Cable defect positioning method based on frequency domain reflection-constant false alarm rate and related device

Abstract

The invention discloses a cable defect positioning method based on a frequency domain reflection-constant false alarm rate and a related device, and belongs to the technical field of cable local defect positioning. The method comprises the following steps: firstly, calculating according to distribution parameters of a defective cable to obtain a head-end impedance spectrum of the defective cable, and then carrying out discrete Fourier transform on the head-end impedance spectrum to extract impedance spectrum characteristic information to obtain a cable defect positioning spectrogram; and finally, substituting the existing positioning spectrum data into an algorithm to carry out one-dimensional calculation by utilizing an adaptive threshold value of CFAR, and if the amplitude value of a data point is greater than the threshold value, judging that the data point is a defect point and keeping the defect point. Otherwise, judging that no defect point exists and setting the data to be zero so as to extract the position of the actual defect point. According to the method, the threshold value can be adaptively changed, the position and the peak value of the defect in the positioning spectrum are extracted, and misjudgment caused by human subjective factors and objective factors on a test site is reduced.

Description

Technical Field

[0001] The invention belongs to the technical field of cable local defect positioning, and relates to a cable defect positioning method based on frequency domain reflection-constant false alarm rate and a related device. Background Art

[0002] With the acceleration of urbanization, power cables are gradually replacing overhead lines and becoming the backbone of urban power grids due to their advantages such as small footprint and high power supply reliability. In actual operation, cables may suffer from insulation defects due to moisture, aging, or external mechanical stress, leading to equipment damage, power outages and other safety accidents. Therefore, it is of great significance to quickly and accurately detect and locate cable defects.

[0003] At present, the most commonly used methods for cable status detection are partial discharge (PD) detection method, time domain reflectometry (TDR) detection method and frequency domain reflectometry (FDR) detection method. The PD method is the most common oscillation wave detection method, which has a good detection effect, but the detection objects are mainly cable accessories and cable installation defects, and it is difficult to detect latent defects in the cable body. The TDR method injects a pulse signal at the head end of the cable, and then directly identifies the reflected waveform in the time domain. This method can intuitively obtain the propagation distance and polarity of the reflected wave, but the incident signal has few high-frequency components, and its attenuation and dispersion phenomena are serious during the propagation process. The positioning accuracy is low, and it is difficult to identify weak defects. The FDR method uses a sweep frequency signal, which is mainly divided into the head end impedance spectrum (Broadband Impedance Spectrum, BIS) method and the reflection coefficient spectrum (Reflection Coefficient Spectrum, RCS) method. The characteristic parameters of the cable are obtained through Fourier transform, and the local defects of the cable are located with high sensitivity.

[0004] However, in the process of locating defects using the FDR method, when Fourier transforming the impedance spectrum, due to spectrum leakage and other reasons, "pseudo peaks" will be generated on the final positioning spectrum, thus affecting the positioning of the actual defect peak. At the same time, in actual testing, the signal attenuation of long cables is quite serious, and the influence of on-site noise is likely to further increase the difficulty of subjective judgment of defect peaks. Summary of the invention

[0005] The purpose of the present invention is to provide a cable defect location method and related devices based on frequency domain reflection-constant false alarm rate, so as to solve the technical problem that when locating defects in the prior art, "pseudo peaks" are easily generated on the positioning spectrum, resulting in misjudgment of defect points.

[0006] In order to achieve the above object, the present invention adopts the following technical solutions:

[0007] In a first aspect, the present invention provides a cable defect location method based on frequency domain reflection-constant false alarm rate, comprising the following steps:

[0008] Calculating the impedance spectrum of the first end of the defective cable according to the distribution parameters of the defective cable, and performing discrete Fourier transform on the impedance spectrum of the first end to extract characteristic information of the impedance spectrum, so as to obtain a cable defect location spectrum;

[0009] The data in the cable defect location spectrum are calculated in one dimension using the mean-type CFAR algorithm. If the amplitude of a data point is greater than the threshold, it is judged as a defect point and retained; if the amplitude of a data point is less than or equal to the threshold, it is judged as a non-defective point and the data is set to zero, thereby completing the extraction and location of the defect point.

[0010] Further, the step of calculating the impedance spectrum of the head end of the defective cable according to the distribution parameters of the defective cable, and performing fast Fourier transform on the impedance spectrum of the head end to extract characteristic information of the impedance spectrum to obtain the cable defect location spectrum specifically includes:

[0011] According to the distribution parameters of the defective cable, the impedance spectrum of the first end of the defective cable is calculated by transmission line theory. The specific calculation formula is:

[0012]

[0013] Where Z0 is the characteristic impedance; Γ L is the reflection coefficient at the end of the cable; γ is the propagation coefficient of the cable;

[0014] The impedance spectrum characteristic information is extracted from the head-end impedance spectrum by discrete Fourier transform to obtain the cable defect location spectrum Loc. The specific formula is:

[0015] Loc=abs(DFT(Im(Z l )))

[0016] Where DFT(·) is discrete Fourier transform and abs(·) is the modulus value.

[0017] Furthermore, the calculation formula of the characteristic impedance Z0 is:

[0018]

[0019] Where, R0 is the distributed resistance per unit length of the transmission line; G0 is the distributed conductance per unit length of the transmission line; j is the imaginary unit; ω is the angular frequency; L0 is the distributed inductance per unit length of the transmission line; C0 is the distributed capacitance per unit length of the transmission line;

[0020] The cable end reflection coefficient ΓL The calculation formula is:

[0021]

[0022] In the formula, Z L is the load impedance at the end of the cable; Z0 is the characteristic impedance;

[0023] The calculation formula of the propagation coefficient γ of the cable is:

[0024]

[0025] Where α is the attenuation coefficient and β is the phase coefficient.

[0026] Furthermore, the distributed parameters of the defective cable include distributed resistance R0 per unit length of the transmission line, distributed inductance L0 per unit length of the transmission line, distributed conductance G0 per unit length of the transmission line, and distributed capacitance C0 per unit length of the transmission line.

[0027] Furthermore, the calculation formula of the distributed resistance R0 per unit length of the transmission line is:

[0028]

[0029] Where μ0 is the vacuum magnetic permeability; r c is the cable core radius; r s is the inner radius of the metal shielding layer; ρ c is the cable core resistivity; ρ s is the resistivity of the metal shielding layer;

[0030] The calculation formula of the distributed inductance L0 per unit length of the transmission line is:

[0031]

[0032] The calculation formula of the distributed conductance G0 per unit length of the transmission line is:

[0033]

[0034] Where σ is the conductivity of the dielectric;

[0035] The calculation formula of the distributed capacitance C0 per unit length of the transmission line is:

[0036]

[0037] Where ε is the dielectric constant of the dielectric.

[0038] Furthermore, the mean-type CFAR algorithm includes a detection unit and 2n reference units; n reference units are arranged on both sides of the detection unit, and a protection unit is arranged between the detection unit and the reference unit; the CFAR algorithm calculates the mean Z through the data in the 2n reference units, thereby calculating the detection threshold T=αZ, where α is the threshold multiplication factor; if the amplitude of the detection unit is greater than the threshold T, it is determined that the target exists; otherwise, the target does not exist.

[0039] Furthermore, the step of performing one-dimensional calculation on the data in the cable defect location spectrum through the mean-type CFAR algorithm specifically includes: after determining the threshold coefficient α and the number of reference units n of the mean-type CFAR algorithm, keeping the false alarm probability unchanged, and then substituting the data in the cable defect location spectrum into the mean-type CFAR algorithm for one-dimensional calculation.

[0040] In a second aspect, the present invention provides a cable defect location system based on frequency domain reflection-constant false alarm rate, comprising:

[0041] A positioning spectrum module is used to calculate the impedance spectrum of the head end of the defective cable according to the distribution parameters of the defective cable, and to perform discrete Fourier transform on the impedance spectrum of the head end to extract the characteristic information of the impedance spectrum, so as to obtain a cable defect positioning spectrum;

[0042] The defect location module is used to perform one-dimensional calculation on the data in the cable defect location spectrum through the mean-type CFAR algorithm. If the amplitude of the data point is greater than the threshold, it is judged as a defect point and retained; if the amplitude of the data point is less than or equal to the threshold, it is judged as a non-defective point and the data is set to zero, thereby completing the extraction and location of the defect point.

[0043] In a third aspect, the present invention provides a computer device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the steps of the above method when executing the computer program.

[0044] In a fourth aspect, the present invention provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps of the above method are implemented.

[0045] Compared with the prior art, the present invention has the following beneficial effects:

[0046] The present invention discloses a method and related device for locating cable defects based on frequency domain reflection-constant false alarm rate. First, the impedance spectrum of the head end of the defective cable is calculated according to the distribution parameters of the defective cable, and then the impedance spectrum characteristic information is extracted by discrete Fourier transform to obtain the cable defect location spectrum. Finally, the adaptive threshold of CFAR is used to substitute the existing location spectrum data into the algorithm for one-dimensional calculation. If the amplitude of the data point is greater than the threshold, it is judged as a defect point and retained; otherwise, it is judged as a non-defective point and the data is set to zero, so as to extract the position of the actual defect point. The present invention can adaptively change the threshold, extract the position and peak value of the defect in the location spectrum, and reduce the misjudgment caused by human subjective factors and objective factors on the test site. The present invention proposes a frequency domain reflection-constant false alarm rate cable defect joint location method, extracts the impedance discontinuity points of the actual cable under complex conditions, and verifies the detection effect of the method on weak defects through simulation and experiment, which solves the problem of misjudgment of defect points to a certain extent. BRIEF DESCRIPTION OF THE DRAWINGS

[0047] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings required for use in the embodiments are briefly introduced below. It should be understood that the following drawings only show certain embodiments of the present invention and therefore should not be regarded as limiting the scope. For ordinary technicians in this field, other related drawings can be obtained based on these drawings without creative work.

[0048] Figure 1 is a flow chart of the method of the present invention;

[0049] Figure 2 is a schematic diagram of the system of the present invention;

[0050] Figure 3 This is a schematic diagram of an equivalent model of cable distribution parameters according to an embodiment of the present invention;

[0051] Figure 4 This is a FDR location diagram of cable defects in an embodiment of the present invention;

[0052] Figure 5 This is a schematic diagram of the mean-class CFAR according to an embodiment of the present invention;

[0053] Figure 6 The embodiment of the present invention simulates the cable GO-CFAR defect detection effect, wherein: Figure 6 (a) is the original positioning spectrum and threshold, Figure 6 (b) is the improved positioning spectrum;

[0054] Figure 7 A schematic diagram of a platform for implementing an embodiment of the present invention;

[0055] Figure 8 The following are the diagnostic results of different cable samples according to the embodiments of the present invention, where: Figure 8 (a) is the diagnostic results of cable samples No. 1 to 5. Figure 8 (b) is the diagnostic result of cable samples No. 6 to No. 9. Figure 8 (c) is the diagnostic result of cable No. 10 sample. Figure 8 (d) is the traditional FDR diagnosis result of cable sample No. 10;

[0056] Fig. 9 It is a schematic diagram of the computer device structure of the present invention. DETAILED DESCRIPTION

[0057] In order to make the purpose, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Generally, the components of the embodiments of the present invention described and shown in the drawings here can be arranged and designed in various different configurations.

[0058] Therefore, the following detailed description of the embodiments of the present invention provided in the accompanying drawings is not intended to limit the scope of the invention claimed for protection, but merely represents selected embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0059] It should be noted that similar reference numerals and letters denote similar items in the following drawings, and therefore, once an item is defined in one drawing, further definition and explanation thereof is not required in subsequent drawings.

[0060] In the description of the embodiments of the present invention, it should be noted that if the terms "upper", "lower", "horizontal", "inner", etc. indicate an orientation or positional relationship based on the orientation or positional relationship shown in the drawings, or the orientation or positional relationship in which the product of the invention is usually placed when in use, it is only for the convenience of describing the present invention and simplifying the description, and does not indicate or imply that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as a limitation on the present invention. In addition, the terms "first", "second", etc. are only used to distinguish the description, and cannot be understood as indicating or implying relative importance.

[0061] In addition, if the term "horizontal" appears, it does not mean that the component must be absolutely horizontal, but can be slightly tilted. For example, "horizontal" only means that its direction is more horizontal than "vertical", which does not mean that the structure must be completely horizontal, but can be slightly tilted.

[0062] In the description of the embodiments of the present invention, it is also necessary to explain that, unless otherwise clearly specified and limited, the terms "set", "install", "connect", and "connect" should be understood in a broad sense, for example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection, or it can be indirectly connected through an intermediate medium, or it can be the internal connection of two components. For ordinary technicians in this field, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0063] The present invention is further described in detail below in conjunction with the accompanying drawings:

[0064] See also Figure 1 The embodiment of the present invention discloses a cable defect location method based on frequency domain reflection-constant false alarm rate, comprising the following steps:

[0065] S1, calculating the impedance spectrum of the head end of the defective cable according to the distribution parameters of the defective cable, and performing discrete Fourier transform on the impedance spectrum of the head end to extract characteristic information of the impedance spectrum, so as to obtain a cable defect location spectrum;

[0066] Principle of cable head-end impedance spectrum positioning:

[0067] According to transmission line theory, when the cable is very long or the signal frequency is high, the cable's signal propagation characteristics need to be described by a distributed parameter model. In this case, the cable can be regarded as a cascade of infinitely many infinitely small distributed parameter element circuits, such as Figure 3 , R0, L0, G0, and C0 represent the distributed resistance, distributed inductance, distributed capacitance, and distributed conductance per unit length of the transmission line, respectively.

[0068] For the distributed parameters of the cable, R0, L0, G0, and C0 can be expressed as:

[0069]

[0070] Where, angular frequency ω = 2πf; r c and r s is the cable core radius and the inner radius of the metal shielding layer; ρ c and ρ s are the resistivity of the cable core and the metal shielding layer respectively; μ0 is the magnetic permeability of vacuum; ε and σ are the dielectric constant and conductivity of the dielectric respectively.

[0071] According to the transmission line theory, the impedance spectrum of the first end of a cable with a length of l can be calculated as:

[0072]

[0073] Where Z0 is the characteristic impedance; Γ Lis the reflection coefficient at the end of the cable; γ is the propagation coefficient of the cable; they are respectively expressed as:

[0074]

[0075] In the formula, Z L is the load impedance at the end of the cable; α is the attenuation coefficient, which characterizes the attenuation characteristics of the signal; β is the phase coefficient, which satisfies β=2πf / v, and characterizes the phase lag characteristics of the signal; v is the propagation speed of the electromagnetic wave in the cable.

[0076] When the cable end is open, Γ L =1, expand formula (5) using Euler's formula, and only take its imaginary part for analysis, and we get:

[0077]

[0078] In the formula, Im(Z l ) is the impedance spectrum of the first end Z l Part of the imaginary part, without considering the attenuation factor e -2αl From formula (6), we can see that the frequency component f l =2l / v, which is equivalent to the round-trip propagation time of the signal from the cable head end to the point l away from the head end, so it can be processed to obtain the defect position of the cable. This paper uses Discrete Fourier Transform (DFT) to obtain the positioning spectrum Loc:

[0079] Loc=abs(DFT(Im(Z l ))) (10)

[0080] Where DFT(·) is discrete Fourier transform and abs(·) is the modulus value.

[0081] For a 1000m simulated cable, a 50Ω ground fault is set at 500m, and the positioning spectrum is obtained as follows: Figure 4 As shown in the figure, there are two obvious peaks, which represent the impedance discontinuity points of the cable, namely the defect at 500m and the end of the cable at 1000m. It can be seen that under ideal conditions, this method has a good effect on identifying centralized defects such as low-resistance grounding faults.

[0082] S2, the data in the cable defect location spectrum is calculated in one dimension through the mean-type CFAR algorithm. If the amplitude of the data point is greater than the threshold, it is judged as a defect point and retained; if the amplitude of the data point is less than or equal to the threshold, it is judged as a non-defective point and the data is set to zero, thereby completing the extraction and location of the defect point.

[0083] In the above detection of cable defects using FDR, the defect is mainly reflected in the positioning spectrum by the size of its peak. Most of the current defect identification methods rely on manual identification. In actual tests, due to the spectrum leakage problem caused by Fourier transform and the influence of noise on the test site, "pseudo-peaks" will appear in the positioning spectrum. Considering that the tester's judgment on the defect location is relatively subjective, misjudgment is easy to occur. CFAR is a common method used in the field of radar communication to determine whether the detected object is the target object, which is exactly the same as the purpose of cable defect identification. Therefore, CFAR can be introduced into FDR to locate cable defects to identify defects and reduce human misjudgment.

[0084] The principle of CFAR is to obtain the power level estimate of the background by processing the sampling values ​​of the reference units around the unit to be detected in real-time echo data, and then calculate the detection threshold of the unit to be detected based on the estimated background power level. The mean CFAR is the first to be proposed and the most widely used and important type of CFAR. Its core idea is to use the processing result of the reference window mean as the background power level estimate, multiply it with the threshold multiplication factor to obtain the detection threshold, and then make a comparison to determine whether there is a target or not;

[0085] like Figure 5 As shown in the figure, the reference unit is located on both sides of the unit to be detected, with n units in front and behind; there is one unit on each side of the protection unit, which mainly plays the role of preventing the target energy from leaking to the reference unit in the case of a single target. The detection threshold T = αZ, where α is the threshold multiplication factor. If the amplitude of the unit to be detected is greater than the threshold T, it is determined that the target exists; otherwise, the target does not exist.

[0086] The choice of mean Z determines different processing methods. In order to obtain a higher threshold level to eliminate the interference of "pseudo-peaks", the unit maximum selection constant false alarm rate (Greatest of CFAR, GO-CFAR) processing method is adopted. The core idea is to take the average of the front and back reference window sampling values ​​and then select the larger one as the background power level estimate. For the data in N (N = 2n) reference cells, there are:

[0087]

[0088]

[0089] Z=max(X,Y) (13)

[0090] Assume that in a uniform environment H0, due to x i Independent and identically distributed, so X and Y are also independent and identically distributed, and both obey Γ distribution, and their probability density function is:

[0091]

[0092] Where a and b are two parameters of Γ distribution; Γ(·) is the Γ function, and for integer a, Γ(a)=(a-1)!.

[0093] In the process of calculating the expected value of the false alarm probability, the relationship between the false alarm probability, the number of reference units and the threshold product factor can be calculated more simply according to the properties of the moment generating function. The moment generating function of Z can be obtained according to the probability theory formula, and then the false alarm probability of GO-CFAR in a uniform environment can be obtained as follows:

[0094]

[0095] Formula (15) shows that after determining the threshold coefficient α and the number of reference units n, the false alarm probability remains unchanged, that is, the constant false alarm rate. Next, we only need to substitute the data in the original positioning spectrum into the GO-CFAR algorithm for one-dimensional calculation to obtain a new positioning spectrum.

[0096] For a 1000m simulated cable, a 1500Ω high-resistance fault is set at 700m. The simulation results are as follows: Figure 6 It can be seen that the defect peak of high resistance fault is not obvious, such as Figure 6 (a). But using GO-CFAR

[0097] The algorithm can give an adaptive judgment threshold according to the signal background power level and successfully detect the high-resistance fault at 700m with obvious characteristics. Figure 6 (b) This shows that this method can be applied to cable defect identification.

[0098] See also Figure 2 The embodiment of the present invention discloses a cable defect location system based on frequency domain reflection-constant false alarm rate, including a location spectrum module and a defect location module. The location spectrum module is used to calculate the impedance spectrum of the head end of the defective cable according to the distribution parameters of the defective cable, and to perform discrete Fourier transform on the impedance spectrum of the head end to extract the characteristic information of the impedance spectrum, so as to obtain a cable defect location spectrum; the defect location module is used to perform one-dimensional calculation on the data in the cable defect location spectrum through a mean-type CFAR algorithm, and if the amplitude of the data point is greater than a threshold, it is judged as a defect point and retained; if the amplitude of the data point is less than or equal to the threshold, it is judged as a non-defective point and the data is set to zero, thereby completing the extraction and location of the defect point.

[0099] See also Figure 7 The embodiment of the present invention discloses a platform for implementing a method for locating cable defects based on frequency domain reflection and constant false alarm rate. The working process of the platform is as follows:

[0100] (1) The computer assigns signal parameters and inputs them into the signal generator;

[0101] (2) The actual signal generated by the signal generator is used as the incident signal and enters the cable under test through the directional coupler;

[0102] (3) The reflected signal generated by the cable under test enters the oscilloscope through the directional coupler and is collected;

[0103] (4) The oscilloscope transmits the collected incident signal and reflected signal to the computer;

[0104] (5) The computer processes the incident signal and the reflected signal and calculates the impedance spectrum of the first end according to the formula;

[0105] (6) The computer processes the impedance spectrum data of the first end using the CFAR algorithm and draws a diagnostic spectrum;

[0106] (7) Locate local defects by detecting the mutation position of the diagnostic function value in the diagnostic map.

[0107] Example:

[0108] The signal transmission characteristics of coaxial cables are similar to those of power cables. To verify the effectiveness of the method proposed in this paper, SYV50-3-4 RF cables with a total length of 800m and 870m were tested in the laboratory. During the experiment, the sheath and insulation layer of the RF cable were stripped, and the transition resistor was connected between the core and the shielding layer to simulate a high-resistance fault. The sweep frequency range was set to 300kHz~50MHz, and the number of sweep points was 50001. Cable No. 1 is a sound cable; cables No. 2 to No. 9 are single-point defect cables; and No. 10 is a multi-point defect cable.

[0109] The coaxial cable samples were tested using the FDR-CFAR joint positioning method. The results are as follows: Figure 8 shown. Figure 8 (a) shows that the defect peaks corresponding to different transition resistance values ​​at the same position are not the same. The weaker the defect, the smaller the corresponding positioning peak, that is, the lower the positioning sensitivity. Figure 8 (b) shows that when defects with the same transition resistance value exist at different locations, the positioning sensitivity becomes lower as it approaches the end of the cable. Figure 8 (c) shows that this method can identify multiple defects occurring on the same cable.

[0110] In summary, the method proposed in the present invention can effectively locate centralized defects such as single-point and multi-point high-resistance faults in cables. Figure 8 (d) shows the positioning effect of the traditional FDR using the BIS method on the No. 10 multi-point defect cable. It can be seen that the defect at 570m can be barely identified, but the defect peak at 500m has been obscured, indicating that the defect at this point is quite weak. In actual testing, the defect at this point will be ignored, which will bring certain hidden dangers to the power system. Figure 8 (c) The defects at 500 m were intuitively identified. This comparison also confirms that the method proposed in this paper can significantly improve the recognition of subtle defects in the cable.

[0111] The present invention aims at the problem of misjudgment in the detection of cable defects by traditional FDR, introduces CFAR algorithm to improve the positioning spectrum, and verifies it through numerical simulation and experimental tests. Due to the subjective and objective factors in actual testing, in order to improve the recognition of defects, this patent proposes a FDR-CFAR cable defect joint positioning method, extracts the impedance discontinuity points of actual cables under complex conditions, verifies the detection effect of this method on weak defects through simulation and experiments, and solves the problem of misjudgment of defect points to a certain extent.

[0112] In one embodiment of the present invention, see Fig. 9 , a computer device is provided, the computer device includes a processor and a memory, the memory is used to store a computer program, the computer program includes program instructions, and the processor is used to execute the program instructions stored in the computer storage medium. The processor may be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gates or transistor logic devices, discrete hardware components, etc. It is the computing core and control core of the terminal, which is suitable for implementing one or more instructions, and is specifically suitable for loading and executing one or more instructions in the computer storage medium to implement the corresponding method flow or corresponding function; the processor described in the embodiment of the present invention can be used for the operation of the cable defect location method based on frequency domain reflection-constant false alarm rate.

[0113] The present invention also provides a storage medium, specifically a computer-readable storage medium (Memory), which is a memory device in a computer device for storing programs and data. It is understandable that the computer-readable storage medium here can include both built-in storage media in the computer device and, of course, extended storage media supported by the computer device. The computer-readable storage medium provides a storage space, which stores the operating system of the terminal. In addition, one or more instructions suitable for being loaded and executed by the processor are also stored in the storage space, and these instructions can be one or more computer programs (including program codes). It should be noted that the computer-readable storage medium here can be a high-speed RAM memory or a non-volatile memory (non-volatile memory), such as at least one disk memory. The processor can load and execute one or more instructions stored in the computer-readable storage medium to implement the corresponding steps of the cable defect location method based on frequency domain reflection-constant false alarm rate in the above embodiment.

[0114] Those skilled in the art will appreciate that embodiments of the present invention may be provided as methods, systems, or computer program products. Therefore, the present invention may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0115] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present invention. 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.

[0116] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate 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 1A function specified in one or more boxes.

[0117] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0118] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the above embodiments, ordinary technicians in the relevant field should understand that the specific implementation methods of the present invention can still be modified or replaced by equivalents. Any modification or equivalent replacement that does not depart from the spirit and scope of the present invention should be covered within the scope of protection of the claims of the present invention.

Claims

1. A cable defect location method based on frequency domain reflection-constant false alarm rate, characterized in that: The following steps are involved: Calculating the impedance spectrum of the first end of the defective cable according to the distribution parameters of the defective cable, and performing discrete Fourier transform on the impedance spectrum of the first end to extract characteristic information of the impedance spectrum, so as to obtain a cable defect location spectrum; The data in the cable defect location spectrum are calculated in one dimension using the mean-type CFAR algorithm. If the amplitude of a data point is greater than the threshold, it is judged as a defect point and retained. If the amplitude of the data point is less than or equal to the threshold, it is judged as a non-defective point and the data is set to zero, thereby completing the extraction and positioning of the defect point.

2. A cable defect location method based on frequency domain reflection-constant false alarm rate according to claim 1, characterized in that: The step of calculating the impedance spectrum of the first end of the defective cable according to the distribution parameters of the defective cable, and performing fast Fourier transform on the impedance spectrum of the first end to extract characteristic information of the impedance spectrum to obtain the cable defect location spectrum specifically includes: According to the distribution parameters of the defective cable, the impedance spectrum of the first end of the defective cable is calculated by transmission line theory. The specific calculation formula is: Where Z0 is the characteristic impedance; Γ L is the reflection coefficient at the end of the cable; γ is the propagation coefficient of the cable; The impedance spectrum characteristic information is extracted from the head-end impedance spectrum by discrete Fourier transform to obtain the cable defect location spectrum Loc. The specific formula is: Loc=abs(DFT(Im(Z l ))) Where DFT(·) is discrete Fourier transform and abs(·) is the modulus value.

3. A cable defect location method based on frequency domain reflection-constant false alarm rate according to claim 2, characterized in that: The calculation formula of the characteristic impedance Z0 is: Where, R0 is the distributed resistance per unit length of the transmission line; G0 is the distributed conductance per unit length of the transmission line; j is the imaginary unit; ω is the angular frequency; L0 is the distributed inductance per unit length of the transmission line; C0 is the distributed capacitance per unit length of the transmission line; The cable end reflection coefficient Γ L The calculation formula is: In the formula, Z L is the load impedance at the end of the cable; Z0 is the characteristic impedance; The calculation formula of the propagation coefficient γ of the cable is: Where α is the attenuation coefficient and β is the phase coefficient.

4. A cable defect location method based on frequency domain reflection-constant false alarm rate according to claim 3, characterized in that: The distributed parameters of the defective cable include the distributed resistance R0 per unit length of the transmission line, the distributed inductance L0 per unit length of the transmission line, the distributed conductance G0 per unit length of the transmission line, and the distributed capacitance C0 per unit length of the transmission line.

5. A cable defect location method based on frequency domain reflection-constant false alarm rate according to claim 4, characterized in that: The calculation formula of the distributed resistance R0 per unit length of the transmission line is: Where μ0 is the vacuum magnetic permeability; r c is the cable core radius; r s is the inner radius of the metal shielding layer; ρ c is the cable core resistivity; ρ s is the resistivity of the metal shielding layer; The calculation formula of the distributed inductance L0 per unit length of the transmission line is: The calculation formula of the distributed conductance G0 per unit length of the transmission line is: Where σ is the conductivity of the dielectric; The calculation formula of the distributed capacitance C0 per unit length of the transmission line is: Where ε is the dielectric constant of the dielectric.

6. The cable defect location method based on frequency domain reflection-constant false alarm rate according to claim 1 is characterized in that: The mean-type CFAR algorithm includes a detection unit and 2n reference units; n reference units are arranged on both sides of the detection unit, and a protection unit is arranged between the detection unit and the reference unit; the CFAR algorithm calculates the mean value Z through the data in the 2n reference units, thereby calculating the detection threshold T=αZ, where α is the threshold multiplication factor; If the detection unit amplitude is greater than the threshold T, it is determined that the target exists; Otherwise the target does not exist.

7. The cable defect location method based on frequency domain reflection-constant false alarm rate according to claim 1 is characterized in that: The step of performing one-dimensional calculation on the data in the cable defect location spectrum through the mean-type CFAR algorithm specifically includes: after determining the threshold coefficient α and the number of reference units n of the mean-type CFAR algorithm, keeping the false alarm probability unchanged, and then substituting the data in the cable defect location spectrum into the mean-type CFAR algorithm for one-dimensional calculation.

8. A cable defect location system based on frequency domain reflection-constant false alarm rate, characterized in that: include: A positioning spectrum module is used to calculate the impedance spectrum of the head end of the defective cable according to the distribution parameters of the defective cable, and to perform discrete Fourier transform on the impedance spectrum of the head end to extract the characteristic information of the impedance spectrum, so as to obtain a cable defect positioning spectrum; The defect location module is used to perform one-dimensional calculation on the data in the cable defect location spectrum using the mean-type CFAR algorithm. If the amplitude of a data point is greater than a threshold, it is judged as a defect point and retained; If the amplitude of the data point is less than or equal to the threshold, it is judged as a non-defective point and the data is set to zero, thereby completing the extraction and positioning of the defect point.

9. A computer device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 7 are implemented.

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