Cable defect detection method and device based on time-frequency domain reflection and medium

Abstract

The embodiment of the invention discloses a cable defect detection method and device based on time-frequency domain reflection and a medium, and relates to the technical field of signal processing, and the method comprises the steps: carrying out the parameter detection of a target detection cable through a preset multi-component incident signal, obtaining a target reflection signal, and carrying out the detection of a cable defect based on the target reflection signal and the multi-component incident signal. Determining a target transmission function corresponding to the target detection cable; according to the target transmission function, fitting a target cable attenuation curve corresponding to the target detection cable to determine a loss function corresponding to the target detection cable; and performing iterative optimization on a preset detection incident signal by using the loss function, and determining an optimized optimization incident signal after optimization, so as to perform defect detection on the target detection cable through the optimization incident signal. Compared with a traditional time-frequency incident signal, the attenuation characteristic curve is fitted by detecting the parameters of the cable, and the parameters are adaptively adjusted based on the attenuation curve, so that the universality of time-frequency domain algorithm detection is improved.

Description

Technical Field

[0001] This specification relates to the field of signal processing technology, and in particular to a cable defect detection method, device, and medium based on time-frequency domain reflection. Background Art

[0002] With the acceleration of urbanization, urban loads and electricity consumption are characterized by high density and rapid growth. To meet cities' demands for reliable and secure transmission systems, while also addressing urban spatial planning constraints, power cables are gradually replacing overhead lines as the primary method of power transmission. However, because cables are laid in trenches, conduits, tunnels, or even buried directly underground, the laying environment and usage can significantly impact their lifespan. Furthermore, improper handling during cable manufacturing or installation can lead to localized defects in cables susceptible to the effects of temperature, electricity, mechanical forces, moisture, oil, organic compounds, alkalis, acids, and microorganisms, leading to failures.

[0003] In time-frequency domain reflectometry (TFDR) technology, the design of the incident signal directly affects the accuracy and anti-interference capability of defect detection. Traditional traveling wave reflectometry uses fixed-frequency pulse signals, such as step pulses or Gaussian pulses, which cannot adapt to high-frequency attenuation scenarios. Signal energy loss is severe in long cables, resulting in inaccurate defect location. Linear frequency modulation signals improve frequency domain resolution through frequency scanning, but their bandwidth is fixed and cannot adapt to different cable lengths or attenuation conditions. For weak cable defects, the effective signal may be submerged in noise. Pseudo-random bit sequence (PRBS) modulation signals use pseudo-random sequences (such as m-sequences) to improve noise resistance, but their uneven frequency domain energy distribution can result in low signal-to-noise ratios in some frequency bands. Furthermore, they involve complex correlation operations and have poor real-time performance.

[0004] Therefore, when using time-frequency domain reflection technology to detect cable defects, fixed incident signal parameters are used, which cannot adapt to the defect detection requirements of different cables, resulting in the need to improve the defect positioning accuracy during the cable detection process. Summary of the Invention

[0005] One or more embodiments of this specification provide a cable defect detection method, device, and medium based on time-frequency domain reflection, which are used to solve the following technical problems: when using time-frequency domain reflection technology to detect cable defects, fixed incident signal parameters are used, which cannot adapt to the defect detection requirements of different cables, resulting in the defect positioning accuracy during the cable detection process needing to be improved.

[0006] One or more embodiments of this specification adopt the following technical solutions: One or more embodiments of the present specification provide a cable defect detection method based on time-frequency domain reflection, the method comprising: performing parameter detection on a target detection cable through a preset multi-component incident signal to obtain a target reflection signal, and determining a target transmission function corresponding to the target detection cable based on the target reflection signal and the multi-component incident signal; fitting a target cable attenuation curve corresponding to the target detection cable according to the target transmission function to determine a loss function corresponding to the target detection cable; and iteratively optimizing a preset detection incident signal using the loss function to determine an optimized incident signal after optimization, so as to perform defect detection on the target detection cable through the optimized incident signal.

[0007] One or more embodiments of this specification provide a cable defect detection device based on time-frequency domain reflection, including: at least one processor; and, a memory communicatively connected to the at least one processor; wherein, The memory stores instructions that can be executed by the at least one processor. The instructions are executed by the at least one processor to enable the at least one processor to perform the above method.

[0008] One or more embodiments of this specification provide a non-volatile computer storage medium storing computer-executable instructions, wherein the computer-executable instructions are configured to execute the above method.

[0009] At least one of the above-mentioned technical solutions adopted in the embodiments of this specification can achieve the following beneficial effects: through the technical solutions of the embodiments of this specification, compared with traditional time-frequency incident signals, by defining a loss function, the center frequency and bandwidth of the signal under the high-frequency attenuation phenomenon and spatial resolution are weighed and selected, and the highest resolution is obtained while satisfying the maximum attenuation of the signal, which is beneficial to improving the accuracy of cable defect positioning; after obtaining the target transmission function based on the multi-component incident signal, the center frequency and bandwidth parameters are dynamically generated based on the fitting results of the target cable attenuation model, so that the incident signal intelligently avoids the high-frequency attenuation area and focuses on the low-loss passband, breaking through the problem of attenuation failure of fixed parameter signals in long-distance cables; compared with traditional time-frequency incident signals, the attenuation characteristics can be fitted by extracting the material parameters and geometric parameters of cables of different lengths and types, and the parameters are adaptively adjusted based on this, which is beneficial to improving the universality of time-frequency domain algorithm detection; adaptive matching of the incident signal and cable characteristics is achieved without human intervention, effectively improving the defect positioning accuracy. BRIEF DESCRIPTION OF THE DRAWINGS

[0010] In order to more clearly illustrate the embodiments of this specification or the technical solutions in the prior art, the following briefly introduces the drawings required for the embodiments or the description of the prior art. Obviously, the drawings described below are only some of the embodiments described in this specification. For those skilled in the art, other drawings can be obtained based on these drawings without inventive work. In the drawings: Figure 1 A schematic diagram of a flow chart of a cable defect detection method based on time-frequency domain reflection provided in an embodiment of this specification; Figure 2 A schematic diagram of a cable attenuation characteristic curve provided in an embodiment of this specification; Figure 3 A schematic diagram of a time domain waveform of an incident signal provided in an embodiment of this specification; Figure 4 A schematic diagram of a frequency domain waveform of an incident signal provided in an embodiment of this specification; Figure 5 A schematic diagram of a defect location curve provided in an embodiment of this specification; Figure 6 A schematic structural diagram of a cable defect detection device based on time-frequency domain reflection provided in an embodiment of this specification. DETAILED DESCRIPTION

[0011] To help those skilled in the art better understand the technical solutions in this specification, the following will provide a clear and complete description of the technical solutions in the embodiments of this specification, in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of this specification, not all of them. All other embodiments obtained by those skilled in the art based on the embodiments of this specification without creative work should fall within the scope of protection of this specification.

[0012] The embodiments of this specification provide a cable defect detection method based on time-frequency domain reflection. It should be noted that the execution subject in the embodiments of this specification can be a server or any device with data processing capabilities. Figure 1 A schematic diagram of a cable defect detection method based on time-frequency domain reflection is provided in the embodiment of this specification, such as Figure 1 As shown, it mainly includes the following steps: Step S101 : performing parameter detection on a target detection cable using a preset multi-component incident signal to obtain a target reflection signal, and determining a target transmission function corresponding to the target detection cable based on the target reflection signal and the multi-component incident signal.

[0013] The incident signal used by the time-frequency domain reflectometry (TFDR) is a linear frequency-adjustable signal with a Gaussian envelope, which has both time domain and frequency domain characteristics. The expression of the incident signal is for ,in is the amplitude coefficient, used to change The magnitude of It is the time domain width coefficient, which determines the duration of the signal. It is the frequency domain width coefficient, which determines the frequency domain bandwidth of the signal. Used to decide The frequency center of Used to decide Time center. The frequency domain expression of the signal obtained by Fourier transform is as follows: 、 .

[0014] The duration T and frequency bandwidth B of the signal are:

[0015] From the above, we can see that TFDR can achieve arbitrary changes in the incident signal duration and frequency domain bandwidth through parameter adjustment to obtain the optimal inspection effect for different research objects.

[0016] Before performing parameter detection on the target detection cable using a preset multi-component incident signal, the method further includes: setting a multi-component incident signal, wherein the multi-component incident signal includes Gaussian pulse components of multiple frequency components, a first frequency component being used to obtain cable length and conductor cross-sectional area parameters, a second frequency component being used to obtain insulating material dielectric constant parameters, and a third frequency component being used to obtain insulating material loss tangent parameters. Based on the target reflection signal and the multi-component incident signal, a target transmission function corresponding to the target detection cable is determined, specifically comprising: performing a Fourier transform on the target reflection signal to determine a reflected frequency domain response signal, and performing a Fourier transform on the multi-component incident signal to obtain an incident frequency domain response signal; and determining the target transmission function corresponding to the target detection cable based on the ratio of the reflected frequency domain response signal to the incident frequency domain response signal.

[0017] In one embodiment of the present specification, a broadband, multi-parameter sensitive, multi-component incident signal is injected into one end of the cable. and calculate its frequency domain response by Fourier transform .

[0018] Among them, the first frequency component Used to capture the total length l of the cable and the cross-sectional area S of the conductor. The 1MHz low-frequency signal has a large penetration depth and can capture the overall conductor characteristics. The 10MHz intermediate-frequency signal is sensitive to the dielectric properties of the insulation layer, so the second frequency component Used to capture the dielectric constant ϵ of cable insulation materials; 30MHz high-frequency signal excitation polarization loss, the third frequency component Used to capture the cable insulation loss tangent tanδ, The pulse width is , is the phase shift constant, which can be set to 0 or set according to needs; is the time center corresponding to the multi-component incident signal, is the amplitude coefficient, which can be set to 1. The reflected signal is recorded at the end where the multi-component incident signal is injected. and obtain the frequency domain response through Fourier transform (FFT) , and calculate the transfer function ,in, .

[0019] Step S102 : fitting a target cable attenuation curve corresponding to the target detection cable according to the target transmission function to determine a loss function corresponding to the target detection cable.

[0020] According to the target transmission function, a target cable attenuation curve corresponding to the target detection cable is fitted to determine a loss function corresponding to the target detection cable, specifically comprising: according to the target transmission function, a target cable attenuation model corresponding to the target detection cable is fitted, wherein the target cable attenuation model includes any one or more of a conductor resistance loss term, an insulation dielectric loss term, and a high-frequency polarization loss term; and based on the target cable attenuation model, a loss function corresponding to the target detection cable is defined.

[0021] In one embodiment of the present specification, based on the transfer function Fitting Cable Attenuation Model in 、 、 , and get the attenuation characteristics. Among them, the expression of the cable attenuation model is , describes the attenuation of the signal for every meter it travels in the cable (in decibels per meter), and the attenuation varies with frequency f. Corresponding to the conductor resistance loss term, this coefficient is related to the length l and the conductor cross-sectional area S, It represents the conductor resistance loss, which increases with the square root of frequency due to the skin effect; Corresponding to the insulation dielectric loss term, the dielectric constant ϵ of the cable insulation material is associated, The dielectric loss of insulation is proportional to the frequency. Corresponding to the high-frequency polarization loss term, the associated cable insulation loss tangent tanδ is: It is high-frequency polarization loss. The higher the frequency, the more serious the polarization lag of the insulating material molecules.

[0022] In addition, the cable attenuation model is established With the transfer function The relationship between , transfer function Indicates the transmission capacity of the cable for signals of different frequencies. It takes the natural logarithm of the modulus value, which is essentially the attenuation decibel value of the signal amplitude. Refers to the length of the round trip path of the signal, which is incident on the defect point and then reflected back to the head end. The total length is twice the cable length. Using the transmission function measured in the previous steps, the actual attenuation data corresponding to this cable is calculated through the relationship between the cable attenuation model and the transmission function. The cable attenuation model is adjusted according to the actual attenuation data. in 、 、 Perform fitting and solving to determine the target cable attenuation model corresponding to this cable.

[0023] The above technical solution achieves a breakthrough in cable defect detection capabilities through the collaborative dual formulas of parameterized attenuation characteristic modeling and test inversion calculation. The parameterized attenuation model decomposes the complex frequency-varying attenuation mechanism into three independent terms with clear physical meanings: conductor loss, insulation dielectric loss, and high-frequency polarization loss. This gives the model strong interpretability and significantly compresses the data dimension. Secondly, the attenuation inversion calculation based on the transfer function is directly linked to the actual measurement data, effectively overcoming theoretical model errors and environmental interference, amplifying weak defect characteristics through logarithmic transformation, and significantly improving the signal-to-noise ratio and defect sensitivity. The combination of the two forms a closed-loop control of measurement-modeling-optimization. On the one hand, it guides the generation of incident signals with concentrated frequency band energy and optimal anti-attenuation capability, ensuring the effective capture of weak reflected signals over long distances. On the other hand, it accurately locates the defect position and type through attenuation anomalies, which can solve the core pain points of traditional methods such as poor adaptability, weak noise resistance, and long-distance failure caused by fixed signal parameters, and achieves high-precision and robust defect positioning for all types of cables without the need for prior knowledge.

[0024] Based on the target cable attenuation model, a loss function is determined, specifically including: determining the average attenuation rate of the target detection cable within a preset frequency band according to the target cable attenuation model, so as to determine the cumulative attenuation parameter corresponding to the target detection cable through the cable length corresponding to the target detection cable obtained in advance; determining the attenuation constraint item based on the cumulative attenuation parameter corresponding to the target detection cable and a preset maximum attenuation threshold; determining the trade-off coefficient corresponding to the attenuation constraint item through the cable length and a preset reference cable length threshold, so as to determine the loss function corresponding to the target detection cable based on the attenuation constraint item, the trade-off coefficient and a preset signal-to-noise ratio.

[0025] In one embodiment of this specification, the loss function is defined as: ,in, ; For the current and The corresponding signal-to-noise ratio, is the center frequency of the incident signal, B is the bandwidth of the incident signal, l is the cable length, For cable in band The average attenuation rate under the condition of , in dB / m, is a trade-off coefficient used to balance the signal-to-noise ratio and attenuation constraints, The maximum allowable attenuation is usually set to 20dB. The SNR is an optimization goal. The higher the SNR, the easier it is to identify defect reflection signals. The negative sign indicates that the loss function needs to be minimized, which is equivalent to maximizing the SNR. A higher SNR leads to more accurate defect detection. However, simply pursuing SNR can lead to problems. For example, selecting a high frequency band may improve resolution, but the signal may be attenuated and unable to travel far. Enforcing attenuation not to exceed the physical limit is equivalent to triggering the penalty only when the attenuation exceeds the limit. λ can be adjusted according to the cable type. It is used to represent the total attenuation of the signal during the entire round trip in the cable. The optimization goal is to find smallest and B; prioritize improving SNR, but if the attenuation of a certain frequency band exceeds the standard, the constraint term generates a positive penalty, forcing the optimizer to avoid this frequency band.

[0026] When determining the trade-off coefficient corresponding to the attenuation constraint term based on the cable length and a preset reference cable length threshold, the reference cable length threshold can be set to 10 km. This length refers to the length at which significant attenuation occurs when the cable length reaches 10 km in practical experience. Therefore, the value of the trade-off coefficient can be determined by the relationship between the cable length and the reference cable length threshold. Generally, when the cable length is greater than the reference cable length threshold, the value can be within the range of [0.5, 1]. When the cable length is not greater than the reference cable length threshold, the value can be within the range of (0, 0.5).

[0027] Through the above technical solution, the loss function realizes the adaptive optimization of the incident signal parameters through the dynamic balance mechanism of the signal-to-noise ratio term and the attenuation constraint term. The signal-to-noise ratio term directly quantifies the effective signal strength of the detection system to ensure the identifiability of the defect reflection wave; the attenuation constraint term intelligently avoids the high attenuation frequency band with a conditional penalty mechanism to prevent excessive dissipation of signal energy during cable transmission; through the collaborative iteration of the gradient descent algorithm, under the premise of strictly meeting the physical limitations of cable attenuation, the center frequency and bandwidth are driven to automatically converge to the working range where the signal-to-noise ratio is maximized; the dynamic optimization mechanism breaks through the inherent defects of traditional fixed parameter signals, significantly improves the adaptability to changes in cable length, differences in material properties and environmental interference, and can maintain high spatial resolution and strong noise resistance under various complex working conditions, realizing the precise positioning of weak defects over long distances.

[0028] Step S103 , iteratively optimizing the preset detection incident signal using the loss function, and determining an optimized incident signal after optimization, so as to perform defect detection on the target detection cable through the optimized incident signal.

[0029] The loss function is used to iteratively optimize the preset detection incident signal to determine the optimized optimized incident signal, specifically including: iteratively optimizing the center frequency and bandwidth of the detection incident signal through the gradient descent method and the loss function to determine the optimized target center frequency and target bandwidth; determining the duration constraint according to the target bandwidth and the cable length parameter of the target detection cable obtained in advance, and determining the optimized duration corresponding to the target detection cable based on the duration constraint; generating a linear frequency modulation incident signal with a Gaussian envelope based on the target center frequency, the target bandwidth and the optimized duration to determine the optimized incident signal.

[0030] Specifically, the center frequency and bandwidth of the detected incident signal are iteratively optimized through the gradient descent method and the loss function, and the optimized target center frequency and target bandwidth are determined, specifically including: iteratively optimizing the center frequency and bandwidth of the detected incident signal through the gradient descent method, and calculating the partial derivatives of the loss function with respect to the center frequency and bandwidth respectively in each iteration process; setting the disturbance frequency and disturbance bandwidth corresponding to the center frequency and bandwidth, and calculating the signal-to-noise ratio change in the loss function through the disturbance frequency and the disturbance bandwidth, and when the preset convergence condition is met, determining the optimized target center frequency and target bandwidth, wherein the convergence condition includes that the loss function change in multiple iterations is not greater than a preset threshold or reaches a preset maximum number of iterations.

[0031] In one embodiment of this specification, the gradient descent is initialized first, and the optimization starting point and termination conditions are set to avoid random search. and The initial value of the clock frequency can be set to 10 MHz, and the learning rate can be set. and the maximum number of iterations , for example, set the learning rate to 0.5 and the maximum number of iterations to 100. Calculate the gradient, and in each iteration, calculate the loss function for and Partial derivatives of : and Through small perturbations and calculate changes, and ;like , then the second part is set to 0. Otherwise: 、 ; Update the center frequency according to the above iterative process and bandwidth : and , perform convergence judgment during the iteration process, when When , or, when the maximum number of iterations is reached, it stops, where, Used to indicate the change in loss function, preset threshold When the convergence condition is met, the center frequency and bandwidth obtained at this time are determined as the optimal center frequency of the incident signal. and optimal bandwidth , that is, the target center frequency and target bandwidth.

[0032] Through the above technical solution, the gradient descent optimization process realizes the adaptive optimization of the incident signal parameters through a mathematical iteration mechanism. The initialization stage sets a reasonable search starting point to avoid random divergence; the gradient calculation stage quantifies the sensitivity of the center frequency and bandwidth adjustment to the signal-to-noise ratio and attenuation constraints with differential approximation, accurately guiding the optimization direction; the parameter update stage dynamically adjusts the frequency band along the steepest descent path of the loss function, while avoiding high attenuation areas and improving the effective signal strength; the constraint processing stage forces the bandwidth to meet the hardware performance boundaries and time-frequency resolution limits to ensure the feasibility of the scheme engineering; the convergence judgment process automatically terminates the iteration based on the gradient norm threshold, achieving the optimal balance between solution accuracy and computational efficiency; the traditional trial-and-error process that relies on experience is transformed into a closed mathematical optimization, realizing intelligent frequency band design without human intervention, and can still stably output signal parameters that take into account both signal-to-noise ratio and resolution in harsh attenuation environments.

[0033] The duration constraint is determined based on the target bandwidth and the pre-acquired cable length parameters of the target detection cable, specifically including: determining the defect delay constraint based on the cable length parameters and the pre-acquired signal propagation speed; determining the product constraint corresponding to the duration based on the target bandwidth, and determining the corresponding device performance constraint through the pre-acquired minimum pulse width of the signal generator; and determining the duration constraint based on the defect delay constraint, the product constraint, and the device performance constraint.

[0034] In one embodiment of this specification, the incident signal duration T is dynamically determined based on the target bandwidth B output by gradient descent optimization and the pre-acquired cable length l through three physical constraints. The first is the defect delay constraint. It should be noted that the delay constraint essentially prevents the signal width from overlapping multiple defect reflection waves. Using the cable length and the signal propagation velocity v pre-determined from the cable dielectric properties, the time domain upper limit corresponding to 2l is calculated, that is, , to avoid overlapping of adjacent defect echoes. The second is the product constraint. The product constraint maintains the physical limit of the signal time-width-bandwidth. Based on the target bandwidth B, the time-frequency uncertainty principle is used to force , to prevent artificial compression of pulse width resulting in bandwidth exceeding the limit; the device performance constraint is the minimum pulse width calibrated by the signal generator , set the physically achievable lower limit , to avoid the design value exceeding the equipment generation capacity. According to the defect delay constraint, the product constraint and the device performance constraint, the duration constraint is determined to be the intersection of the three: ,in The maximum allowable duration of the system is determined by the hardware architecture of the signal acquisition system. It is the time resource boundary of the signal acquisition system and is determined by the sampling window, storage depth and real-time processing capability of the specific equipment. Its introduction ensures the unity of the optimization results between theoretical completeness and engineering feasibility. For example, according to the IEEE 1766 cable detection standard, the maximum allowable duration of the system can be set as Through the time delay constraint, the defect spatial resolution is guaranteed, and the signal frequency domain validity is guaranteed through the product constraint, and the hardware feasibility is guaranteed through the device constraint. Under the above premise, the bandwidth will be optimized. B The cable parameters are converted into a rigid boundary for the signal duration, providing a complete theoretical basis for physical signal generation.

[0035] In one embodiment of the present specification, a linear frequency modulation incident signal with a Gaussian envelope is generated based on the obtained target center frequency, target bandwidth and optimized duration to determine the optimized incident signal and obtain a TFDR incident signal. By optimizing the incident signal, defect detection is performed on the target detection cable, and accurate positioning of defects can be achieved for cables of different types and lengths.

[0036] In one embodiment of this specification, before an incident signal is injected into a cable for inspection, it is windowed using an adaptive window function that senses instantaneous frequency energy. The standard deviation of the window function is dynamically correlated with the signal's instantaneous frequency energy. The Gaussian window standard deviation is adjusted based on the signal's local energy distribution, enhancing suppression in low-energy regions (signal edges) while maintaining signal integrity in high-energy regions. A weighted window function that also senses instantaneous frequency is used to suppress noise, concentrating the energy in the target frequency band in the frequency domain. This prevents the incident signal from being overwhelmed by noise during cable defect location, enabling the location of subtle defects over long distances. Through the technical solutions of the embodiments of this specification, compared with traditional time-frequency incident signals, by defining a loss function, a trade-off is made between the center frequency and bandwidth of the signal under high-frequency attenuation and spatial resolution, and the highest resolution is obtained while satisfying the maximum attenuation of the signal, which is beneficial to improving the accuracy of cable defect positioning; after obtaining the target transmission function based on the multi-component incident signal, the center frequency and bandwidth parameters are dynamically generated based on the fitting results of the target cable attenuation model, so that the incident signal intelligently avoids the high-frequency attenuation area and focuses on the low-loss passband, breaking through the problem of attenuation failure of fixed parameter signals in long-distance cables; compared with traditional time-frequency incident signals, the attenuation characteristics can be fitted by extracting the material parameters and geometric parameters of cables of different lengths and types, and the parameters are adaptively adjusted based on this, which is beneficial to improving the universality of time-frequency domain algorithm detection; adaptive matching of the incident signal and cable characteristics is achieved without human intervention, effectively improving the defect positioning accuracy.

[0037] This specification also provides an example of cable defect detection based on time-frequency domain reflection. For a YJV22-0.6 / 1Kv 2*16mm2 cable with a length of 500m, the incident signal needs to consider the attenuation characteristics of this type of cable to select the signal parameters. First, the attenuation characteristics of the cable are extracted. Figure 2 This is a schematic diagram of a cable attenuation characteristic curve provided in an embodiment of this specification, such as Figure 2As shown, the maximum allowed signal attenuation is 0.85dB / 100m. The gradient descent method is used to calculate the optimal center frequency to be 10MHz and the bandwidth to be 10MHz. The rise time, fall time and sweep range performance of the signal generator limit the signal duration to a minimum of 25ns. The time domain resolution requires a minimum duration of 50ns, so a signal duration of 50ns is selected. In summary, the linear frequency modulation incident signal of the Gaussian envelope will be set with the following parameters: the center frequency is 10MHz, the signal duration is 50ns, and the time width coefficient is a frequency bandwidth of 10MHz (5MHz, 15MHz); the time domain waveform and frequency domain waveform of the incident signal are finally generated as shown below. Figure 3 and Figure 4 As shown, Figure 3 A schematic diagram of a time domain waveform of an incident signal provided in an embodiment of this specification, Figure 4 This is a schematic diagram of a frequency domain waveform of an incident signal provided in an embodiment of this specification. The incident signal is used for cable defect location and processed using a window function of instantaneous frequency perception. Figure 5 This is a schematic diagram of a defect location curve provided in the embodiment of this specification. The location result is as follows: Figure 5 As shown in the figure, the cable defect is located at 450m, and the positioning curve shows the result is 449.5m, with an error of only 0.1%, indicating that this method has the accuracy to locate weak defects over long distances.

[0038] The embodiment of this specification also provides a cable defect detection device based on time-frequency domain reflection, such as Figure 6 As shown, the device includes: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions that can be executed by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to perform the above method.

[0039] The embodiments of this specification also provide a non-volatile computer storage medium storing computer executable instructions, wherein the computer executable instructions are configured to execute the above method.

[0040] The various embodiments in this specification are described in a progressive manner. Similar portions between the various embodiments can be referenced to each other, and each embodiment focuses on the differences from the other embodiments. In particular, the device, apparatus, and non-volatile computer storage medium embodiments are generally similar to the method embodiments, so their descriptions are relatively simplified. For relevant details, refer to the descriptions of the method embodiments.

[0041] The foregoing description of this specification describes specific embodiments. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps recited in the claims can be performed in an order different from that described in the embodiments and still achieve the desired results. Furthermore, the processes depicted in the accompanying drawings do not necessarily require the specific order shown or the sequential order to achieve the desired results. In certain embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0042] The devices and media provided in the embodiments of this specification correspond one-to-one to the methods. Therefore, the devices and media also have similar beneficial technical effects to their corresponding methods. Since the beneficial technical effects of the methods have been described in detail above, the beneficial technical effects of the devices and media will not be repeated here.

[0043] Those skilled in the art will appreciate that the embodiments of this specification may be provided as methods, systems, or computer program products. Thus, this specification may take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware. Furthermore, this specification may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to magnetic disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0044] This specification is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of this specification. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 a process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0045] These computer program instructions may also be stored in a computer readable memory that can direct a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 a process or multiple processes and / or boxes Figure 1 The function specified in one or more boxes.

[0046] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operational steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing the instructions executed on the computer or other programmable device for implementing the process. Figure 1 a process or multiple processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.

[0047] In a typical configuration, a computing device includes one or more processors (CPUs), input / output interfaces, network interfaces, and memory.

[0048] Memory may include non-permanent storage in a computer-readable medium, in the form of random access memory (RAM) and / or non-volatile memory, such as read-only memory (ROM) or flash RAM. Memory is an example of a computer-readable medium.

[0049] Computer-readable media includes both permanent and non-permanent, removable and non-removable media that can be implemented using any method or technology to store information. Information can be computer-readable instructions, data structures, program modules, or other data. Examples of computer storage media include, but are not limited to, phase-change RAM (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technologies, compact disc read-only memory (CD-ROM), digital versatile disc (DVD) or other optical storage, magnetic cassettes, magnetic tape, magnetic disk storage or other magnetic storage devices, or any other non-transmission media that can be used to store information that can be accessed by a computing device. As defined herein, computer-readable media does not include transitory computer-readable media such as modulated data signals and carrier waves.

[0050] It should also be noted that the terms "comprises," "includes," or any other variations thereof are intended to encompass non-exclusive inclusion, such that a process, method, commodity, or apparatus that includes a series of elements includes not only those elements but also other elements not explicitly listed, or includes elements inherent to such process, method, commodity, or apparatus. In the absence of further limitations, an element defined by the phrase "comprises a ..." does not exclude the presence of other identical elements in the process, method, commodity, or apparatus that includes the element.

[0051] The foregoing description is merely one or more embodiments of this specification and is not intended to limit this specification. It will be apparent to those skilled in the art that various modifications and variations may be made to one or more embodiments of this specification. Any modifications, equivalent substitutions, or improvements made within the spirit and principles of one or more embodiments of this specification are intended to be within the scope of the claims of this specification.

Claims

1. A cable defect detection method based on time-frequency domain reflection, characterized in that: The method comprises: Performing parameter detection on the target detection cable through a preset multi-component incident signal to obtain a target reflection signal, so as to determine a target transmission function corresponding to the target detection cable based on the target reflection signal and the multi-component incident signal; fitting a target cable attenuation curve corresponding to the target detection cable according to the target transmission function to determine a loss function corresponding to the target detection cable; The loss function is used to iteratively optimize the preset detection incident signal to determine an optimized incident signal, so as to perform defect detection on the target detection cable through the optimized incident signal.

2. The cable defect detection method based on time-frequency domain reflection according to claim 1, characterized in that: Before performing parameter detection on the target detection cable using the preset multi-component incident signal, the method further includes: A multi-component incident signal is set, wherein the multi-component incident signal includes a Gaussian pulse component of multiple frequency components, the first frequency component is used to obtain the cable length and conductor cross-sectional area parameters, the second frequency component is used to obtain the dielectric constant parameter of the insulating material, and the third frequency component is used to obtain the loss tangent parameter of the insulating material.

3. The cable defect detection method based on time-frequency domain reflection according to claim 1, characterized in that: Determining a target transmission function corresponding to the target detection cable based on the target reflection signal and the multi-component incident signal specifically includes: Performing Fourier transform on the target reflected signal to determine a reflected frequency domain response signal, and performing Fourier transform on the multi-component incident signal to obtain an incident frequency domain response signal; The target transmission function corresponding to the target detection cable is determined by the ratio of the reflected frequency domain response signal to the incident frequency domain response signal.

4. The cable defect detection method based on time-frequency domain reflection according to claim 1, characterized in that: Fitting a target cable attenuation curve corresponding to the target detection cable according to the target transmission function to determine a loss function corresponding to the target detection cable specifically includes: Fitting a target cable attenuation model corresponding to the target detection cable according to the target transfer function, wherein the target cable attenuation model includes any one or more of a conductor resistance loss term, an insulation dielectric loss term, and a high-frequency polarization loss term; Based on the target cable attenuation model, a loss function corresponding to the target detection cable is defined.

5. The cable defect detection method based on time-frequency domain reflection according to claim 4 is characterized in that: Based on the target cable attenuation model, determining a loss function specifically includes: Determine, according to the target cable attenuation model, an average attenuation rate of the target detection cable within a preset frequency band, and determine, by using a pre-acquired cable length corresponding to the target detection cable, a cumulative attenuation parameter corresponding to the target detection cable; Determining an attenuation constraint item based on a cumulative attenuation parameter corresponding to the target detection cable and a preset maximum attenuation threshold; The trade-off coefficient corresponding to the attenuation constraint term is determined by the cable length and a preset reference cable length threshold, so as to determine the loss function corresponding to the target detection cable based on the attenuation constraint term, the trade-off coefficient and a preset signal-to-noise ratio.

6. The cable defect detection method based on time-frequency domain reflection according to claim 1, characterized in that: Iteratively optimizing the preset detection incident signal using the loss function to determine the optimized incident signal specifically includes: Iteratively optimizing the center frequency and bandwidth of the detected incident signal using a gradient descent method and the loss function to determine an optimized target center frequency and target bandwidth; Determining a duration constraint condition according to the target bandwidth and a pre-acquired cable length parameter of the target detection cable, so as to determine an optimized duration corresponding to the target detection cable based on the duration constraint condition; A linear frequency modulated incident signal with a Gaussian envelope is generated based on the target center frequency, the target bandwidth, and the optimized duration to determine the optimized incident signal.

7. The cable defect detection method based on time-frequency domain reflection according to claim 6, characterized in that: Iteratively optimizing the center frequency and bandwidth of the detected incident signal using a gradient descent method and the loss function to determine an optimized target center frequency and target bandwidth, specifically including: Iteratively optimizing the center frequency and bandwidth of the detected incident signal by a gradient descent method, and calculating the partial derivatives of the loss function with respect to the center frequency and bandwidth in each iteration process; The disturbance frequency and disturbance bandwidth corresponding to the center frequency and bandwidth are set, and the signal-to-noise ratio change in the loss function is calculated through the disturbance frequency and the disturbance bandwidth. When the preset convergence condition is met, the optimized target center frequency and target bandwidth are determined, wherein the convergence condition includes that the change in the loss function during multiple iterations is not greater than a preset threshold or reaches a preset maximum number of iterations.

8. The cable defect detection method based on time-frequency domain reflection according to claim 6, characterized in that: Determining a duration constraint condition based on the target bandwidth and a pre-acquired cable length parameter of the target detection cable, specifically including: Determining a defect delay constraint condition based on the cable length parameter and a pre-acquired signal propagation speed; Determining a product constraint corresponding to the duration based on the target bandwidth, and determining a corresponding device performance constraint using a pre-acquired minimum pulse width of the signal generator; The duration constraint is determined according to the defect delay constraint, the product constraint, and the device performance constraint.

9. A cable defect detection device based on time-frequency domain reflection, characterized in that: The device comprises: at least one processor; and, a memory communicatively connected to the at least one processor; wherein, The memory stores instructions that can be executed by the at least one processor. The instructions are executed by the at least one processor to enable the at least one processor to perform the method according to any one of claims 1 to 8.

10. A non-volatile computer storage medium storing computer executable instructions, characterized in that: The computer executable instructions are configured to execute the method according to any one of claims 1 to 8.

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