Cable defect positioning method, system, equipment, medium and product

Abstract

The invention relates to the technical field of power systems, and discloses a cable defect positioning method, system and device, a medium and a product, and the method comprises the steps: taking a Gaussian envelope linear chirp signal as an initial incident signal for frequency domain reflection, optimizing the signal characteristic parameter of the initial incident signal, obtaining an incident signal, and carrying out the positioning of a cable defect. The method comprises the following steps: exciting a target cable through an incident signal, obtaining a reflection signal on a preset measuring point of the target cable, respectively carrying out time-frequency conversion on the incident signal and the reflection signal to obtain an incident time-frequency domain signal and a reflection time-frequency domain signal, and obtaining a time-frequency domain signal and a reflection time-frequency domain signal on the basis of a cross-correlation function. The peak position of a cross-correlation function is determined through the incident time-frequency domain signal and the reflected time-frequency domain signal, the signal propagation defect time delay of the target cable is determined according to the peak position of the cross-correlation function, and the defect position of the target cable is determined according to the signal propagation defect time delay and the propagation speed of the incident signal. Therefore, surrounding signal interference can be filtered out, and the accuracy of cable defect positioning is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of power systems, and in particular to a cable defect locating method, system, equipment, medium and product. Background Art

[0002] Cables play a vital role in power transmission and have a direct impact on the power quality of urban power systems. However, localized defects within cables, such as insulation degradation or shield wear, can lead to significant economic losses or even loss of life if not addressed promptly. Therefore, cable defect location methods such as reflectometry have been proposed to pinpoint cable defects.

[0003] At present, the method of locating cable defects using the reflection method is easily interfered by surrounding signals, resulting in poor accuracy in cable defect positioning. Summary of the Invention

[0004] In view of this, the present invention provides a cable defect location method, system, device, medium and product, which solves the technical problem that the method of locating cable defects using the reflection method is easily interfered by surrounding signals, resulting in poor accuracy of cable defect location.

[0005] A first aspect of the present invention provides a cable defect locating method, comprising:

[0006] Determining an initial incident signal for frequency domain reflection based on a Gaussian envelope linear chirp signal;

[0007] Optimizing the signal characteristic parameters of the initial incident signal to obtain an incident signal;

[0008] Based on the frequency domain reflection method, the target cable is excited by the incident signal, and a reflected signal is obtained at a preset measuring point of the target cable;

[0009] Performing time-frequency conversion on the incident signal and the reflected signal respectively to obtain an incident time-frequency domain signal and a reflected time-frequency domain signal;

[0010] Based on the cross-correlation function, determining the peak position of the cross-correlation function through the incident time-frequency domain signal and the reflected time-frequency domain signal, and determining the signal propagation defect delay of the target cable according to the peak position of the cross-correlation function;

[0011] The defect position of the target cable is determined according to the signal propagation defect delay and the propagation speed of the incident signal.

[0012] Preferably, the signal characteristic parameters include Gaussian envelope time domain parameters and chirp modulation frequency;

[0013] The optimizing the signal characteristic parameters of the initial incident signal to obtain the incident signal includes:

[0014] Taking maximizing the product of the Gaussian envelope time domain parameter and the chirp modulation frequency as the optimization goal, and determining constraint conditions; wherein the constraint conditions include a range resolution constraint, an attenuation constraint, a trade-off coefficient constraint, and a sampling rate constraint;

[0015] Based on the constraints, an objective function corresponding to the optimization goal is optimized and solved, and optimal signal characteristic parameters are determined according to the optimal solution;

[0016] The initial incident signal is updated according to the optimal signal characteristic parameter to obtain the incident signal.

[0017] Preferably, the method based on frequency domain reflection method, wherein the target cable is excited by the incident signal and a reflected signal is obtained at a preset measuring point of the target cable, further comprises:

[0018] determining a phase delay of a frequency component caused by the incident signal propagating in the target cable based on a phase coefficient of the incident signal and a propagation length of the incident signal in the target cable;

[0019] Determining a propagation phase delay of a preset inverse filter according to the phase delay of the frequency component;

[0020] Performing Fourier transform on the incident signal to obtain an incident frequency domain signal;

[0021] Compensating the input radio frequency signal according to the propagation phase delay to obtain a compensated input radio frequency signal;

[0022] An inverse Fourier transform is performed on the compensated incident frequency domain signal to obtain an incident time domain signal; wherein the incident time domain signal is used to excite the target cable.

[0023] Preferably, performing time-frequency conversion on the incident signal and the reflected signal respectively to obtain an incident time-frequency domain signal and a reflected time-frequency domain signal comprises:

[0024] By introducing a pseudo Wigner-Ville distribution of a Gaussian rectangular window function, time-frequency conversion is performed on the incident signal and the reflected signal to obtain the incident time-frequency domain signal and the reflected time-frequency domain signal.

[0025] Preferably, the determining of the peak position of the cross-correlation function by using the incident time-frequency domain signal and the reflected time-frequency domain signal based on the cross-correlation function, and determining the signal propagation defect delay of the target cable according to the peak position of the cross-correlation function, includes:

[0026] Calculating the similarity between the incident time-frequency domain signal and the reflected time-frequency domain signal based on the cross-correlation function, and determining the position with the highest similarity as the peak position of the cross-correlation function;

[0027] The signal propagation defect delay is determined according to the peak position of the cross-correlation function and the sampling interval period.

[0028] Preferably, determining the defect location of the target cable according to the signal propagation defect delay and the propagation speed of the incident signal includes:

[0029] The distance between the defect on the target cable and the excitation point corresponding to the incident signal is determined based on the product of the signal propagation defect delay and the propagation speed of the incident signal; wherein the distance is the defect position of the target cable.

[0030] In a second aspect, the present invention further provides a cable defect location system, comprising:

[0031] An incident signal determination module, configured to determine an initial incident signal for frequency domain reflection based on a Gaussian envelope linear chirp signal;

[0032] An incident signal optimization module, configured to optimize the signal characteristic parameters of the initial incident signal to obtain an incident signal;

[0033] A signal excitation module is used to excite the target cable with the incident signal based on the frequency domain reflection method, and obtain a reflected signal at a preset measuring point of the target cable;

[0034] A time-frequency conversion module, configured to perform time-frequency conversion on the incident signal and the reflected signal to obtain an incident time-frequency domain signal and a reflected time-frequency domain signal;

[0035] a time delay determination module, configured to determine a peak position of the cross-correlation function based on the incident time-frequency domain signal and the reflected time-frequency domain signal, and determine a signal propagation defect time delay of the target cable according to the peak position of the cross-correlation function;

[0036] The defect location module is configured to determine the defect location of the target cable according to the signal propagation defect delay and the propagation speed of the incident signal.

[0037] In a third aspect, the present invention further provides an electronic device comprising a memory and a processor, wherein a computer program is stored in the memory, and when the computer program is executed by the processor, the processor executes the steps of the cable defect location method as described in the first aspect.

[0038] In a fourth aspect, the present invention further provides a computer-readable storage medium having a computer program stored thereon, which, when executed, implements the steps of the cable defect locating method as described in the first aspect.

[0039] In a fifth aspect, the present invention further provides a computer program product, comprising a computer program stored on a non-transitory computer-readable storage medium, wherein the computer program comprises program instructions, wherein when the program instructions are executed by a computer, the computer is caused to perform the steps of the cable defect location method as described in the first aspect.

[0040] It can be seen from the above technical scheme that the present invention uses a Gaussian envelope linear chirp signal as the initial incident signal for frequency domain reflection, and optimizes the signal characteristic parameters of the initial incident signal to obtain an incident signal, excites the target cable through the incident signal, and obtains a reflected signal at a preset measuring point of the target cable, performs time-frequency conversion on the incident signal and the reflected signal, respectively, to obtain an incident time-frequency domain signal and a reflected time-frequency domain signal, and based on the cross-correlation function, determines the peak position of the cross-correlation function through the incident time-frequency domain signal and the reflected time-frequency domain signal, and determines the signal propagation defect delay of the target cable according to the peak position of the cross-correlation function, and determines the defect position of the target cable according to the signal propagation defect delay and the propagation speed of the incident signal, thereby filtering out the interference of surrounding signals and improving the accuracy of cable defect positioning. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0042] Figure 1 A diagram illustrating an application environment of a cable defect location method provided by an embodiment of the present invention;

[0043] Figure 2 A flow chart of a cable defect location method provided by an embodiment of the present invention;

[0044] Figure 3 A schematic structural diagram of a cable defect location system provided by an embodiment of the present invention;

[0045] Figure 4 A schematic structural diagram of an electronic device provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0046] In order to enable those skilled in the art to better understand the solutions of the present invention, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts shall fall within the scope of protection of the present invention.

[0047] The cable defect location method provided in the embodiment of the present application can be applied to Figure 1 In the application environment shown. Among them, the terminal 101 communicates with the server 102 through the network. The data storage system can store the data that the server 102 needs to process. The data storage system can be integrated on the server 102, or placed on the cloud or other network servers. The terminal 101 or the server 102 determines the initial incident signal for frequency domain reflection based on the Gaussian envelope linear chirp signal; optimizes the signal characteristic parameters of the initial incident signal to obtain the incident signal; based on the frequency domain reflection method, the target cable is excited by the incident signal, and the reflected signal is obtained at the preset measuring point of the target cable; the incident signal and the reflected signal are time-frequency converted respectively to obtain the incident time-frequency domain signal and the reflected time-frequency domain signal; based on the cross-correlation function, the peak position of the cross-correlation function is determined by the incident time-frequency domain signal and the reflected time-frequency domain signal, and the signal propagation defect delay of the target cable is determined according to the peak position of the cross-correlation function; the defect position of the target cable is determined according to the signal propagation defect delay and the propagation speed of the incident signal.

[0048] The terminal 101 may be, but is not limited to, various personal computers, laptops, smart phones, tablet computers, and the like.

[0049] The server 102 may be an independent physical server, a server cluster or a distributed system composed of multiple physical servers, or a cloud server that provides cloud computing services.

[0050] like Figure 2 As shown, the embodiment of the present application provides a cable defect location method, which is applied to Figure 1 The terminal 101 or the server 102 in the embodiment is used as an example to illustrate the method, which includes the following steps S1 to S6.

[0051] Step S1: Determine an initial incident signal for frequency domain reflection according to a Gaussian envelope linear chirp signal.

[0052] Among them, in Time-Frequency Domain Reflectometry (TFDR), the Gaussian Envelope Linear Chirp Signal (GELC) is selected as the initial incident signal for frequency domain reflection due to its unique characteristics.

[0053] The GELC signal exhibits a linearly increasing instantaneous frequency and is enveloped by a Gaussian function, which gives the signal resolution in both the time and frequency domains. The GELC signal can be represented as follows:

[0054]

[0055] Where, is the GELC signal, is the Gaussian envelope signal, is a linear chirp signal, is the Gaussian envelope time domain parameter, is the chirp frequency, e is a constant, t is time, is the center time, j is the imaginary unit, and f is the center frequency. f can be set to 150 MHz.

[0056] Step S2: Optimize the signal characteristic parameters of the initial incident signal to obtain an incident signal.

[0057] The signal characteristic parameters include Gaussian envelope time-domain parameters and chirp frequency. The Gaussian envelope time-domain parameters control the width and shape of the Gaussian envelope, while the chirp frequency determines the rate of change of the signal's frequency. Optimizing these parameters aims to improve the efficiency of signal propagation in the cable and the clarity of the reflected signal, thereby enhancing the accuracy of defect location. The optimization process may involve complex mathematical calculations and algorithm iterations to find the optimal parameter combination that balances key factors such as distance resolution, signal strength, and anti-interference capability. By fine-tuning these parameters, the present invention can significantly improve the accuracy and reliability of cable defect location.

[0058] Step S3: Based on the frequency domain reflection method, the target cable is excited by the incident signal, and a reflected signal is obtained at a preset measuring point of the target cable.

[0059] The target cable is the cable line to be inspected, and the preset measurement points are pre-set measurement locations on the target cable. An incident signal is transmitted into the target cable at the preset transmission points via a specific transmitter, where it propagates through the cable. When the incident signal encounters a defect in the cable (such as a break, a poor joint, or moisture intrusion), part of the signal is reflected back, forming a reflected signal. This reflected signal carries information about the defect's location. By receiving these reflected signals at the preset measurement points, further analysis can be performed to determine the defect's location.

[0060] Step S4: perform time-frequency conversion on the incident signal and the reflected signal respectively to obtain an incident time-frequency domain signal and a reflected time-frequency domain signal.

[0061] Time-frequency conversion is a technique that converts signals from the time or frequency domain to the time-frequency domain, simultaneously displaying the signal's frequency characteristics as they change over time. In this invention, appropriate time-frequency conversion methods are employed to obtain the time-frequency characteristics of the incident and reflected signals. By performing time-frequency conversion on the incident and reflected signals, incident and reflected time-frequency domain signals can be obtained. These signals more intuitively reflect the dynamic changes of the signal as it propagates through the cable.

[0062] Step S5: Based on the cross-correlation function, the peak position of the cross-correlation function is determined by the incident time-frequency domain signal and the reflected time-frequency domain signal, and the signal propagation defect delay of the target cable is determined according to the peak position of the cross-correlation function.

[0063] The cross-correlation function measures the similarity between the incident and reflected time-frequency domain signals. By calculating the cross-correlation function, we can find the location of the highest similarity, i.e., the peak of the cross-correlation function. This location corresponds to the time delay of the reflected signal relative to the incident signal, i.e., the signal propagation defect delay.

[0064] Step S6: Determine the defect location of the target cable according to the signal propagation defect delay and the propagation speed of the incident signal.

[0065] The propagation speed of the incident signal in the cable is generally known and depends on the cable's material and structure. By measuring the signal propagation defect delay—the delay of the reflected signal relative to the incident signal—the distance between the defect and the incident signal stimulus point can be calculated.

[0066] It should be noted that, in the embodiment of the present application, a Gaussian envelope linear chirp signal is used as the initial incident signal for frequency domain reflection, and the signal characteristic parameters of the initial incident signal are optimized to obtain an incident signal, the target cable is excited by the incident signal, and a reflected signal is obtained at a preset measuring point of the target cable, and the incident signal and the reflected signal are time-frequency converted to obtain an incident time-frequency domain signal and a reflected time-frequency domain signal, and based on the cross-correlation function, the peak position of the cross-correlation function is determined by the incident time-frequency domain signal and the reflected time-frequency domain signal, and the signal propagation defect delay of the target cable is determined according to the peak position of the cross-correlation function, and the defect position of the target cable is determined according to the signal propagation defect delay and the propagation speed of the incident signal, thereby filtering out the interference of surrounding signals and improving the accuracy of cable defect positioning.

[0067] In some embodiments, the signal characteristic parameters include Gaussian envelope time domain parameters and chirp frequency.

[0068] The signal characteristic parameters of the initial incident signal are optimized to obtain the incident signal, including:

[0069] Step S201: maximizing the product of the Gaussian envelope time domain parameter and the chirp modulation frequency is taken as the optimization goal, and constraints are determined; wherein the constraints include distance resolution constraint, attenuation constraint, trade-off coefficient constraint and sampling rate constraint.

[0070] The relationship between the Gaussian envelope time domain parameters and the chirp modulation frequency can be expressed by the following formula:

[0071]

[0072]

[0073] Where B is the frequency bandwidth and T is the signal period.

[0074] The Gaussian envelope time-domain parameters and chirp frequency can be flexibly adjusted based on factors such as total cable length and equipment performance. However, the parameter values ​​are not infinite. For example, α should be large enough to shorten the signal period and minimize blind spots. However, it is worth noting that the selection of α is also constrained by the signal generator's sampling rate. If α is set too high, defects near the cable head may not be detected. Conversely, if α is too small, signal overlap may occur.

[0075] To reduce signal period and blind spots, α should be sufficiently high, but due to the relationship between the Gaussian envelope time-domain parameters and the chirp modulation frequency, β will be reduced. To achieve better TFDR, both α and β should be sufficiently high. Therefore, the product of α and β (α × β) is used to obtain a value that satisfies both low blind spots and good spatial resolution. Based on the maximum value of α × β, α and β are determined. That is, the optimization goal is to maximize the product of the Gaussian envelope time-domain parameters and the chirp modulation frequency, and the objective function is constructed:

[0076]

[0077] To accurately detect cable defects, the range resolution constraint ensures that the incident signal propagating through the cable has a certain range resolution. Range resolution refers to the minimum distance between two adjacent reflectors. In frequency domain reflectometry, range resolution is limited by the bandwidth and pulse width of the incident signal. A wider bandwidth and a narrower pulse width result in higher range resolution. Therefore, during the optimization process, a range resolution constraint is required to ensure that the incident signal has sufficient bandwidth and an appropriate pulse width to meet the range resolution requirements for cable defect location. A trade-off coefficient constraint is used to balance signal strength and interference rejection. In practical applications, higher signal strength and improved interference rejection are associated with more accurate defect detection. However, increased signal strength may reduce signal bandwidth, which in turn affects range resolution. Therefore, a trade-off coefficient constraint is required during the optimization process to achieve a balance between signal strength and interference rejection. The sampling rate constraint is determined by the performance of the signal generator. The sampling rate refers to the number of samples collected per second and determines the accuracy and frequency range of signal digitization. In frequency-domain reflectometry, the sampling rate must be high enough to capture the high-frequency components in both the incident and reflected signals, ensuring accurate defect location. Therefore, during the optimization process, sampling rate constraints must be considered to ensure that the frequency components of the incident signal are within the sampling rate range of the signal generator. In summary, by optimizing the Gaussian envelope time-domain parameters and chirp frequency, and imposing range resolution constraints, attenuation constraints, trade-off coefficient constraints, and sampling rate constraints during the optimization process, an incident signal with excellent performance can be obtained, thereby improving the accuracy and reliability of cable defect location.

[0078] Specifically, the distance resolution constraint is:

[0079]

[0080] Where v is the propagation velocity of the incident signal.

[0081] The decay constraint is:

[0082]

[0083] Where, is the frequency-dependent attenuation coefficient, L is the propagation length of the incident signal in the target cable, is the maximum allowable power loss.

[0084] Trade-off coefficient constraints:

[0085]

[0086] Where η is the trade-off coefficient, B e is the effective bandwidth, B i is the ideal bandwidth, is the minimum allowable trade-off coefficient, d is the distance resolution; where,

[0087]

[0088] Where, P tx is the transmission power, P min is the receiver sensitivity, and b is the attenuation coefficient.

[0089] The sampling rate constraint is:

[0090]

[0091] Where, f s is the sampling rate, and are the maximum Gaussian envelope time domain parameters and the maximum chirp modulation frequency, respectively, which are determined by the performance of the signal generator.

[0092] Step S202: Based on the constraints, the objective function corresponding to the optimization target is optimized and solved, and the optimal signal characteristic parameters are determined according to the optimal solution.

[0093] The optimization process can use a variety of optimization algorithms, such as genetic algorithms, particle swarm optimization, or gradient descent methods. These algorithms use iterative searches to find the parameter combination that makes the objective function reach the optimal value under the constraints.

[0094] In this paper, an appropriate optimization algorithm is selected, along with a reasonable number of iterations and search step size. Signal parameters α and β are determined by optimizing β × α, while satisfying constraints such as range resolution, attenuation, and trade-off coefficients. The objective function is solved using the sequential least squares algorithm in Python. By optimizing the objective function, an optimal set of Gaussian envelope time-domain parameters and chirp modulation frequency can be obtained.

[0095] Step S203: Update the initial incident signal according to the optimal signal characteristic parameters to obtain an incident signal.

[0096] The incident signal is obtained by substituting the optimal Gaussian envelope time domain parameters and chirp modulation frequency into the initial incident signal to update the signal.

[0097] In some embodiments, based on the frequency domain reflectometry, the target cable is stimulated by an incident signal, and a reflected signal is obtained at a preset measuring point of the target cable, which also includes:

[0098] Step S21 : determining the phase delay of the frequency component caused by the incident signal propagating in the target cable according to the phase coefficient of the incident signal and the propagation length of the incident signal in the target cable.

[0099] The phase coefficient of the incident signal is related to the material, structure and propagation environment of the cable, and it determines the rate of change of the phase of the signal when it propagates in the cable. The phase coefficient of the incident signal is:

[0100]

[0101] Among them, the phase delay of the frequency component caused by the incident signal propagating in the target cable is:

[0102]

[0103] Where, is the phase delay.

[0104] Step S22: Determine the propagation phase delay of the preset inverse filter according to the phase delay of the frequency component.

[0105] Among them, the inverse filter is designed, and the propagation phase delay of the inverse filter is determined according to the phase delay of the frequency component:

[0106]

[0107] Where H phase (f) is the propagation phase delay of the inverse filter.

[0108] Step S23: Perform Fourier transform on the incident signal to obtain an incident frequency domain signal.

[0109] The purpose of performing a Fourier transform on an incident signal is to convert it from the time domain to the frequency domain for further analysis and processing. The Fourier transform decomposes a signal into a superposition of sine or cosine waves of different frequencies. The Fourier transform yields a representation of the incident signal in the frequency domain, the incident frequency domain signal. This signal contains the amplitude and phase information of the incident signal at each frequency.

[0110] Step S24: Compensate the input radio frequency signal according to the propagation phase delay to obtain a compensated input radio frequency signal.

[0111] Among them, in order to compensate for the phase delay caused by the incident signal when it propagates in the cable and improve the signal quality and analysis accuracy, it is necessary to compensate the incident radio frequency signal according to the propagation phase delay of the inverse filter. The compensation process is to multiply the propagation phase delay of the inverse filter with the incident radio frequency signal, thereby adjusting the phase of the signal so that it is close to the phase when it propagates in an ideal lossless cable. Through this step, the compensated incident radio frequency signal can be obtained. The signal has more accurate phase information, which is helpful for subsequent signal processing and defect location analysis. The compensated incident radio frequency signal will be used for subsequent frequency domain reflection measurement. By performing time-frequency conversion and cross-correlation analysis with the reflected signal, the defect location in the cable can be determined. Specifically, the compensated incident radio frequency signal is:

[0112]

[0113] Where, is the incoming radio frequency signal, is the compensated input radio frequency signal.

[0114] Step S25: performing inverse Fourier transform on the compensated incident frequency domain signal to obtain an incident time domain signal; wherein the incident time domain signal is used to excite the target cable.

[0115] The purpose of performing an inverse Fourier transform on the compensated incident frequency domain signal is to convert the signal from the frequency domain back to the time domain for subsequent cable excitation and defect location measurement. The inverse Fourier transform is the process of converting a frequency domain signal into a time domain signal. It is the inverse operation of the Fourier transform. Through the inverse Fourier transform, a representation of the incident signal in the time domain, namely the incident time domain signal, can be obtained. This signal will be used to excite the target cable in step S3 and receive the reflected signal at the preset measuring point for subsequent defect location analysis. The incident time domain signal has accurate phase and amplitude information, which can ensure good performance when propagating in the cable, thereby improving the accuracy and reliability of defect location.

[0116] In some embodiments, performing time-frequency conversion on the incident signal and the reflected signal to obtain the incident time-frequency domain signal and the reflected time-frequency domain signal respectively includes:

[0117] By introducing the pseudo Wigner-Ville distribution of the Gaussian rectangular window function, the incident signal and the reflected signal are transformed into time-frequency domain signals to obtain the incident time-frequency domain signals and the reflected time-frequency domain signals.

[0118] Among them, the incident signal and the reflected signal need to be time-frequency converted to obtain time domain information and frequency domain information at the same time. However, the traditional Wigner-Ville distribution used for time-frequency conversion will cause cross-term interference problems of multi-component signals. Therefore, a cross-term suppression method is needed. Since the calculation process of time-frequency conversion is very time-consuming, the cross-term suppression method of the Wigner-Ville distribution should not be too complicated. Therefore, the embodiment of the present application adopts a pseudo-Wigner-Ville distribution as a time-frequency conversion method to suppress the cross-term caused by the multi-component signal, perform time-frequency conversion on the incident signal, and obtain an incident time-frequency domain signal, which can be expressed as follows:

[0119]

[0120] Where, is the incident time-frequency domain signal, is the Gaussian rectangular window function, is the Hilbert transform of the incident signal, is the time-integrated variable, 、 The incident signal moves forward on the time axis and move backward , is the complex conjugate of the incident signal.

[0121] The Gaussian rectangular window function does not increase the variance of the pseudo-Wigner-Ville distribution, so the computational effort required for time-frequency conversion remains largely unchanged. For the pseudo-Wigner-Ville distribution, the key to avoiding cross-term interference is the window function. The Gaussian rectangular window function is defined as follows:

[0122]

[0123] Where δ represents the standard deviation, which is used to control the window width, and it can vary according to the Gaussian envelope of the incident signal.

[0124] In some embodiments, based on the cross-correlation function, determining the peak position of the cross-correlation function using the incident time-frequency domain signal and the reflected time-frequency domain signal, and determining the signal propagation defect delay of the target cable according to the peak position of the cross-correlation function includes:

[0125] Step S501 : Calculate the similarity between the incident time-frequency domain signal and the reflected time-frequency domain signal based on the cross-correlation function, and determine the position with the highest similarity as the peak position of the cross-correlation function.

[0126] The time-frequency distribution of the defect signal is not obvious compared with the incident signal and the signal reflected from the cable end. Therefore, the location of the defect should be extracted by the following cross-correlation function, which is expressed as:

[0127]

[0128] Where, is the similarity, is the reflected time-frequency domain signal after the impulse response.

[0129] Among them, the reflected time-frequency signal after the impulse response is It is expressed as follows:

[0130]

[0131] Where, is the reflected time-frequency domain signal, is the impulse response of the cable. It is expressed as follows:

[0132]

[0133] Where, represents the reflection coefficient of the i-th defect, represents the round-trip delay of the signal to the i-th defect, b and d i They represent the attenuation coefficient and the distance resolution of the i-th defect respectively; p(t) represents the dispersion effect of the cable, usually the frequency domain phase response The inverse transform of .

[0134] Step S502: Determine the signal propagation defect delay according to the peak position of the cross-correlation function and the sampling interval period.

[0135] It can be understood that the peak position of the cross-correlation function corresponds to the point of maximum similarity between the defect signal and the incident signal, which reflects the location of the defect in the cable. The sampling interval is the time interval between signal sampling and determines the temporal resolution. By multiplying the peak position of the cross-correlation function by the sampling interval, the propagation delay of the defect signal relative to the incident signal can be calculated. The signal propagation delay reflects the time it takes for the signal to propagate through the cable to the defect location and reflect back, thereby determining the specific location of the defect in the cable.

[0136] In some embodiments, determining the defect location of the target cable based on the signal propagation defect delay and the propagation speed of the incident signal includes:

[0137] The distance between the defect on the target cable and the excitation point corresponding to the incident signal is determined based on the product of the signal propagation defect delay and the propagation speed of the incident signal; where the distance is the defect location of the target cable.

[0138] The distance between the defect on the target cable and the excitation point corresponding to the incident signal is:

[0139] Where, is the distance between the defect on the target cable and the excitation point corresponding to the incident signal, is the signal propagation defect delay.

[0140] Based on the same inventive concept, an embodiment of the present application further provides a cable defect locating system for implementing the above-mentioned cable defect locating method.

[0141] The solution provided by the system to solve the problem is similar to the solution described in the above method. Therefore, the specific limitations in one or more cable defect location system embodiments provided below can refer to the limitations on the cable defect location method above and will not be repeated here.

[0142] like Figure 3 As shown, an embodiment of the present application provides a cable defect location system, comprising:

[0143] An incident signal determination module 100 is configured to determine an initial incident signal for frequency domain reflection based on a Gaussian envelope linear chirp signal;

[0144] An incident signal optimization module 200 is used to optimize the signal characteristic parameters of the initial incident signal to obtain an incident signal;

[0145] The signal excitation module 300 is used to excite the target cable with an incident signal based on the frequency domain reflectometry method, and obtain a reflected signal at a preset measuring point of the target cable;

[0146] The time-frequency conversion module 400 is used to perform time-frequency conversion on the incident signal and the reflected signal to obtain an incident time-frequency domain signal and a reflected time-frequency domain signal;

[0147] The time delay determination module 500 is used to determine the peak position of the cross-correlation function based on the incident time-frequency domain signal and the reflected time-frequency domain signal, and determine the signal propagation defect delay of the target cable according to the peak position of the cross-correlation function;

[0148] The defect location module 600 is used to determine the defect location of the target cable according to the signal propagation defect delay and the propagation speed of the incident signal.

[0149] In some embodiments, the signal characteristic parameters include Gaussian envelope time domain parameters and chirp modulation frequency;

[0150] The incident signal optimization module 200 is used to:

[0151] The optimization objective is to maximize the product of the Gaussian envelope time domain parameter and the chirp modulation frequency, and determine the constraints; the constraints include range resolution constraint, attenuation constraint, trade-off coefficient constraint, and sampling rate constraint;

[0152] Based on the constraints, the objective function corresponding to the optimization goal is optimized and solved, and the optimal signal characteristic parameters are determined according to the optimal solution;

[0153] The initial incident signal is updated according to the optimal signal characteristic parameters to obtain an incident signal.

[0154] In some embodiments, the system further includes a signal compensation module configured to:

[0155] determining a phase delay of a frequency component caused by the incident signal propagating in the target cable according to a phase coefficient of the incident signal and a propagation length of the incident signal in the target cable;

[0156] determining a propagation phase delay of a preset inverse filter according to the phase delay of the frequency component;

[0157] Perform Fourier transform on the incident signal to obtain the incident frequency domain signal;

[0158] Compensating the input radio frequency signal according to the propagation phase delay to obtain a compensated input radio frequency signal;

[0159] The compensated incident frequency domain signal is subjected to inverse Fourier transform to obtain an incident time domain signal; wherein the incident time domain signal is used to excite the target cable.

[0160] In some embodiments, the time-frequency conversion module 400 is configured to:

[0161] By introducing the pseudo Wigner-Ville distribution of the Gaussian rectangular window function, the incident signal and the reflected signal are transformed into time-frequency domain signals to obtain the incident time-frequency domain signals and the reflected time-frequency domain signals.

[0162] In some embodiments, the delay determination module 500 is configured to:

[0163] Based on the cross-correlation function, the similarity between the incident time-frequency domain signal and the reflected time-frequency domain signal is calculated, and the position with the highest similarity is determined as the peak position of the cross-correlation function;

[0164] The signal propagation defect delay is determined based on the peak position of the cross-correlation function and the sampling interval period.

[0165] In some embodiments, the defect localization module 600 is configured to:

[0166] The distance between the defect on the target cable and the excitation point corresponding to the incident signal is determined based on the product of the signal propagation defect delay and the propagation speed of the incident signal; where the distance is the defect location of the target cable.

[0167] like Figure 4 As shown, an embodiment of the present application provides an electronic device, the electronic device 10 includes a memory 20 and a processor 30, the memory 20 stores a computer program, and when the computer program is executed by the processor 30, the processor 30 performs the steps of the cable defect location method in the above embodiment.

[0168] An embodiment of the present application provides a computer-readable storage medium having a computer program stored thereon. When the computer program is executed, the steps of the cable defect location method in the above embodiment are implemented.

[0169] An embodiment of the present application provides a computer program product, which includes a computer program stored on a non-transitory computer-readable storage medium, and the computer program includes program instructions. When the program instructions are executed by a computer, the computer executes the steps of the cable defect location method in the above embodiment.

[0170] Those skilled in the art will clearly understand that, for the convenience and brevity of description, the specific working processes of the above-described systems, electronic devices, computer storage media, and computer program products can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0171] It should be noted that the terms "including" and "having" and any variations thereof in the specification and claims of the present invention and the above-mentioned drawings are intended to cover non-exclusive inclusions. For example, a process, method, system, product or apparatus comprising a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or are inherent to these processes, methods, products or apparatuses.

[0172] It should be understood that, although the various steps in the flowcharts involved in the various embodiments described above are displayed in sequence according to the instructions of the arrows, these steps are not necessarily executed in sequence in the order indicated by the arrows. Unless otherwise specified herein, there is no strict order restriction on the execution of these steps, and these steps can be executed in other orders. Moreover, at least a portion of the steps in the flowcharts involved in the various embodiments described above can include multiple steps or multiple stages, and these steps or stages are not necessarily executed and completed at the same time, but can be executed at different times, and the execution order of these steps or stages is not necessarily to be carried out in sequence, but can be executed in turn or alternately with other steps or at least a portion of steps or stages in other steps.

[0173] In the several embodiments provided by the present invention, it should be understood that the disclosed systems, electronic devices, computer storage media, computer program products and methods can be implemented in other ways. For example, the device embodiments described above are merely schematic. For example, the division of the units is merely a logical function division. In actual implementation, there may be other division methods, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be an indirect coupling or communication connection through some interfaces, devices or units, which can be electrical, mechanical or other forms.

[0174] The units described as separate components may or may not be physically separate, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed across multiple network units. Some or all of these units may be selected to achieve the purpose of this embodiment according to actual needs.

[0175] In addition, the functional units in the various embodiments of the present invention may be integrated into a single processing unit, each unit may exist physically separately, or two or more units may be integrated into a single unit. The aforementioned integrated units may be implemented in the form of hardware or software functional units.

[0176] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the portion that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions for executing all or part of the steps of the method described in each embodiment of the present invention via a computer device (which can be a personal computer, server, or network device, etc.). The aforementioned storage medium includes various media that can store program code, such as a USB flash drive, a mobile hard drive, a read-only memory (ROM), a random access memory (RAM), a magnetic disk, or an optical disk.

[0177] 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 aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the various embodiments of the present invention.

Claims

1. A cable defect location method, characterized in that: include: Determining an initial incident signal for frequency domain reflection based on a Gaussian envelope linear chirp signal; Optimizing the signal characteristic parameters of the initial incident signal to obtain an incident signal; Based on the frequency domain reflection method, the target cable is excited by the incident signal, and a reflected signal is obtained at a preset measuring point of the target cable; Performing time-frequency conversion on the incident signal and the reflected signal respectively to obtain an incident time-frequency domain signal and a reflected time-frequency domain signal; Based on the cross-correlation function, determining the peak position of the cross-correlation function through the incident time-frequency domain signal and the reflected time-frequency domain signal, and determining the signal propagation defect delay of the target cable according to the peak position of the cross-correlation function; The defect position of the target cable is determined according to the signal propagation defect delay and the propagation speed of the incident signal.

2. The cable defect location method according to claim 1, characterized in that: The signal characteristic parameters include Gaussian envelope time domain parameters and chirp modulation frequency; The optimizing the signal characteristic parameters of the initial incident signal to obtain the incident signal includes: Taking maximizing the product of the Gaussian envelope time domain parameter and the chirp modulation frequency as the optimization goal, and determining constraint conditions; wherein the constraint conditions include a range resolution constraint, an attenuation constraint, a trade-off coefficient constraint, and a sampling rate constraint; Based on the constraints, an objective function corresponding to the optimization goal is optimized and solved, and optimal signal characteristic parameters are determined according to the optimal solution; The initial incident signal is updated according to the optimal signal characteristic parameter to obtain the incident signal.

3. The cable defect location method according to claim 1, characterized in that: The method, based on the frequency domain reflection method, excites the target cable with the incident signal and obtains a reflected signal at a preset measuring point of the target cable, and also includes: determining a phase delay of a frequency component caused by the incident signal propagating in the target cable based on a phase coefficient of the incident signal and a propagation length of the incident signal in the target cable; Determining a propagation phase delay of a preset inverse filter according to the phase delay of the frequency component; Performing Fourier transform on the incident signal to obtain an incident frequency domain signal; Compensating the input radio frequency signal according to the propagation phase delay to obtain a compensated input radio frequency signal; An inverse Fourier transform is performed on the compensated incident frequency domain signal to obtain an incident time domain signal; wherein the incident time domain signal is used to excite the target cable.

4. The cable defect location method according to claim 1, characterized in that: The performing time-frequency conversion on the incident signal and the reflected signal respectively to obtain an incident time-frequency domain signal and a reflected time-frequency domain signal includes: By introducing a pseudo Wigner-Ville distribution of a Gaussian rectangular window function, time-frequency conversion is performed on the incident signal and the reflected signal to obtain the incident time-frequency domain signal and the reflected time-frequency domain signal.

5. The cable defect location method according to claim 1, characterized in that: The method of determining a peak position of the cross-correlation function based on the incident time-frequency domain signal and the reflected time-frequency domain signal, and determining the signal propagation defect delay of the target cable according to the peak position of the cross-correlation function, includes: Calculating the similarity between the incident time-frequency domain signal and the reflected time-frequency domain signal based on the cross-correlation function, and determining the position with the highest similarity as the peak position of the cross-correlation function; The signal propagation defect delay is determined according to the peak position of the cross-correlation function and the sampling interval period.

6. The cable defect location method according to claim 1, characterized in that: The determining the defect position of the target cable according to the signal propagation defect delay and the propagation speed of the incident signal includes: The distance between the defect on the target cable and the excitation point corresponding to the incident signal is determined based on the product of the signal propagation defect delay and the propagation speed of the incident signal; wherein the distance is the defect position of the target cable.

7. A cable defect location system, characterized in that: include: An incident signal determination module, configured to determine an initial incident signal for frequency domain reflection based on a Gaussian envelope linear chirp signal; An incident signal optimization module, configured to optimize the signal characteristic parameters of the initial incident signal to obtain an incident signal; A signal excitation module is used to excite the target cable with the incident signal based on the frequency domain reflection method, and obtain a reflected signal at a preset measuring point of the target cable; A time-frequency conversion module, configured to perform time-frequency conversion on the incident signal and the reflected signal to obtain an incident time-frequency domain signal and a reflected time-frequency domain signal; a time delay determination module, configured to determine a peak position of the cross-correlation function based on the incident time-frequency domain signal and the reflected time-frequency domain signal, and determine a signal propagation defect time delay of the target cable according to the peak position of the cross-correlation function; The defect location module is configured to determine the defect location of the target cable according to the signal propagation defect delay and the propagation speed of the incident signal.

8. An electronic device, characterized in that: The electronic device includes a memory and a processor, wherein a computer program is stored in the memory. When the computer program is executed by the processor, the processor executes the steps of the cable defect location method according to any one of claims 1 to 6.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed, the steps of the cable defect locating method according to any one of claims 1 to 6 are implemented.

10. A computer program product, characterized in that The computer program product comprises a computer program stored on a non-transitory computer-readable storage medium, wherein the computer program comprises program instructions, wherein when the program instructions are executed by a computer, the computer is caused to perform the steps of the cable defect location method according to any one of claims 1 to 6.

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