CN118962343B

CN118962343B - FDR defect location method based on k-means clustering and fractional Fourier transform

Info

Publication number: CN118962343B
Application number: CN202411455868.0A
Authority: CN
Inventors: 宋鹏先; 朱明正; 唐庆华; 李旭; 孟峥峥; 张华�; 李隆基; 李季; 林国洲; 胡泉伟; 于洋; 姜涛; 陈荣; 安家慧; 唐志荣; 周凯; 李泽瑞
Original assignee: State Grid Corp of China SGCC; State Grid Tianjin Electric Power Co Ltd; Electric Power Research Institute of State Grid Tianjin Electric Power Co Ltd
Current assignee: State Grid Corp of China SGCC; State Grid Tianjin Electric Power Co Ltd; Electric Power Research Institute of State Grid Tianjin Electric Power Co Ltd
Priority date: 2024-10-18
Filing date: 2024-10-18
Publication date: 2025-01-14
Anticipated expiration: 2044-10-18
Also published as: CN118962343A

Abstract

The invention provides an FDR defect positioning method based on k-means clustering and fractional Fourier transform, which can be applied to the technical field of high voltage. The method comprises the steps of introducing different sweep signals into a cable to be detected according to the same sampling mode to obtain an initial reflection coefficient spectrum set, clustering the initial reflection coefficient spectrum set to obtain a plurality of reflection coefficient spectrum clustering clusters, respectively performing spectrum leakage reduction pretreatment on a plurality of reflection coefficient spectrums obtained based on the plurality of reflection coefficient spectrum clustering clusters to obtain a plurality of target reflection coefficient spectrums, respectively performing fractional Fourier transform on the plurality of target reflection coefficient spectrums to obtain a plurality of two-dimensional time-frequency spectrograms, respectively performing spectrogram conversion on the plurality of two-dimensional time-frequency spectrograms to obtain a plurality of positioning graphs for defect detection, and obtaining a defect detection result of the cable to be detected based on the plurality of positioning graphs.

Description

FDR defect positioning method based on k-means clustering and fractional Fourier transform

Technical Field

The invention relates to the technical field of high voltage, in particular to an FDR defect positioning method based on k-means clustering and fractional Fourier transform.

Background

The safety and stability of the cable, which is an important carrier for power transmission, are directly related to the normal operation of the power system. However, since the cable is operated in a complicated environment for a long period of time, it is affected by various factors such as damage by external force, insulation aging, moisture invasion, etc., various defects are liable to occur. These defects, if not found and handled in time, can lead to cable failure and even fire disasters, among other serious consequences. Therefore, the accurate and rapid positioning of the cable defect is of great significance in ensuring the safe operation of the power system. The frequency domain reflectometry (frequency domain reflectometry, FDR) is a widely used method for detecting cable defects, which is capable of locating cable defects by analyzing frequency domain signals.

In the process of implementing the invention, at least the following problems are found in the prior art, and the frequency of the reflected wave is changed along with the acquisition time due to the influence of the dispersion effect, and further the generation of simple harmonic is caused, so that a false peak exists in a defect positioning map, the detection precision is low, and the defect is easy to misjudge.

Disclosure of Invention

In view of the above, the invention provides a FDR defect positioning method based on k-means clustering and fractional Fourier transform.

According to a first aspect of the invention, there is provided a method for locating FDR defects based on k-means clustering and fractional Fourier transform, comprising the steps of introducing different sweep frequency signals to a cable to be detected according to the same sampling mode to obtain an initial reflection coefficient spectrum set; the method comprises the steps of clustering an initial reflection coefficient spectrum set to obtain a plurality of reflection coefficient spectrum clustering clusters, respectively performing spectrum leakage reduction pretreatment on a plurality of reflection coefficient spectrums obtained based on the plurality of reflection coefficient spectrum clustering clusters to obtain a plurality of target reflection coefficient spectrums, respectively performing fractional Fourier transform on the plurality of target reflection coefficient spectrums to obtain a plurality of two-dimensional time-frequency spectrums, respectively performing spectrogram conversion on the plurality of two-dimensional time-frequency spectrums to obtain a plurality of positioning graphs used for defect detection, and obtaining defect detection results of a cable to be detected based on the plurality of positioning graphs, respectively performing spectrum leakage reduction pretreatment on the plurality of reflection coefficient spectrums obtained based on the plurality of reflection coefficient spectrum clustering clusters to obtain a plurality of target reflection coefficient spectrums, respectively adding window functions to the reflection coefficient spectrums, respectively performing bilinear transformation on the reflection coefficient spectrums added with the window functions to obtain target reflection coefficient spectrums, performing bilinear transformation on the reflection coefficient spectrums added with the window functions to obtain the target reflection coefficient spectrums, and performing convolution function-added reflection coefficient conjugate function to obtain the target reflection coefficient spectrums.

According to the embodiment of the invention, different sweep signals are introduced into the cable to be detected according to the same sampling mode to obtain an initial reflection coefficient spectrum set, wherein the signal acquisition is carried out on the cable to be detected which is introduced with different sweep signals according to the same sampling frequency and the same sampling point number to obtain the initial reflection coefficient spectrum set, and the sweep signals comprise angular frequencies of 0.15MHz-100 MHz.

According to the embodiment of the invention, the initial reflection coefficient spectrum set is clustered to obtain a plurality of reflection coefficient spectrum clustering clusters, wherein the clustering of the initial reflection coefficient spectrum set is based on the preset clustering number and the signal information of the sweep frequency signal to obtain a plurality of reflection coefficient spectrum clustering clusters.

According to the embodiment of the invention, fractional Fourier transform is respectively carried out on a plurality of target reflection coefficient spectrums to obtain a plurality of two-dimensional time-frequency spectrograms, wherein the fractional Fourier transform is carried out on the target reflection coefficient spectrums by adding a rotation angle to obtain the two-dimensional time-frequency spectrograms.

According to the embodiment of the invention, spectrogram conversion is respectively carried out on a plurality of two-dimensional time-frequency spectrograms to obtain a plurality of positioning graphs for defect detection, wherein the method comprises the steps of carrying out pseudo-peak suppression processing on rotation angles in the two-dimensional time-frequency spectrograms to obtain a pseudo-peak suppression spectrogram, carrying out time domain integration on the pseudo-peak suppression spectrogram to obtain a frequency response function, and carrying out spectrogram conversion on the frequency response function to obtain the positioning graphs.

According to the embodiment of the invention, the defect detection result of the cable to be detected is obtained based on a plurality of positioning graphs, and the defect detection result is obtained based on the respective amplitude values of the plurality of target positioning graphs.

The second aspect of the present invention provides an FDR defect localization device based on k-means clustering and fractional fourier transform, including:

The signal sampling module is used for introducing different sweep frequency signals to the cable to be detected according to the same sampling mode to obtain an initial reflection coefficient spectrum set;

The set clustering module is used for clustering the initial reflection coefficient spectrum set to obtain a plurality of reflection coefficient spectrum clustering clusters;

The digital spectrum preprocessing module is used for respectively preprocessing a plurality of reflection coefficient spectrums obtained based on a plurality of reflection coefficient spectrum clustering clusters to reduce spectrum leakage and obtain a plurality of target reflection coefficient spectrums;

The digital spectrum conversion module is used for respectively carrying out fractional Fourier transform on the multiple target reflection coefficient spectrums to obtain multiple two-dimensional time-frequency spectrograms;

The spectrogram conversion module is used for respectively carrying out spectrogram conversion on the two-dimensional time-frequency spectrograms to obtain a plurality of positioning graphs for defect detection;

And the result determining module is used for obtaining a defect detection result of the cable to be detected based on the plurality of positioning graphs.

A third aspect of the invention provides an electronic device comprising one or more processors and a memory for storing one or more computer programs, wherein the one or more processors execute the one or more computer programs to implement the steps of the method.

A fourth aspect of the invention also provides a computer readable storage medium having stored thereon a computer program or instructions which when executed by a processor performs the steps of the above method.

The fifth aspect of the invention also provides a computer program product comprising a computer program or instructions which, when executed by a processor, carries out the steps of the method described above.

According to the embodiment of the invention, different sweep frequency signals are introduced into the cable to be detected, the same sampling mode is used for sampling, and the initial reflection coefficient spectrum set obtained by sampling is clustered to obtain a plurality of reflection coefficient spectrum clustering clusters, so that the effects of reducing noise and reducing errors are realized. And carrying out pretreatment for reducing frequency spectrum leakage on the reflection coefficient spectrum clustering cluster to obtain a target reflection coefficient spectrum, thereby further reducing errors caused by frequency spectrum leakage. After fractional Fourier transform and spectrogram transformation are carried out on the target reflection coefficient spectrum, the two-dimensional spectrogram is converted into a one-dimensional spectrogram, a plurality of positioning graphs for defect detection are obtained, and the defect detection precision is improved. And determining a defect detection result of the cable to be detected by analyzing the positioning curve graph. In summary, the invention achieves the effects of reducing errors and improving the cable defect detection precision through various processing means.

Drawings

The foregoing and other objects, features and advantages of the invention will be apparent from the following description of embodiments of the invention with reference to the accompanying drawings, in which:

FIG. 1 illustrates a flow chart of a method for FDR defect localization based on k-means clustering and fractional Fourier transform in accordance with an embodiment of the invention;

FIG. 2 shows a schematic view of a rotation angle according to an embodiment of the invention;

FIG. 3 shows a schematic diagram of a two-dimensional time-frequency spectrogram in accordance with an embodiment of the present invention;

FIG. 4 is a diagram showing the positioning results of a simulation model according to an embodiment of the present invention and a frequency domain reflection method;

FIG. 5 shows a block diagram of an FDR defect localization apparatus based on k-means clustering and fractional Fourier transform in accordance with an embodiment of the invention;

FIG. 6 illustrates a block diagram of an electronic device suitable for implementing a FDR defect localization method based on k-means clustering and fractional Fourier transform in accordance with an embodiment of the invention.

Detailed Description

Hereinafter, embodiments of the present invention will be described with reference to the accompanying drawings. It should be understood that the description is only illustrative and is not intended to limit the scope of the invention. In the following detailed description, for purposes of explanation, numerous specific details are set forth in order to provide a thorough understanding of the embodiments of the invention. It may be evident, however, that one or more embodiments may be practiced without these specific details. In addition, in the following description, descriptions of well-known structures and techniques are omitted so as not to unnecessarily obscure the present invention.

The terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention. The terms "comprises," "comprising," and/or the like, as used herein, specify the presence of stated features, steps, operations, and/or components, but do not preclude the presence or addition of one or more other features, steps, operations, or components.

All terms (including technical and scientific terms) used herein have the same meaning as commonly understood by one of ordinary skill in the art unless otherwise defined. It should be noted that the terms used herein should be construed to have meanings consistent with the context of the present specification and should not be construed in an idealized or overly formal manner.

Where a convention analogous to "at least one of A, B and C, etc." is used, in general such a convention should be interpreted in accordance with the meaning of one of skill in the art having generally understood the convention (e.g., "a system having at least one of A, B and C" would include, but not be limited to, systems having a alone, B alone, C alone, a and B together, a and C together, B and C together, and/or A, B, C together, etc.).

In the technical scheme of the invention, the related user information (including but not limited to user personal information, user image information, user equipment information, such as position information and the like) and data (including but not limited to data for analysis, stored data, displayed data and the like) are information and data authorized by a user or fully authorized by all parties, and the related data are collected, stored, used, processed, transmitted, provided, disclosed, applied and the like, all comply with related laws and regulations and standards, necessary security measures are adopted, no prejudice to the public order is provided, and corresponding operation entries are provided for the user to select authorization or rejection.

In the scene of using personal information to make automatic decision, the method, the device and the system provided by the embodiment of the invention provide corresponding operation inlets for users to choose to agree or reject the automatic decision result, and enter an expert decision flow if the users choose to reject. The expression "automated decision" here refers to an activity of automatically analyzing, assessing the behavioral habits, hobbies or economic, health, credit status of an individual, etc. by means of a computer program, and making a decision. The expression "expert decision" here refers to an activity of making a decision by a person who is specializing in a certain field of work, has specialized experience, knowledge and skills and reaches a certain level of expertise.

Noise is also generated by attenuation of the test signal to distortion due to noise in the measurement environment, which affects the accuracy of defect detection.

The embodiment of the invention provides an FDR defect positioning method based on k-means clustering and fractional Fourier transform, which comprises the steps of introducing different sweep signals into a cable to be detected according to the same sampling mode to obtain an initial reflection coefficient spectrum set, clustering the initial reflection coefficient spectrum set to obtain a plurality of reflection coefficient spectrum clustering clusters, respectively performing spectrum leakage reduction pretreatment on the reflection coefficient spectrums obtained based on the reflection coefficient spectrum clustering clusters to obtain a plurality of target reflection coefficient spectrums, respectively performing fractional Fourier transform on the target reflection coefficient spectrums to obtain a plurality of two-dimensional time-frequency spectrograms, respectively performing spectrogram conversion on the two-dimensional time-frequency-spectrograms to obtain a plurality of positioning graphs for defect detection, and obtaining a defect detection result of the cable to be detected based on the positioning graphs.

FIG. 1 illustrates a flow chart of a method for FDR defect localization based on k-means clustering and fractional Fourier transform in accordance with an embodiment of the invention.

As shown in FIG. 1, the FDR defect localization method based on k-means clustering and fractional Fourier transform of the embodiment comprises operations S110-S160.

In operation S110, different sweep signals are introduced into the cable to be detected according to the same sampling mode, so as to obtain an initial reflection coefficient spectrum set.

According to an embodiment of the invention, the cable to be inspected comprises a cable for which cable defect detection is required to determine whether a defect exists. The sampling mode comprises parameters such as sampling frequency, sampling point number and the like, wherein the sampling frequency is the frequency for carrying out signal acquisition on the cable to be detected after the sweep frequency signal is introduced, and the sampling point number is the number of positions for sampling when the cable to be detected after the sweep frequency signal is introduced is subjected to signal acquisition.

According to an embodiment of the present invention, the sweep signal is a signal whose frequency varies linearly or non-linearly with time, and the sweep signal may be generated by a modulation technique, for example, using a direct digital synthesis technique or a frequency modulation technique in an analog circuit, and may also be generated by a software algorithm.

According to the embodiment of the invention, after the sampling mode is determined, different sweep signals are introduced into the cable to be detected for a plurality of times, so that a plurality of initial reflection coefficient spectrums are obtained, and an initial reflection coefficient spectrum set is determined.

In operation S120, the initial set of reflection coefficient spectrums is clustered to obtain a plurality of clusters of reflection coefficient spectrums.

According to the embodiment of the invention, after the initial reflection coefficient spectrum set is mapped into the feature space and a plurality of nodes corresponding to the initial reflection coefficient spectrum set are determined, a plurality of nodes corresponding to the initial reflection coefficient spectrum set can be clustered by using a center-based clustering algorithm to obtain a plurality of reflection coefficient spectrum cluster clusters, wherein the center-based clustering algorithm can minimize the sum of distances from each node to the nearest centroid by iteratively moving the centroid, and each reflection coefficient spectrum cluster comprises one centroid and a plurality of nodes taking the cluster center as the center.

In operation S130, a plurality of reflection coefficient spectrums obtained based on the plurality of reflection coefficient spectrum clustering clusters are respectively subjected to a spectrum leakage reduction preprocessing to obtain a plurality of target reflection coefficient spectrums.

According to the embodiment of the invention, in the frequency domain analysis, particularly when the frequency domain signal is not periodic or the length of the frequency domain signal is not an integer multiple of the sampling frequency, a spectrum leakage phenomenon may occur, and the spectrum leakage may cause signal energy which should be concentrated at a specific frequency to be dispersed to other frequencies, thereby causing the accuracy of the spectrum analysis result to be reduced.

According to an embodiment of the present invention, in order to reduce spectrum leakage during frequency domain analysis, the signal may be preprocessed by adding a window function, filling 0 into the signal to increase the signal length, signal overlap, periodically expanding the signal, and so on. The addition of the window function is to apply the window function to the frequency domain signal to reduce abrupt changes at both ends of the signal before fourier transforming the frequency domain signal, thereby reducing spectral leakage. Filling the signal with 0's to increase the signal length may increase spectral resolution to reduce spectral leakage. Signal overlap may be achieved by having an overlap between two adjacent segments of the signal and applying a window function in the overlap region to reduce spectral leakage due to segment-to-segment discontinuities. The periodic expansion of the signal can change the signal into a periodic signal, thereby avoiding the situation of frequency spectrum leakage during Fourier transformation.

According to the embodiment of the invention, one reflection coefficient spectrum is determined based on each reflection coefficient spectrum cluster, and a plurality of target reflection coefficient spectrums are determined after a plurality of reflection coefficient spectrums are processed by a preprocessing means for reducing spectrum leakage.

In operation S140, fractional fourier transform is performed on the multiple target reflection coefficient spectrums, respectively, to obtain multiple two-dimensional time-frequency spectrograms.

According to an embodiment of the present invention, the fractional fourier transform (Fractional Fourier Transform, frFT) is a variant of the conventional fourier transform, which is to transform a signal from the time domain to the frequency domain, while the FrFT allows a frequency domain analysis of the signal in non-integer order, i.e. a partial conversion between the time domain and the frequency domain, so that the FrFT can be used to analyze and process non-stationary signals, improving the flexibility and efficiency of signal processing.

According to the embodiment of the invention, the sweep frequency signal is introduced into the signal to be detected, so that the obtained initial reflection coefficient spectrum set, the reflection coefficient spectrum cluster, the reflection coefficient spectrum and the target reflection coefficient spectrum are all non-stationary signals, and fractional Fourier transform is respectively carried out on the target reflection coefficient spectrums to obtain a plurality of two-dimensional time-frequency spectrograms.

In operation S150, spectrum conversion is performed on the two-dimensional time-frequency spectrograms, respectively, to obtain a plurality of positioning graphs for defect detection.

According to the embodiment of the invention, the spectrograms are respectively converted to the two-dimensional time-frequency spectrograms, so that the two-dimensional time-frequency spectrograms are respectively converted into the corresponding one-dimensional signals, namely the positioning curve graph for defect detection.

In operation S160, a defect detection result of the cable to be detected is obtained based on the plurality of positioning graphs.

According to the embodiment of the invention, analysis is performed based on a plurality of positioning graphs, and a defect detection result of the cable to be detected is determined according to the analysis result, wherein the defect detection result can be used for representing whether the cable to be detected has a defect or not and determining the position of the defect in the cable to be detected if the defect exists.

According to the embodiment of the invention, different sweep frequency signals are introduced into the cable to be detected, the same sampling mode is used for sampling, and the initial reflection coefficient spectrum set obtained by sampling is clustered to obtain a plurality of reflection coefficient spectrum clustering clusters, so that the effects of reducing noise and reducing errors are realized. And carrying out pretreatment for reducing frequency spectrum leakage on the reflection coefficient spectrum clustering cluster to obtain a target reflection coefficient spectrum, thereby further reducing errors caused by frequency spectrum leakage. After fractional Fourier transform and spectrogram transformation are carried out on the target reflection coefficient spectrum, the two-dimensional spectrogram is converted into a one-dimensional spectrogram, a plurality of positioning graphs for defect detection are obtained, and the defect detection precision is improved. And determining a defect detection result of the cable to be detected by analyzing the positioning curve graph. Through multiple processing means, reach the effect that reduces the error, improve cable defect detection precision.

According to the embodiment of the invention, signal acquisition is carried out on the cables to be detected which are fed with different sweep signals according to the same sampling mode to obtain an initial reflection coefficient spectrum set, wherein the signal acquisition is carried out on the cables to be detected which are fed with different sweep signals according to the same sampling frequency and the same sampling point number to obtain the initial reflection coefficient spectrum set, and the sweep signals comprise angular frequencies of 0.15MHz-100 MHz.

According to the embodiment of the invention, different sweep signals are sequentially introduced into the cable to be detected, and after one sweep signal is introduced into the cable to be detected each time, signal acquisition is carried out on the cable to be detected according to the same sampling frequency and the same sampling point number to obtain an initial reflection coefficient spectrum, wherein the value range of the angular frequency of the sweep signal, which changes along with the time, is 0.15MHz-100MHz, and the different sweep signals can be sweep signals with the same change rule of the frequency along with the time, but different initial angular frequencies can also be sweep signals with different change rules of the frequency along with the time.

According to an embodiment of the present invention, an initial reflection coefficient spectrum set x (ω) is determined from a plurality of initial reflection coefficient spectrums corresponding to a plurality of different sweep signals, as shown in formula (1):

(1)

Wherein q is the number of sweep signals, A _i is the amplitude of the ith sweep signal, deltaf is the time interval of the sweep signals being fed into the cable to be detected, n is any integer, omega _i is the angular frequency of the ith sweep signal, ,Is the equivalent frequency of the ith sweep signal.

According to the embodiment of the invention, the signal acquisition is carried out on the cable to be detected, which is fed with the sweep signals with different angular frequencies, so that the detection result of the cable to be detected is comprehensively and accurately determined by analyzing the output of the cable to be detected on different sweep signals, and the accuracy of cable defect detection is improved.

According to an embodiment of the invention, the initial set of reflection coefficient spectra is clustered using a center-based clustering algorithm, such as a K-means algorithm.

According to an embodiment of the invention, the clustering is performed by determining a plurality of initial centroids in the feature space based on a predetermined number of clusters, wherein the predetermined number of clusters may include noise and non-noise, and thus the predetermined number of clusters may be determined according to the number of noise and the number of non-noise, and the positions of the plurality of initial centroids are randomly determined. And determining the distances between the corresponding nodes in the feature space and the initial centroids, and dividing each node into clusters corresponding to the centroids with the smallest distances. After the clusters are determined, re-determining respective middle centroids based on each cluster, and repeating the above operation until the centroid position is not changed, so as to complete the clustering of the initial reflection coefficient spectrum set and obtain the reflection coefficient spectrum cluster corresponding to the centroids.

According to the embodiment of the invention, the initial reflection coefficient spectrum is clustered, so that similar data points in the reflection coefficient spectrum are classified by utilizing the internal structure and the statistical property of the initial reflection coefficient spectrum, and the clustered cluster is noise or non-noise according to the clustered result because the matrix formed by the similar data points has low rank property and the matrix formed by the noise data points does not have the characteristic, thereby reducing noise.

According to the embodiment of the invention, the spectrum leakage reduction pretreatment is respectively carried out on a plurality of reflection coefficient spectrums obtained based on a plurality of reflection coefficient spectrum clustering clusters to obtain a plurality of target reflection coefficient spectrums, wherein the reflection coefficient spectrums corresponding to the respective centroids of the reflection coefficient spectrum clustering clusters are taken as the reflection coefficient spectrums, window functions are respectively added to the reflection coefficient spectrums, and the reflection coefficient spectrums added with the window functions are subjected to bilinear transformation to obtain the target reflection coefficient spectrums.

According to the embodiment of the invention, after the reflection coefficient spectrums corresponding to a plurality of centroids in the reflection coefficient spectrum cluster are used as the reflection coefficient spectrums, window functions are respectively added to each reflection coefficient spectrum to obtain the reflection coefficient spectrums x '(omega) added with the window functions, and the reflection coefficient spectrums x' (omega) are shown in a formula (2):

(2)

Wherein, kaiser (omega) is a window function, and Kaiser window function is a locally optimized window function with stronger capability, which can be used for adjusting the relation between the frequency spectrum parameters of the window function, thereby reducing the frequency spectrum leakage problem.

According to the embodiment of the invention, the reflection coefficient spectrum added with the window function can be further processed in a bilinear transformation mode, so that the influence caused by the non-periodic characteristic of the reflection coefficient spectrum added with the window function is reduced.

According to the embodiment of the invention, a plurality of clustered clusters obtained by clustering are respectively used as reflection coefficient spectrums, and the window function is added to perform bilinear transformation, so that the problem of frequency spectrum leakage is reduced, and the error of defect detection is reduced.

According to the embodiment of the invention, the reflection coefficient spectrum added with the window function is subjected to bilinear transformation to obtain a target reflection coefficient spectrum, and the convolution processing is carried out on the reflection coefficient spectrum added with the window function and the reflection coefficient spectrum added with the window function which is conjugated to obtain the target reflection coefficient spectrum.

According to the embodiment of the invention, the reflection coefficient spectrum x ' (omega) added with the window function is conjugated to obtain x ' ^* (omega), and the convolution processing is carried out on the x ' (omega) and the reflection coefficient spectrum added with the window function, which is conjugated, to obtain a target reflection coefficient spectrum x ' ' (omega), as shown in a formula (3):

(3)

Where conv [. Cndot. ] is the calculated convolution function, (. Cndot. ] ^* is the conjugation of the content in brackets.

According to the embodiment of the invention, the reflection coefficient spectrum added with the window function is convolved with the conjugate thereof, so that the information of the signal can be enhanced according to the self-similarity of the signal, the noise can be suppressed, and the error can be further reduced.

According to the embodiment of the invention, the rotation angle alpha is added to the traditional Fourier transform to change the traditional Fourier transform into the fractional Fourier transform, so that the time domain characteristics of the reflection coefficient spectrum are converted into the frequency domain characteristics, and the converted signal better reflects the frequency distribution of the signal. By varying the rotation angle, the order of the fractional fourier transform can be varied.

According to an embodiment of the present invention, the rotation angle α may be determined using formula (4):

(4)

where p is the order of the transformation.

Fig. 2 shows a schematic view of a rotation angle according to an embodiment of the present invention.

As shown in fig. 2, fig. 2 shows that p is taken as 1, ω is a time domain variable, u is a time domain variable or a frequency domain variable, p· (pi/2) is calculated, a rotation angle α is determined, after the time domain ω axis is rotated counterclockwise by α, a new rotation angle γ in the domain axis u, ω can be obtained, and after the rotation angle γ is converted to u, the angle is unchanged.

By using different values of p, the time domain signal can be converted into different phase spaces, so that the rotation of the signal in the time-frequency domain space is realized, and different characteristics of the signal are found. For example, in the case where p takes 1, the rotation angle α=pi/2, and thus the ω -axis is rotated counterclockwise by pi/2, resulting in the u-axis, the time domain signal can be converted into the frequency domain. In the case where p is taken to be 2, the rotation angle α=pi, and thus the ω axis is rotated counterclockwise by pi, the time domain signal phase can be inverted. When the value range of p is [0,1], the value range of the rotation angle α is [0, pi/2 ], and the time domain signal can be converted into a state intermediate between the time domain and the frequency domain.

According to an embodiment of the present invention, by changing the rotation angle α of s (ω), F ^α { s (ω) } can be obtained as shown in equation (5):

(5)

Wherein K _α is% U) is a kernel function of fractional Fourier transform, and the form of the kernel function is shown in a formula (6):

(6)

wherein j is a super parameter, and u is a time domain obtained by rotating the omega-axis of the time domain by an angle alpha anticlockwise.

According to an embodiment of the present invention, s (ω) is replaced with the target reflectance spectrum x″ (ω) to obtain a two-dimensional time-frequency spectrum F ^α { x″ (ω) }, as shown in equation (7):

(7)

According to the embodiment of the invention, since the integral value in the two-dimensional time-frequency spectrogram has a negative value, the amplitude value of each position in the two-dimensional time-frequency spectrogram can be calculated by taking the absolute value, and the two-dimensional time-frequency spectrogram is updated as shown in a formula (8):

(8)

Wherein A is the amplitude of each position, and abs (·) is the absolute value.

According to the embodiment of the invention, the fractional Fourier transform is performed on the target reflection coefficient by adding the rotation angle, so that localized information of signals is provided on different time frequencies, the characteristics of non-stationary signals are fully utilized, and the accuracy of cable defect detection is improved.

Fig. 3 shows a schematic diagram of a two-dimensional time-frequency spectrogram according to an embodiment of the invention.

As shown in fig. 3, the two-dimensional time-frequency spectrum includes the position in the cable to be detected, the selected rotation angle and the amplitude. By taking absolute values of all points of the two-dimensional time-frequency spectrogram, the amplitude values of all positions of the cable to be detected when different rotation angles are selected can be obtained, and the updated two-dimensional time-frequency spectrogram can be obtained by representing a plurality of amplitude values in a coordinate system.

According to an embodiment of the present invention, the matrix expression form of the two-dimensional time-frequency spectrogram is as shown in formula (9):

(9)

Wherein N and M are the dimensions of the matrix expression form of the two-dimensional time-frequency spectrogram respectively.

According to an embodiment of the present invention, the pseudo-peak suppression processing includes setting a value at which the rotation angle in the matrix is not equal to 1 to 0, thereby obtaining a pseudo-peak suppression spectrogram F ^α { x "(ω) }'.

According to an embodiment of the present invention, the rotation angle α of F ^α { x "(ω) } 'is regarded as a time variable, and F ^α { x" (ω) }' is time-domain integrated to obtain a frequency response function L (ω), as shown in formula (10):

(10)

According to the embodiment of the invention, according to the propagation speed of the sweep frequency signal in the cable to be detected, the frequency response function is subjected to spectrogram conversion to obtain a positioning curve graph L _location, as shown in a formula (11):

(11)

Where v is the propagation velocity of the swept frequency signal in the cable to be tested, preferably v may take 168 meters/microsecond.

According to the embodiment of the invention, the influence of the pseudo peak on the positioning curve graph can be reduced by performing pseudo peak suppression processing on the rotation angle of the two-dimensional time-frequency spectrogram, performing time domain integration on the obtained pseudo peak suppression spectrogram and further performing spectrogram conversion to obtain the positioning curve graph, so that the influence on the accuracy of the defect detection result is reduced.

According to the embodiment of the present invention, in the case where the cable to be detected has a defect, the reflection intensity at the position where the defect exists is small, and thus it is difficult to intuitively observe the position of the defect, and therefore, the reflection intensity update can be performed for each positioning graph by taking the form of logarithms, as shown in the formula (12):

(12)

where log (-) is a logarithmic function based on the natural number e.

According to the embodiment of the invention, whether the cable to be detected has defects at various positions is determined based on the respective amplitudes of a plurality of target positioning graphs, so that a defect detection result is obtained, wherein the closer the amplitude of a certain position is to 1 in the target positioning graphs, the more likely the cable to be detected has defects at the position.

According to the embodiment of the invention, the amplitude difference between the position where the defect exists and the position where the defect does not exist of the cable to be detected in the target positioning curve graph is increased by taking the logarithmic form, so that the cable defect detection can be more accurately and easily carried out according to the target positioning curve graph, and the accuracy of the cable defect detection is improved.

According to the embodiment of the invention, when the result analysis is carried out by utilizing the target positioning curve graph and the curve graphs obtained by other defect detection methods, the obtained amplitude values can be normalized, so that the error of the result analysis caused by different data ranges is avoided. For example, after the reflection intensity update is performed on each positioning graph by using the formula (12), since the multiplying power of the logarithmic function in the formula (12) is 20, the value of each point in the target positioning graph can be divided by 20 before the result analysis is performed, so as to control the amplitude range of the target positioning graph to be [0,1], thereby completing normalization.

FIG. 4 shows a plot of positioning of a simulation model with frequency domain reflection in accordance with an embodiment of the present invention.

As shown in fig. 4, a curve 1 represents a positioning curve diagram obtained by performing cable defect detection on a simulation model by using a frequency domain reflection method, a curve 2 represents a target positioning curve diagram obtained by performing cable defect detection on the simulation model by using an FDR defect positioning method based on k-means clustering and fractional fourier transform, wherein an abscissa represents detection results at different positions of a cable to be detected, an ordinate represents a result obtained by normalizing amplitude values, and defects exist at 0m and 500m in the cable to be detected of the simulation model.

According to the positioning curve graph and the target positioning curve graph, it can be determined that when the detection is performed by using the FDR defect positioning method based on k-means clustering and fractional Fourier transform, the defect detection result is that the cable to be detected has defects at 0 meter and 500 meters, and when the detection is performed by using the frequency domain reflection method, the defect detection result is that the cable to be detected has defects at 0 meter, 200 meters and 500 meters, so that the accuracy of the defect detection result is higher than that of the frequency domain reflection method.

In addition, the values of the target positioning curve graph are all close to 0 at the position of 0m, the position of 200 m and the position of 500 m, and in the positioning curve graph of the frequency domain reflection method, the values of the other positions are 0.3-0.6, so that when the analysis is performed, the positioning curve graph of the frequency domain reflection method is easy to cause misjudgment, and the target positioning curve graph is not easy to cause misjudgment because the values of the positions without defects are close to 0.

Based on the FDR defect positioning method based on the k-means clustering and the fractional Fourier transform, the invention also provides an FDR defect positioning device based on the k-means clustering and the fractional Fourier transform. The device will be described in detail below in connection with fig. 5.

FIG. 5 shows a block diagram of an FDR defect localization apparatus based on k-means clustering and fractional Fourier transform in accordance with an embodiment of the invention.

As shown in fig. 5, the FDR defect localization apparatus 500 based on k-means clustering and fractional fourier transform of this embodiment includes a signal sampling module 510, a set clustering module 520, a spectrum preprocessing module 530, a spectrum transformation module 540, a spectrum transformation module 550, and a result determination module 560.

The signal sampling module 510 is configured to introduce different sweep signals into the cable to be detected according to the same sampling manner, so as to obtain an initial reflection coefficient spectrum set. In an embodiment, the signal sampling module 510 may be configured to perform the operation S110 described above, which is not described herein.

The set clustering module 520 is configured to cluster the initial set of reflection coefficient spectra to obtain a plurality of clusters of reflection coefficient spectra. In an embodiment, the set clustering module 520 may be configured to perform the operation S120 described above, which is not described herein.

The digital spectrum preprocessing module 530 is configured to perform spectral leakage reduction preprocessing on a plurality of reflection coefficient spectrums obtained based on a plurality of reflection coefficient spectrum clustering clusters, so as to obtain a plurality of target reflection coefficient spectrums. In an embodiment, the spectrum preprocessing module 530 may be used to perform the operation S130 described above, which is not described herein.

The digital spectrum transformation module 540 is configured to perform fractional fourier transformation on the multiple target reflection coefficient spectrums, so as to obtain multiple two-dimensional time-frequency spectrograms. In an embodiment, the spectrum transformation module 540 may be used to perform the operation S140 described above, which is not described herein.

The spectrogram conversion module 550 is configured to perform spectrogram conversion on a plurality of two-dimensional time-frequency spectrograms, so as to obtain a plurality of positioning graphs for defect detection. In an embodiment, the spectrogram conversion module 550 may be used to perform the operation S150 described above, which is not described herein.

The result determining module 560 is configured to obtain a defect detection result of the cable to be detected based on the plurality of positioning graphs. In an embodiment, the result determining module 560 may be configured to perform the operation S160 described above, which is not described herein.

According to an embodiment of the invention, the signal sampling module 510 includes a signal sampling sub-module.

The signal sampling sub-module is used for carrying out signal acquisition on cables to be detected, which are fed with different sweep signals, according to the same sampling frequency and the same sampling point number to obtain an initial reflection coefficient spectrum set, wherein the sweep signals comprise angular frequencies of 0.15MHz-100 MHz.

According to an embodiment of the invention, the aggregate clustering module 520 includes an aggregate clustering sub-module.

And the aggregate clustering sub-module is used for clustering the initial reflection coefficient spectrum aggregate based on the preset clustering number and the signal information of the sweep frequency signals to obtain a plurality of reflection coefficient spectrum clustering clusters.

According to an embodiment of the present invention, the spectrum preprocessing module 530 includes a spectrum determination sub-module, a function addition sub-module, and a spectrum conversion sub-module.

The digital spectrum determining submodule is used for taking the reflection coefficient spectrums corresponding to the centroids of the reflection coefficient spectrum clustering clusters as the reflection coefficient spectrums.

And the function adding submodule is used for respectively adding window functions to the reflection coefficient spectrums.

And the digital spectrum conversion sub-module is used for carrying out bilinear conversion on the reflection coefficient spectrum added with the window function to obtain a target reflection coefficient spectrum.

According to an embodiment of the invention, the digital spectrum conversion submodule comprises a digital spectrum convolution unit.

And the digital spectrum convolution unit is used for carrying out convolution processing on the reflection coefficient spectrum added with the window function and the reflection coefficient spectrum added with the window function which is conjugated to obtain a target reflection coefficient spectrum.

According to an embodiment of the invention, the digital spectrum conversion module 540 includes a digital spectrum conversion sub-module.

And the digital spectrum conversion sub-module is used for carrying out fractional Fourier transform on the target reflection coefficient spectrum by adding a rotation angle to obtain a two-dimensional time-frequency spectrogram.

According to an embodiment of the present invention, the spectrogram conversion module 550 includes a rotation angle suppression sub-module, a spectrogram product sub-module, and a spectrogram conversion sub-module.

And the rotation angle suppression submodule is used for performing pseudo-peak suppression processing on the rotation angle in the two-dimensional time-frequency spectrogram to obtain a pseudo-peak suppression spectrogram.

And the spectrogram integrating sub-module is used for carrying out time domain integration on the pseudo-peak suppression spectrogram to obtain a frequency response function.

And the spectrogram conversion sub-module is used for performing spectrogram conversion on the frequency response function to obtain a positioning graph.

According to an embodiment of the invention, the result determination module 560 includes an intensity update sub-module and a result determination sub-module.

And the intensity updating sub-module is used for updating the reflection intensity of each positioning curve graph to obtain a plurality of target positioning curve graphs.

And the result determination submodule is used for obtaining a defect detection result based on the respective amplitude values of the target positioning graphs.

Any of the plurality of modules of the signal sampling module 510, the ensemble clustering module 520, the spectrum preprocessing module 530, the spectrum conversion module 540, the spectrum conversion module 550, and the result determination module 560 may be combined in one module to be implemented, or any of the plurality of modules may be split into a plurality of modules according to an embodiment of the present invention. Or at least some of the functionality of one or more of the modules may be combined with, and implemented in, at least some of the functionality of other modules. At least one of the signal sampling module 510, the ensemble clustering module 520, the spectral preprocessing module 530, the spectral transformation module 540, the spectral conversion module 550, and the result determination module 560 may be implemented at least in part as hardware circuitry, such as a Field Programmable Gate Array (FPGA), a Programmable Logic Array (PLA), a system-on-chip, a system-on-substrate, a system-on-package, an Application Specific Integrated Circuit (ASIC), or as hardware or firmware in any other reasonable manner of integrating or packaging the circuitry, or as any one of or a suitable combination of any of the three implementations of software, hardware, and firmware, in accordance with an embodiment of the present invention. Or at least one of the signal sampling module 510, the ensemble clustering module 520, the spectrum preprocessing module 530, the spectrum transformation module 540, the spectrum conversion module 550, and the result determination module 560 may be at least partially implemented as a computer program module, which may perform the corresponding functions when executed.

As shown in fig. 6, the electronic device 600 according to the embodiment of the present invention includes a processor 601 that can perform various appropriate actions and processes according to a program stored in a read only memory ROM602 or a program loaded from a storage section 608 into a random access memory RAM 603. The processor 601 may include, for example, a general purpose microprocessor (e.g., a CPU), an instruction set processor and/or an associated chipset and/or a special purpose microprocessor (e.g., an Application Specific Integrated Circuit (ASIC)), or the like. Processor 601 may also include on-board memory for caching purposes. Processor 601 may include a single processing unit or multiple processing units for performing the different actions of the method flows according to embodiments of the invention.

In the RAM 603, various programs and data necessary for the operation of the electronic apparatus 600 are stored. The processor 601, the ROM 602, and the RAM 603 are connected to each other through a bus 604. The processor 601 performs various operations of the method flow according to an embodiment of the present invention by executing programs in the ROM 602 and/or the RAM 603. Note that the program may be stored in one or more memories other than the ROM 602 and the RAM 603. The processor 601 may also perform various operations of the method flow according to embodiments of the present invention by executing programs stored in the one or more memories.

According to an embodiment of the invention, the electronic device 600 may also include an input/output (I/O) interface 605, the input/output (I/O) interface 605 also being connected to the bus 604. The electronic device 600 may also include one or more of an input portion 606 including a keyboard, a mouse, etc., an output portion 607 including a display such as a Cathode Ray Tube (CRT), a Liquid Crystal Display (LCD), etc., and a speaker, etc., a storage portion 608 including a hard disk, etc., and a communication portion 609 including a network interface card such as a LAN card, a modem, etc., connected to an input/output (I/O) interface 605. The communication section 609 performs communication processing via a network such as the internet. The drive 610 is also connected to an input/output (I/O) interface 605 as needed. Removable media 611 such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, or the like is installed as needed on drive 610 so that a computer program read therefrom is installed as needed into storage section 608.

The present invention also provides a computer-readable storage medium that may be included in the apparatus/device/system described in the above embodiments, or may exist alone without being assembled into the apparatus/device/system. The computer-readable storage medium carries one or more programs which, when executed, implement methods in accordance with embodiments of the present invention.

According to embodiments of the invention, the computer-readable storage medium may be a non-volatile computer-readable storage medium, which may include, for example, but is not limited to, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In the context of this document, a computer readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. For example, according to embodiments of the invention, the computer-readable storage medium may include ROM 602 and/or RAM 603 and/or one or more memories other than ROM 602 and RAM 603 described above.

Embodiments of the present invention also include a computer program product comprising a computer program containing program code for performing the method shown in the flowcharts. When the computer program product runs in a computer system, the program code is used for enabling the computer system to realize the FDR defect locating method based on k-means clustering and fractional Fourier transform provided by the embodiment of the invention.

The above-described functions defined in the system/apparatus of the embodiment of the present invention are performed when the computer program is executed by the processor 601. The systems, apparatus, modules, units, etc. described above may be implemented by computer program modules according to embodiments of the invention.

In one embodiment, the computer program may be based on a tangible storage medium such as an optical storage device, a magnetic storage device, or the like. In another embodiment, the computer program may also be transmitted, distributed in the form of signals over a network medium, and downloaded and installed via the communication section 609, and/or installed from the removable medium 611. The computer program may comprise program code that is transmitted using any appropriate network medium, including but not limited to wireless, wireline, etc., or any suitable combination of the preceding.

In such an embodiment, the computer program may be downloaded and installed from a network through the communication portion 609, and/or installed from the removable medium 611. The above-described functions defined in the system of the embodiment of the present invention are performed when the computer program is executed by the processor 601. The systems, devices, apparatus, modules, units, etc. described above may be implemented by computer program modules according to embodiments of the invention.

According to embodiments of the present invention, program code for carrying out computer programs provided by embodiments of the present invention may be written in any combination of one or more programming languages, and in particular, such computer programs may be implemented in high-level procedural and/or object-oriented programming languages, and/or in assembly/machine languages. Programming languages include, but are not limited to, such as Java, c++, python, "C" or similar programming languages. The program code may execute entirely on the user's computing device, partly on the user's device, partly on a remote computing device, or entirely on the remote computing device or server. In the case of remote computing devices, the remote computing device may be connected to the user computing device through any kind of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or may be connected to an external computing device (e.g., connected via the Internet using an Internet service provider).

The flowcharts and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present invention. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams or flowchart illustration, and combinations of blocks in the block diagrams or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.

Those skilled in the art will appreciate that the features recited in the various embodiments of the invention and/or in the claims may be combined in various combinations and/or combinations, even if such combinations or combinations are not explicitly recited in the invention. In particular, the features recited in the various embodiments of the invention and/or in the claims can be combined in various combinations and/or combinations without departing from the spirit and teachings of the invention. All such combinations and/or combinations fall within the scope of the invention.

The embodiments of the present invention are described above. These examples are for illustrative purposes only and are not intended to limit the scope of the present invention. Although the embodiments are described above separately, this does not mean that the measures in the embodiments cannot be used advantageously in combination. The scope of the invention is defined by the appended claims and equivalents thereof. Various alternatives and modifications can be made by those skilled in the art without departing from the scope of the invention, and such alternatives and modifications are intended to fall within the scope of the invention.

Claims

1. An FDR defect localization method based on k-means clustering and fractional fourier transform, the method comprising:

According to the same sampling mode, different sweep frequency signals are introduced into the cable to be detected, and an initial reflection coefficient spectrum set is obtained;

clustering the initial reflection coefficient spectrum set to obtain a plurality of reflection coefficient spectrum clustering clusters;

Respectively carrying out pretreatment for reducing frequency spectrum leakage on a plurality of reflection coefficient spectrums obtained based on a plurality of reflection coefficient spectrum clustering clusters to obtain a plurality of target reflection coefficient spectrums;

fractional Fourier transform is respectively carried out on the target reflection coefficient spectrums to obtain a plurality of two-dimensional time-frequency spectrograms;

performing spectrogram conversion on the two-dimensional time-frequency spectrograms to obtain a plurality of positioning graphs for defect detection, and

Obtaining a defect detection result of the cable to be detected based on a plurality of positioning graphs;

The preprocessing for reducing spectrum leakage is performed on a plurality of reflection coefficient spectrums obtained based on a plurality of reflection coefficient spectrum clustering clusters to obtain a plurality of target reflection coefficient spectrums, and the method comprises the following steps:

Taking a reflection coefficient spectrum corresponding to the mass center of each reflection coefficient spectrum cluster as the reflection coefficient spectrum;

adding a window function to the reflectance spectrum, respectively, and

Performing bilinear transformation on the reflection coefficient spectrum added with the window function to obtain the target reflection coefficient spectrum;

the step of performing bilinear transformation on the reflection coefficient spectrum added with the window function to obtain the target reflection coefficient spectrum comprises the following steps:

Convolving the reflection coefficient spectrum added with the window function and the conjugate reflection coefficient spectrum added with the window function to obtain the target reflection coefficient spectrum;

the performing spectrogram conversion on the two-dimensional time-frequency spectrograms to obtain a plurality of positioning graphs for defect detection, wherein the method comprises the following steps of:

Performing pseudo-peak suppression processing on the rotation angle in the two-dimensional time-frequency spectrogram to obtain a pseudo-peak suppression spectrogram;

performing time domain integration on the pseudo-peak suppression spectrogram to obtain a frequency response function, and

Performing spectrogram conversion on the frequency response function to obtain the positioning curve graph;

the spectrum conversion is carried out on the frequency response function to obtain the positioning curve graph, which comprises the following steps:

Determining the propagation speed of the sweep frequency signal in the cable to be detected, and

The positioning graph is determined based on the propagation velocity and the frequency response function.

2. The method according to claim 1, wherein the step of introducing different sweep signals into the cable to be detected according to the same sampling manner to obtain the initial reflection coefficient spectrum set includes:

According to the same sampling frequency and sampling point number, the cables to be detected which are fed with different sweep frequency signals are subjected to signal acquisition to obtain an initial reflection coefficient spectrum set,

Wherein the sweep signal comprises an angular frequency of 0.15MHz-100 MHz.

3. The method of claim 1, wherein clustering the initial set of reflectance spectra to obtain a plurality of clusters of reflectance spectra includes:

And clustering the initial reflection coefficient spectrum set based on the preset clustering number and the signal information of the sweep frequency signals to obtain a plurality of reflection coefficient spectrum clustering clusters.

4. The method of claim 1, wherein the performing fractional fourier transform on the plurality of target reflectance spectra, respectively, to obtain a plurality of two-dimensional time-frequency spectrograms comprises:

and carrying out fractional Fourier transform on the target reflection coefficient spectrum by adding a rotation angle to obtain the two-dimensional time-frequency spectrogram.

5. The method according to claim 4, wherein the step of performing fractional fourier transform on the target reflection coefficient spectrum by adding a rotation angle to obtain the two-dimensional time-frequency spectrogram includes:

Determining the rotation angle based on the order of the fractional Fourier transform, and

And carrying out fractional Fourier transform on the target reflection coefficient spectrum based on a Fourier transform method and the rotation angle to obtain the two-dimensional time-frequency spectrogram.

6. The method according to claim 1, wherein obtaining the defect detection result of the cable to be detected based on the plurality of positioning graphs includes:

Updating the reflection intensity of each positioning curve graph to obtain a plurality of target positioning curve graphs, and

And obtaining a defect detection result based on the respective amplitude values of the target positioning graphs.

7. An FDR defect localization apparatus based on k-means clustering and fractional fourier transform, the apparatus comprising:

The digital spectrum preprocessing module is used for respectively preprocessing a plurality of reflection coefficient spectrums obtained based on a plurality of reflection coefficient spectrum clustering clusters to obtain a plurality of target reflection coefficient spectrums;

The digital spectrum conversion module is used for respectively carrying out fractional Fourier transform on the target reflection coefficient spectrums to obtain a plurality of two-dimensional time-frequency spectrograms;

a spectrogram conversion module for respectively performing spectrogram conversion on a plurality of the two-dimensional time-frequency spectrograms to obtain a plurality of positioning graphs for defect detection, and

The result determining module is used for obtaining defect detection results of the cable to be detected based on a plurality of positioning graphs;

wherein, the digital spectrum preprocessing module comprises:

A digital spectrum determining sub-module, configured to use a reflection coefficient spectrum corresponding to each centroid of the reflection coefficient spectrum cluster as the reflection coefficient spectrum;

a function adding sub-module for adding window functions to the reflection coefficient spectrums respectively, and

The digital spectrum conversion sub-module is used for carrying out bilinear conversion on the reflection coefficient spectrum added with the window function to obtain the target reflection coefficient spectrum;

the digital spectrum conversion sub-module comprises:

the digital spectrum convolution unit is used for carrying out convolution processing on the reflection coefficient spectrum added with the window function and the reflection coefficient spectrum added with the window function which is conjugated to obtain the target reflection coefficient spectrum;

the spectrogram conversion module comprises:

the rotation angle suppression submodule is used for performing pseudo-peak suppression processing on the rotation angle in the two-dimensional time-frequency spectrogram to obtain a pseudo-peak suppression spectrogram;

A spectrogram integrating sub-module for performing time domain integration on the pseudo-peak suppression spectrogram to obtain a frequency response function, and

The spectrogram conversion sub-module is used for performing spectrogram conversion on the frequency response function to obtain the positioning curve graph;

8. An electronic device, comprising:

One or more processors;

A memory for storing one or more computer programs,

Characterized in that the one or more processors execute the one or more computer programs to implement the steps of the method according to any one of claims 1-6.