distribution interval of the phase measurement value within its range, and set two proportional coefficients α1 and α2, where 0<α1<α2, to evaluate the quality of the data. The specific evaluation indicators are: When β<α1 or β>1-α1, the data quality is low; When α1≤β<α2 or 1-α2<β≤1-α1, the data quality is medium; When α2≤β≤1-α2, the data quality is high; Then, when the data qualities corresponding to the two measured phase values are β1 and β2 respectively, the phase data is processed: (1) When the data quality β1 is in the low-quality interval β1<α1∪β1>1-α1, the data of this channel is unreliable, and the measurement result of this channel is completely discarded, and 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 interval β2<α1∪β2>1-α1, only the measurement result of the other channel is used as the final phase value; (2) When both β1 and β2 are in the high-quality interval of the data α2≤β1≤1-α2∩α2≤β2≤1-α2, the two-way data are both reliable, and the arithmetic mean of the two-way measurement results is used as the final phase value; (3) In other cases, that is, when both paths are in the medium quality interval of the data (α1≤β1,β2<α2∪1-α2<β1,β2≤1-α1), or when one path is in the high quality interval and the other path is in the medium quality interval, a weighted average is performed based on the specific values of β1 and β2, and a larger weight is assigned to the path with higher quality to obtain the final phase value.

5. The cable defect detection method based on dual-path coupled frequency domain reflectometry according to claim 1, characterized in that: In step S4, the reflection coefficient spectrum is optimized by a window function to remove interference and improve signal resolution, thereby obtaining signal characteristics; the optimized spectrum is converted into a time domain reflection waveform by inverse Fourier transform, and the reflection peak time information is extracted. The specific process is as follows: Step S41: Use the Gaussian pulse window function to perform optimization processing, as shown below: Where W(f) is the Gaussian pulse function; f is the frequency of the electromagnetic wave; f0 is the center frequency; σ is the window width control parameter; Step S42: Convert the frequency domain signal into a time domain signal through inverse Fourier transform (IFFT) to obtain the time domain information h(t) of the cable reflection, as shown below: h(t)=IFFT[K(f)·W(f)]; where K(f) is the reflection coefficient.

6. The cable defect detection method based on dual-path coupled frequency domain reflection according to claim 5, characterized in that: 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 time characteristics in the time domain and calculate the location of the defect through the time difference.

7. The cable defect detection method based on dual-path coupled frequency domain reflectometry according to claim 1, characterized in that: In step S5, the defect position is calculated by measuring the time difference of the time domain reflection peak and combining it with the electromagnetic wave propagation velocity. The specific process is as follows: The distance L between the cable defect and the first section of the cable defect The calculation is as follows: Where Δt is the time difference between the reflection peak and the incident peak; v is the propagation speed of the electromagnetic wave, which is calculated as follows: 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 is the relative dielectric constant of the cable insulation material; c0 is the speed of electromagnetic waves in vacuum; μ r is the relative magnetic permeability of the cable insulation material.

8. A cable defect detection method based on dual-path coupled frequency domain reflection according to claims 1-7, applied to a cable defect detection system based on dual-path coupled frequency domain reflection, 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. 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 defect location and severity judgment.

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

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