Railway section signal cable local defect detection and evaluation method and related equipment

Abstract

The invention discloses a railway section signal cable local defect detection and evaluation method and related equipment. The method comprises the steps that vector parameters of a cable to be detected are determined through a frequency domain reflection method, and a head end broadband impedance spectrum of the cable to be detected is calculated; performing high-pass filtering, time-frequency domain conversion and windowing processing on the head-end broadband impedance spectrum to obtain a local defect positioning curve; measuring distribution parameters of an intact cable with unit length under single frequency, fitting to obtain a change curve of the distribution parameters along with the frequency, further calculating an attenuation characteristic curve, and performing virtual compensation on a local defect positioning curve to obtain a local defect diagnosis curve; and carrying out positioning and severity evaluation on the local defect of the cable according to the peak position and the peak amplitude of the local defect diagnosis curve. According to the embodiment of the invention, attenuation compensation can be carried out based on the change curve of the cable distribution parameters along with the frequency, and the accuracy of cable local defect detection is improved. The method can be widely applied to the technical field of railway maintenance.

Description

Technical Field

[0001] This application relates to the field of railway maintenance technology, and in particular to a method and related equipment for detecting and evaluating local defects in railway section signal cables. Background Technology

[0002] Railway section signal cables are specialized cables used in railway signaling systems to transmit control signals, monitor track conditions, and ensure safe train operation. They are primarily laid alongside the tracks in railway sections between two stations. They are the "nerves" of the railway signaling system, directly impacting train safety and transportation efficiency. However, when railway section signal cables suffer varying degrees of localized damage due to aging or external forces, their electrical parameters change. If these minor localized damages are not addressed promptly, they will eventually lead to a decrease in the insulation of the cable core, causing malfunctions and, in severe cases, affecting train operation safety. Because railway section cables are laid between two stations, with long distances and numerous intermediate connections, locating damage points in these underground cables is often difficult and time-consuming, causing significant interference to the normal operation of the railway signaling system. Therefore, when localized defects occur in railway section signal cables, the maintenance management department can promptly identify the defective areas and intuitively understand the severity of these defects, which is crucial for improving the stability of the railway transportation system.

[0003] Frequency Domain Reflectometry (FDR), based on the traveling wave reflection method, locates faults by measuring the reflection coefficient spectrum at the cable's beginning. It is currently one of the effective techniques for detecting and locating localized defects in cables. First, a broadband sinusoidal signal is injected into the core of the cable under test. High-frequency signals do not reflect in a uniform medium. However, when the characteristics of the local medium change due to defects or aging, a reflected signal is generated. By analyzing the time-frequency characteristics of the reflection coefficient spectrum at the cable's beginning, the localized cable defect can be detected and located.

[0004] Unlike coaxial power cables, railway signal cables are multi-core cables, which are more prone to attenuation of high-frequency signals. Due to the long distance between sections and the numerous intermediate connections, each intermediate connection is equivalent to an impedance mismatch point, reflecting a portion of the incident signal. This significantly reduces the signal amplitude at the point of localized damage at the far end of the cable, making it impossible to determine the severity of potential defects such as localized damage at the cable end using the FDR positioning curve, leading to misjudgments or even missed detections.

[0005] In summary, the technical problems existing in the relevant technologies need to be improved. Summary of the Invention

[0006] The main objective of this application is to propose a method and related equipment for detecting and evaluating local defects in railway signal cables. Based on the attenuation compensation of the cable distribution parameters with frequency, the method achieves accurate location and severity assessment of local defects in railway signal cables, thereby improving the accuracy of local defect detection.

[0007] To achieve the above objectives, one aspect of this application proposes a method for detecting and evaluating local defects in railway signal cables, the method comprising: The frequency domain parameters are determined based on the length of the cable under test, the vector parameters of the cable under test are determined by the frequency domain reflection method, and the first-end broadband impedance spectrum of the cable under test is calculated based on the vector parameters. The first broadband impedance spectrum is subjected to high-pass filtering to obtain the second broadband impedance spectrum. The second broadband impedance spectrum is then subjected to time-frequency domain transformation and windowing to obtain the local defect location curve of the cable under test. The distribution parameters of a unit length of intact cable at a single frequency are measured, and the curve of the distribution parameters changing with frequency is calculated by data fitting method. Based on the curve of the distribution parameters changing with frequency, the attenuation coefficient of the cable under test at each frequency point is calculated to obtain the attenuation characteristic curve of the cable under test. The local defect location curve is virtually compensated by the attenuation characteristic curve to obtain the local defect diagnosis curve of the cable under test. The location of the local defect in the cable under test is determined based on the peak position of the local defect diagnosis curve, and the severity of the local defect is assessed based on the peak amplitude of the local defect.

[0008] In some embodiments, the first-end broadband impedance spectrum of the cable under test is calculated using the following formula:

[0009] in, The first broadband impedance spectrum is shown. To test the characteristic impedance of the system, The vector parameter is denoted as .

[0010] In some embodiments, the first-end broadband impedance spectrum is high-pass filtered using the following formula:

[0011] in, This is the second first-end broadband impedance spectrum. The first broadband impedance spectrum is shown. These are the filter weight coefficients.

[0012] In some embodiments, the second first-end broadband impedance spectrum is subjected to time-frequency domain transformation and windowing using the following formula:

[0013] in, This is the local defect location curve. This is the second first-end broadband impedance spectrum. For window functions.

[0014] In some embodiments, the distributed parameters include distributed resistance, distributed inductance, and distributed capacitance, and the curves of the distributed parameters as a function of frequency are calculated using the following formula:

[0015]

[0016]

[0017] in, The curve showing the variation of the distributed resistance with frequency is shown. These are the fitting parameters for the first distributed resistance. For frequency, These are the fitting parameters for the second distributed resistance. The fitting parameters for the third distributed resistance are... The curve showing the variation of the distributed inductance with frequency is shown below. These are the fitting parameters for the first distributed inductance. These are the fitting parameters for the second distributed inductance. The fitting parameters for the third distributed inductance are... These are the fitting parameters for the fourth distributed inductance. The fitting parameters for the fifth distributed inductance are... The fitting parameters for the sixth distributed inductance are... The fitting parameters for the seventh distributed inductance are... The fitting parameters for the eighth distributed inductance are... The fitting parameters for the ninth distributed inductance are... The curve showing the variation of the distributed capacitance with frequency is shown. These are the fitting parameters for the first distributed capacitance. These are the fitting parameters for the second distributed capacitance. The fitting parameters for the third distributed capacitance are... These are the fitting parameters for the fourth distributed capacitance.

[0018] In some embodiments, the distributed parameters include distributed resistance, distributed inductance, and distributed capacitance. The attenuation coefficient of the cable under test at each frequency point is calculated using the following formula to obtain the attenuation characteristic curve of the cable under test:

[0019]

[0020] in, The attenuation characteristic curve is shown below. Angular frequency, For frequency, The curve showing the variation of the distributed resistance with frequency is shown. The curve showing the variation of the distributed inductance with frequency is shown below. The conductivity of the cable under test is given. The curve shows the variation of the distributed capacitance with frequency.

[0021] In some embodiments, the local defect location curve is virtually compensated using the following formula:

[0022] in, This is the diagnostic curve for the local defect. This is the local defect location curve. The attenuation characteristic curve is shown below. The length of the cable to be tested is given.

[0023] To achieve the above objectives, another aspect of this application proposes a device for detecting and evaluating local defects in railway section signal cables, the device comprising: The signal transmission and reflection signal acquisition module is used to determine the frequency domain parameters based on the length of the cable under test, determine the vector parameters of the cable under test through the frequency domain reflection method, and calculate the first-end broadband impedance spectrum of the cable under test based on the vector parameters. The data preprocessing module is used to perform high-pass filtering on the first broadband impedance spectrum to obtain the second broadband impedance spectrum, and to perform time-frequency domain transformation and windowing on the second broadband impedance spectrum to obtain the local defect location curve of the cable under test. The attenuation characteristic curve calculation module is used to measure the distribution parameters of a unit length of intact cable at a single frequency, calculate the curve of the distribution parameters changing with frequency through a data fitting method, calculate the attenuation coefficient of the cable under test at each frequency point based on the curve of the distribution parameters changing with frequency, and obtain the attenuation characteristic curve of the cable under test. An attenuation compensation module is used to virtually compensate the local defect location curve using the attenuation characteristic curve to obtain the local defect diagnosis curve of the cable under test. The local defect diagnosis module is used to determine the location of the local defect in the cable under test based on the peak position of the local defect diagnosis curve, and to assess the severity of the local defect based on the peak amplitude of the local defect.

[0024] To achieve the above objectives, another aspect of this application provides an electronic device, which includes a memory and a processor. The memory stores a computer program, and the processor executes the computer program to implement the methods described above.

[0025] To achieve the above objectives, another aspect of the embodiments of this application proposes a computer-readable storage medium storing a computer program that, when executed by a processor, implements the methods described above.

[0026] To achieve the above objectives, another aspect of this application provides a computer program product, including a computer program that, when executed by a processor, implements the methods described above. The embodiments of this application include at least the following beneficial effects: This application provides a method and related equipment for detecting and evaluating local defects in railway signal cables. This method calculates the broadband impedance spectrum at the beginning of the cable under test, providing a data basis for subsequent signal preprocessing and defect location. By performing high-pass filtering, time-frequency domain conversion, and windowing on the broadband impedance spectrum at the beginning, the high-frequency components of the signal can be enhanced, compensating for the high-frequency attenuation of the cable itself, thus facilitating more accurate defect location. By measuring the distributed parameters of a single frequency, unit length of intact cable, and using data fitting methods to calculate the curve of the distributed parameters changing with frequency, the attenuation characteristic curve can be further calculated, enabling accurate... This method characterizes the signal attenuation pattern of cables at different frequencies, providing a mathematical basis for subsequent attenuation compensation. By virtually compensating the local defect location curve using the attenuation characteristic curve, a local defect diagnosis curve is obtained. Based on this curve, defect location and severity assessment are performed, effectively eliminating signal attenuation caused by transmission distance. The peak amplitude of the compensated cable defect diagnosis curve depends only on the impedance mismatch at the reflection point, reducing the probability of missed and false detections at the far end of the test. Furthermore, the magnitude of the peak amplitude can be used to intuitively assess the severity of the defect, facilitating maintenance personnel to quickly determine the defect location and processing priority, thus improving the maintenance efficiency of the railway system. Attached Figure Description

[0027] Figure 1 This is a flowchart illustrating the steps of a method for detecting and evaluating local defects in railway signal cables according to an embodiment of this application. Figure 2 This is a schematic diagram of the cable local defect location curve provided in the embodiments of this application; Figure 3 This is a schematic diagram of the cable defect diagnosis curve provided in the embodiments of this application; Figure 4 This is a schematic diagram of the structure of a local defect detection and evaluation device for railway section signal cables provided in an embodiment of this application; Figure 5 This is a schematic diagram of the hardware structure of the electronic device provided in the embodiments of this application. Detailed Implementation

[0028] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of this application and are not intended to limit it. In the following description, when referring to the accompanying drawings, unless otherwise indicated, the same numbers in different drawings represent the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with those of this application; they are merely examples of apparatuses and methods consistent with some aspects of the embodiments of this application as detailed in the appended claims.

[0029] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs. The terminology used herein is for the purpose of describing embodiments of this application only and is not intended to limit this application.

[0030] The concept of the present invention will now be explained in conjunction with the background art.

[0031] Existing cable defect detection methods mostly employ frequency domain reflection analysis to locate anomalies within the cable. However, railway signal cables differ from coaxial power cables. Railway section cables are multi-core cables, which inherently suffer from significant attenuation of high-frequency signals. Furthermore, due to the long distances between sections and numerous intermediate connections, each connection represents an impedance mismatch point, reflecting a portion of the incident signal. This drastically reduces the signal amplitude reaching the localized breakage point at the cable's distal end, making it impossible to determine the severity of potential defects such as localized breakage points at the cable's end using FDR (Frequency Domain Reflectometry) curves, leading to misjudgments or even missed detections.

[0032] In view of this, this application provides a method and related equipment for detecting and evaluating local defects in railway signal cables. Based on the attenuation compensation of the cable distribution parameters with frequency, it realizes the accurate location and severity assessment of local defects in railway signal cables, effectively solving the problems of difficulty in detecting potential faults such as local damage to railway signal cables and difficulty in assessing the severity of faults.

[0033] This application provides a method for detecting and evaluating local defects in railway signal cables, relating to the field of information technology. This method can be applied to a terminal, a server, or software running on either a terminal or a server. In some embodiments, the terminal can be a smartphone, tablet, laptop, desktop computer, smart speaker, smartwatch, or in-vehicle terminal, but is not limited to these. The server can be configured as an independent physical server, a server cluster or distributed system composed of multiple physical servers, or a cloud server providing basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communication, middleware services, domain name services, security services, CDN, and big data and artificial intelligence platforms. The server can also be a node server in a blockchain network. The software can be an application implementing the method for detecting and evaluating local defects in railway signal cables, but is not limited to the above forms.

[0034] This application can be used in a wide variety of general-purpose or special-purpose computer system environments or configurations. Examples include: personal computers, server computers, handheld or portable devices, tablet devices, multiprocessor systems, microprocessor-based systems, set-top boxes, programmable consumer electronics, network PCs, minicomputers, mainframe computers, and distributed computing environments including any of the above systems or devices. This application can be described in the general context of computer-executable instructions executed by a computer, such as program modules. Generally, program modules include routines, programs, objects, components, data structures, etc., that perform specific tasks or implement specific abstract data types. This application can also be practiced in distributed computing environments where tasks are performed by remote processing devices connected via a communication network. In distributed computing environments, program modules can reside in local and remote computer storage media, including storage devices.

[0035] Figure 1 This is an optional flowchart of a method for detecting and evaluating local defects in railway section signal cables provided in an embodiment of this application. Figure 1 The method may include, but is not limited to, steps S101 to S105.

[0036] S101. Determine the frequency domain parameters based on the length of the cable under test, determine the vector parameters of the cable under test using the frequency domain reflection method, and calculate the broadband impedance spectrum of the first end of the cable under test based on the vector parameters. In some embodiments, the first-terminal broadband impedance spectrum of the cable under test is calculated using the following formula:

[0037] in, The first broadband impedance spectrum. To test the characteristic impedance of the system, These are vector parameters.

[0038] Specifically, in this embodiment, frequency parameters (including frequency bandwidth, frequency step size, etc.) are determined based on the length of the cable under test. Based on these frequency parameters, a stepped-frequency signal is injected into the cable using the frequency domain reflection method. The S-parameters are measured using a vector network analyzer. Then, the first-end broadband impedance spectrum of the cable under test is further calculated based on the aforementioned formula. The characteristic impedance of the test system (i.e., the vector network analyzer).

[0039] S102. High-pass filtering is performed on the first broadband impedance spectrum to obtain the second broadband impedance spectrum. Time-frequency domain transformation and windowing are performed on the second broadband impedance spectrum to obtain the local defect location curve of the cable under test. In some embodiments, the first-end broadband impedance spectrum is high-pass filtered using the following formula:

[0040] in, The second-end broadband impedance spectrum. The first broadband impedance spectrum. These are the filter weight coefficients.

[0041] Specifically, due to the high-frequency attenuation characteristics of railway signal cables, the high-frequency energy of the reflected signal is low. Therefore, in this embodiment, the impedance spectrum of the first end of the cable under test (i.e., the first broadband impedance spectrum of the first end) is first uploaded to the host computer software and then high-pass filtered by a first-order high-pass filter to enhance the energy of the high-frequency part of the reflected signal, which is convenient for subsequent processing. The value range of the filter weight coefficient μ is [0, 1].

[0042] In some embodiments, the second-end broadband impedance spectrum is subjected to time-frequency domain transformation and windowing using the following formula:

[0043] in, This is a curve for locating local defects. The second-end broadband impedance spectrum. For window functions.

[0044] Specifically, in this embodiment, W(n) represents a window function, which can be one of the Blackman window, the Kaiser window, or other window functions.

[0045] S103. Measure the distributed parameters of a unit length of intact cable at a single frequency, calculate the curve of the distributed parameters changing with frequency through data fitting method, calculate the attenuation coefficient of the cable under test at each frequency point based on the curve of the distributed parameters changing with frequency, and obtain the attenuation characteristic curve of the cable under test. In some embodiments, the distributed parameters include distributed resistance, distributed inductance, and distributed capacitance. The curves of the distributed parameters as a function of frequency are calculated using the following formula:

[0046]

[0047]

[0048] in, This is a curve showing the distribution resistance as a function of frequency. These are the fitting parameters for the first distributed resistance. For frequency, These are the fitting parameters for the second distributed resistance. The fitting parameters for the third distributed resistance are... The curve shows the variation of distributed inductance with frequency. These are the fitting parameters for the first distributed inductance. These are the fitting parameters for the second distributed inductance. The fitting parameters for the third distributed inductance are... These are the fitting parameters for the fourth distributed inductance. The fitting parameters for the fifth distributed inductance are... The fitting parameters for the sixth distributed inductance are... The fitting parameters for the seventh distributed inductance are... The fitting parameters for the eighth distributed inductance are... The fitting parameters for the ninth distributed inductance are... This is a curve showing the variation of distributed capacitance with frequency. These are the fitting parameters for the first distributed capacitance. These are the fitting parameters for the second distributed capacitance. The fitting parameters for the third distributed capacitance are... These are the fitting parameters for the fourth distributed capacitance.

[0049] Specifically, in this embodiment, an impedance analyzer is used to measure the distributed parameters (including distributed resistance, distributed inductance, and distributed capacitance) of a unit length of intact cable at a single frequency; further, a data fitting method is used to obtain the curves of each distributed parameter changing with frequency within the test frequency. Referring to the above formula, this example constructs a fitting equation based on the least squares fitting algorithm to obtain the curves of the cable distributed parameters changing with frequency.

[0050] In some embodiments, the distributed parameters include distributed resistance, distributed inductance, and distributed capacitance. The attenuation coefficient of the cable under test at each frequency point is calculated using the following formula to obtain the attenuation characteristic curve of the cable under test:

[0051]

[0052] in, The attenuation characteristic curve is shown. Angular frequency, For frequency, This is a curve showing the distribution resistance as a function of frequency. The curve shows the variation of distributed inductance with frequency. The conductivity of the cable under test, This is a curve showing the variation of distributed capacitance with frequency.

[0053] Specifically, referring to the above formula, this embodiment calculates the attenuation coefficient of the cable under test at each frequency point based on the curves of the variation of each distributed parameter with frequency, and obtains the curves of the variation of the attenuation coefficient with frequency.

[0054] S104. Virtual compensation is performed on the local defect location curve using the attenuation characteristic curve to obtain the local defect diagnosis curve of the cable under test. In some embodiments, the local defect location curve is virtually compensated using the following formula:

[0055] in, This is a local defect diagnosis curve. This is a curve for locating local defects. The attenuation characteristic curve is shown. The length of the cable to be tested is given.

[0056] S105. Determine the location of the local defect in the cable under test based on the peak position of the local defect diagnosis curve, and assess the severity of the local defect based on the peak amplitude of the local defect.

[0057] Specifically, referring to the above formula, this embodiment uses the attenuation characteristic curve to virtually compensate the defect location curve based on the local defect location curve and the attenuation characteristic curve of the cable under test. After obtaining the local defect diagnosis curve of the cable under test, the location of the local defect is determined according to the peak position of the local defect diagnosis curve, and the severity of the defect is assessed according to the magnitude of the defect peak amplitude.

[0058] The present invention will be further described below with reference to a specific embodiment: Taking the measured faulty cable data at a railway station as an example, the tested cable is an underground PTYA23 railway section signal cable. This section of cable includes two above-ground junction boxes, located 908 meters and 2785 meters from the signal tower respectively, with a total cable length of 4665 meters. The broadband impedance spectrum of the cable's head end was collected using testing instruments, and after high-pass filtering and windowing, Fourier transform was performed to obtain the following data: Figure 2 The curve shown is a local defect location curve for the cable.

[0059] Reference Figure 2 Significant peak values ​​appeared at 908 meters, 2787 meters, and 4666 meters, corresponding to splice 1, splice 2, and the end of the cable, respectively. A significant peak value also appeared at 1816 meters, suggesting a possible localized defect at this location. Normally, the peak value is positively correlated with the degree of impedance mismatch; the peak value should be largest at the cable end where impedance mismatch is most severe. However, if… Figure 2 As shown, the peak value of the splice box near the test end is the largest, even exceeding the peak value at the end. This is due to the high-frequency attenuation of the cable in the section. For long cables in railway sections, the high-frequency attenuation of the cable itself may cause misjudgment and missed detection of the degree of defect.

[0060] To compensate for the high-frequency attenuation of the cable itself in railway sections and the signal attenuation with transmission distance, the distributed parameters R, L, and C of the cable were first measured at a single frequency. Then, the cable's frequency variation curve within the frequency band was obtained using a least-squares fitting algorithm. Further calculations were performed to obtain the cable attenuation curve as a function of length. This cable attenuation curve was then used to compensate for the cable's local defect location curve, thus obtaining... Figure 3 The cable defect diagnosis curve shown is shown.

[0061] Reference Figure 3 After attenuation compensation, the signal waveform amplitude does not decrease with transmission distance, and the peak amplitude at the cable terminal box and cable end is significantly improved, making the fault peak more obvious. This means that the peak amplitude of the cable defect diagnosis curve after compensation depends only on the impedance mismatch at the reflection point. This not only effectively reduces the probability of missed and false detections at the far end of the test, but also allows for a direct understanding of the severity of the defect by observing the peak amplitude, providing strong support for railway operation and maintenance management departments to adopt effective maintenance plans.

[0062] Please see Figure 4 This application also provides a device for detecting and evaluating local defects in railway section signal cables, which can implement the above-mentioned method. The device includes: The signal transmission and reflection signal acquisition module is used to determine the frequency domain parameters based on the length of the cable under test, determine the vector parameters of the cable under test through the frequency domain reflection method, and calculate the first-end broadband impedance spectrum of the cable under test based on the vector parameters. The data preprocessing module is used to perform high-pass filtering on the first end broadband impedance spectrum to obtain the second end broadband impedance spectrum, and to perform time-frequency domain transformation and windowing on the second end broadband impedance spectrum to obtain the local defect location curve of the cable under test. The attenuation characteristic curve calculation module is used to measure the distributed parameters of a unit length of intact cable at a single frequency. It calculates the curve of the distributed parameters changing with frequency through data fitting method, and calculates the attenuation coefficient of the cable under test at each frequency point based on the curve of the distributed parameters changing with frequency, thus obtaining the attenuation characteristic curve of the cable under test. The attenuation compensation module is used to virtually compensate the local defect location curve through the attenuation characteristic curve to obtain the local defect diagnosis curve of the cable under test. The local defect diagnosis module is used to determine the location of local defects in the cable under test based on the peak position of the local defect diagnosis curve, and to assess the severity of the local defects based on the peak amplitude of the local defects.

[0063] It is understood that the content of the above method embodiments is applicable to the present device embodiments. The specific functions implemented by the present device embodiments are the same as those of the above method embodiments, and the beneficial effects achieved are also the same as those achieved by the above method embodiments.

[0064] This application also provides an electronic device, which includes a memory and a processor. The memory stores a computer program, and the processor executes the computer program to implement the above-described method. This electronic device can be any smart terminal, including tablet computers, in-vehicle computers, etc.

[0065] It is understood that the content of the above method embodiments is applicable to this device embodiment. The specific functions implemented by this device embodiment are the same as those of the above method embodiments, and the beneficial effects achieved are also the same as those achieved by the above method embodiments.

[0066] Please see Figure 5 , Figure 5 The hardware structure of an electronic device according to another embodiment is illustrated. The electronic device includes: The processor 901 can be implemented using a general-purpose CPU (Central Processing Unit), microprocessor, application-specific integrated circuit (ASIC), or one or more integrated circuits, and is used to execute relevant programs to implement the technical solutions provided in the embodiments of this application. The memory 902 can be implemented as a read-only memory (ROM), static storage device, dynamic storage device, or random access memory (RAM). The memory 902 can store the operating system and other application programs. When the technical solutions provided in the embodiments of this specification are implemented through software or firmware, the relevant program code is stored in the memory 902 and is called and executed by the processor 901 using the methods described in the embodiments of this application. The input / output interface 903 is used to implement information input and output; The communication interface 904 is used to enable communication and interaction between this device and other devices. Communication can be achieved through wired means (such as USB, Ethernet cable, etc.) or wireless means (such as mobile network, WIFI, Bluetooth, etc.). Bus 905 transmits information between various components of the device (e.g., processor 901, memory 902, input / output interface 903, and communication interface 904); The processor 901, memory 902, input / output interface 903, and communication interface 904 are connected to each other within the device via bus 905.

[0067] This application also provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the above-described method.

[0068] It is understood that the content of the above method embodiments is applicable to this storage medium embodiment. The specific functions implemented in this storage medium embodiment are the same as those in the above method embodiments, and the beneficial effects achieved are also the same as those achieved in the above method embodiments.

[0069] This application also provides a computer program product, including a computer program that, when executed by a processor, implements the above-described method.

[0070] It is understood that the content of the above method embodiments is applicable to the embodiments of this program product. The specific functions implemented by the embodiments of this program product are the same as those of the above method embodiments, and the beneficial effects achieved are also the same as those achieved by the above method embodiments.

[0071] Memory, as a non-transitory computer-readable storage medium, can be used to store non-transitory software programs and non-transitory computer-executable programs. Furthermore, memory may include high-speed random access memory, and may also include non-transitory memory, such as at least one disk storage device, flash memory device, or other non-transitory solid-state storage device. In some embodiments, memory may optionally include memory remotely located relative to the processor, and these remote memories can be connected to the processor via a network. Examples of such networks include, but are not limited to, the Internet, intranets, local area networks, mobile communication networks, and combinations thereof.

[0072] This application provides a method and related equipment for detecting and evaluating local defects in railway signal cables. The method involves calculating the broadband impedance spectrum at the beginning of the cable under test, providing a data foundation for subsequent signal preprocessing and defect localization. By performing high-pass filtering, time-frequency domain transformation, and windowing on the broadband impedance spectrum, the high-frequency components of the signal are enhanced, compensating for the high-frequency attenuation of the cable itself, thus facilitating more accurate defect localization. Furthermore, by measuring the distributed parameters of a single frequency and a unit length of intact cable, and using data fitting methods to calculate the curve of the distributed parameters changing with frequency, the attenuation characteristic curve is further calculated. The line can accurately characterize the signal attenuation law of the cable at different frequencies, providing a mathematical basis for subsequent attenuation compensation. By virtually compensating the local defect location curve through the attenuation characteristic curve, a local defect diagnosis curve is obtained. Based on the local defect diagnosis curve, defect location and severity assessment are performed, effectively eliminating signal attenuation caused by transmission distance. The peak amplitude of the compensated cable defect diagnosis curve depends only on the impedance mismatch at the reflection point, reducing the probability of missed and false detections at the far end of the test. Furthermore, the severity of the defect can be intuitively assessed by the magnitude of the peak amplitude, making it easier for maintenance personnel to quickly determine the defect location and processing priority, thus improving the maintenance efficiency of the railway system.

[0073] The embodiments described in this application are for the purpose of more clearly illustrating the technical solutions of the embodiments of this application, and do not constitute a limitation on the technical solutions provided by the embodiments of this application. As those skilled in the art will know, with the evolution of technology and the emergence of new application scenarios, the technical solutions provided by the embodiments of this application are also applicable to similar technical problems.

[0074] Those skilled in the art will understand that the technical solutions shown in the figures do not constitute a limitation on the embodiments of this application, and may include more or fewer steps than shown, or combine certain steps, or different steps.

[0075] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs.

[0076] Those skilled in the art will understand that all or some of the steps in the methods disclosed above, as well as the functional modules / units in the systems and devices, can be implemented as software, firmware, hardware, or suitable combinations thereof.

[0077] The terms “first,” “second,” “third,” “fourth,” etc. (if present) in the specification and accompanying drawings of this application are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of this application described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms “comprising” and “having,” and any variations thereof, are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0078] It should be understood that in this application, "at least one (item)" means one or more, and "more than" means two or more. "And / or" is used to describe the relationship between related objects, indicating that three relationships can exist. For example, "A and / or B" can represent three cases: only A exists, only B exists, and both A and B exist simultaneously, where A and B can be singular or plural. The character " / " generally indicates that the preceding and following related objects are in an "or" relationship. "At least one (item) of the following" or similar expressions refer to any combination of these items, including any combination of single or plural items. For example, at least one (item) of a, b, or c can represent: a, b, c, "a and b", "a and c", "b and c", or "a and b and c", where a, b, and c can be single or multiple.

[0079] In the several embodiments provided in this application, it should be understood that the disclosed apparatus and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of the units described above is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between apparatuses or units may be electrical, mechanical, or other forms.

[0080] The units described above as separate components may or may not be physically separate. 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 the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0081] Furthermore, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0082] 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 this application, in essence, or the part 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 multiple instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods of the various embodiments of this application. The aforementioned storage medium includes various media capable of storing programs, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0083] The preferred embodiments of the present application have been described above with reference to the accompanying drawings, but this does not limit the scope of the claims of the present application. Any modifications, equivalent substitutions, and improvements made by those skilled in the art without departing from the scope and substance of the embodiments of the present application shall be within the scope of the claims of the present application.

Claims

1. A method for assessing the detection of local defects in a railway section signal cable, characterized in that, The method comprises the following steps: determining a frequency domain parameter according to the length of the to-be-tested cable, determining a vector parameter of the to-be-tested cable by a frequency domain reflection method, calculating a first head-end broadband impedance spectrum of the to-be-tested cable according to the vector parameter; performing high-pass filtering on the first head-end broadband impedance spectrum to obtain a second head-end broadband impedance spectrum, and performing time-frequency domain conversion and windowing on the second head-end broadband impedance spectrum to obtain a local defect positioning curve of the to-be-tested cable; measuring a distributed parameter of a unit length of intact cable at a single frequency, calculating a curve of the distributed parameter changing with frequency by a data fitting method, calculating an attenuation coefficient of the to-be-tested cable at each frequency point according to the curve of the distributed parameter changing with frequency to obtain an attenuation characteristic curve of the to-be-tested cable; virtually compensating the local defect positioning curve by using the attenuation characteristic curve to obtain a local defect diagnosis curve of the to-be-tested cable; determining the position of the local defect of the to-be-tested cable according to the peak position of the local defect diagnosis curve, and evaluating the severity of the local defect according to the peak amplitude of the local defect.

2. A method for evaluating partial defect of a railway section signal cable according to claim 1, characterized in that, The first head-end broadband impedance spectrum of the to-be-tested cable is calculated by the following formula: wherein, is the first open-circuit wideband impedance spectrum, is the characteristic impedance of the test system, is the vector parameter.

3. A method for evaluating partial defect of railway section signal cable according to claim 1, characterized in that, The high-pass filtering on the first head-end broadband impedance spectrum is performed by the following formula: wherein, is the second head wideband impedance spectrum, is the first head wideband impedance spectrum, is a filter weight coefficient.

4. The method for evaluating partial defect of railway section signal cable according to claim 1, characterized in that, The time-frequency domain conversion and windowing on the second head-end broadband impedance spectrum are performed by the following formula: wherein, locating a curve for the local defect, locating a second terminal broadband impedance spectrum, is a window function.

5. A method for evaluating partial defect of railway section signal cable according to claim 1, characterized in that, The distributed parameter includes a distributed resistance, a distributed inductance and a distributed capacitance, and the curve of the distributed parameter changing with frequency is calculated by the following formula: wherein is a curve of the distributed resistance as a function of frequency, is a first distributed resistance fitting parameter, is a frequency, is a second distributed resistance fitting parameter, is a third distributed resistance fitting parameter, is a curve of the distributed inductance as a function of frequency, is a first distributed inductance fitting parameter, is a second distributed inductance fitting parameter, is a third distributed inductance fitting parameter, is a fourth distributed inductance fitting parameter, is a fifth distributed inductance fitting parameter, is a sixth distributed inductance fitting parameter, is a seventh distributed inductance fitting parameter, is an eighth distributed inductance fitting parameter, is a ninth distributed inductance fitting parameter, is a curve of the distributed capacitance as a function of frequency, is a first distributed capacitance fitting parameter, is a second distributed capacitance fitting parameter, is a third distributed capacitance fitting parameter, is a fourth distributed capacitance fitting parameter.

6. A method for evaluating partial defect of railway section signal cable according to claim 1, characterized in that, The distributed parameter includes a distributed resistance, a distributed inductance and a distributed capacitance, and the attenuation coefficient of the to-be-tested cable at each frequency point is calculated by the following formula to obtain the attenuation characteristic curve of the to-be-tested cable: wherein is the attenuation characteristic curve, is the angular frequency, is the frequency, is the distributed resistance curve as a function of frequency, is the distributed inductance curve as a function of frequency, is the conductance of the cable under test, is the distributed capacitance curve as a function of frequency.

7. The method for evaluating partial defect of railway section signal cable according to claim 1, characterized in that, The local defect positioning curve is virtually compensated by the following formula: wherein is the local defect diagnosis curve, is the local defect localization curve, is the attenuation characteristic curve, is the length of the cable under test.

8. A railway section signal cable partial defect detection evaluation device, characterized by, The device comprises: a signal transmission and reflection signal acquisition module, configured to determine a frequency domain parameter according to the length of the to-be-tested cable, determine a vector parameter of the to-be-tested cable by a frequency domain reflection method, and calculate a first head-end broadband impedance spectrum of the to-be-tested cable according to the vector parameter; a data preprocessing module, configured to perform high-pass filtering on the first head-end broadband impedance spectrum to obtain a second head-end broadband impedance spectrum, and perform time-frequency domain conversion and windowing on the second head-end broadband impedance spectrum to obtain a local defect positioning curve of the to-be-tested cable; an attenuation characteristic curve calculation module, configured to measure a distributed parameter of a unit length of intact cable at a single frequency, calculate a curve of the distributed parameter changing with frequency by a data fitting method, and calculate an attenuation coefficient of the to-be-tested cable at each frequency point according to the curve of the distributed parameter changing with frequency to obtain an attenuation characteristic curve of the to-be-tested cable; an attenuation compensation module, configured to virtually compensate the local defect positioning curve by using the attenuation characteristic curve to obtain a local defect diagnosis curve of the to-be-tested cable; a local defect diagnosis module, configured to determine the position of the local defect of the to-be-tested cable according to the peak position of the local defect diagnosis curve, and evaluate the severity of the local defect according to the peak amplitude of the local defect.

9. An electronic device, comprising: The electronic device comprises a memory and a processor, the memory stores a computer program, and the processor implements the method in any one of claims 1 to 7 when executing the computer program.

10. A computer program product comprising a computer program, characterized in that, The computer program is executed by the processor to implement the method in any one of claims 1 to 7.

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