Insulation fault detection method, system and device for flexible signal cable

Abstract

The invention relates to the technical field of cable fault detection, in particular to an insulation fault detection method, system and device for a flexible signal cable, and the method comprises the steps: obtaining the electromagnetic wave intensity of each position at different sampling moments in the working process of the flexible signal cable, extracting the local pulse segment of each high-frequency sequence, and obtaining the local pulse segment of each high-frequency sequence; constructing a pulse steep coefficient of each local pulse segment by combining the change degree of the electromagnetic wave intensity in each local pulse segment and the pulse duration; and analyzing the frequency range and the phase difference of the electromagnetic wave intensity in the frequency domain, and constructing the partial discharge frequency coefficient of each ultrahigh frequency sensor by combining the amplitude average level and the phase fluctuation, thereby obtaining the partial discharge characterization value of each ultrahigh frequency sensor so as to detect the insulation fault of the flexible signal cable. According to the invention, the influence of electromagnetic interference on insulation fault detection can be reduced, and the accuracy of insulation fault detection of the flexible signal cable is improved.

Description

Technical Field

[0001] The present application relates to the technical field of cable fault detection, and in particular to a method, system and device for detecting insulation faults of flexible signal cables. Background Art

[0002] Flexible signal cables usually use high-purity multi-strand fine oxygen-free bare copper wire as conductors. Compared with ordinary cables, the insulation and sheath materials are more resistant to mechanical fatigue and have higher strength and flexibility.

[0003] During the transportation of flexible signal cables, they often have to go through multiple shipments and liftings, and the cables will inevitably be squeezed and rubbed, which will cause damage to the insulation layer of the cable. In addition, due to various factors in the processing and manufacturing process, such as bubbles or impurities, the breakdown voltage of some insulating areas in the cable is greatly reduced. During the use of the cable, local discharge will occur inside the insulator. The local discharge phenomenon will cause the insulation material of the cable to gradually age, and even insulation breakdown, thereby causing cable insulation failure. Existing insulation fault detection methods include electromagnetic wave method, acoustic wave method, pulse current method, etc. These detection methods have their own advantages and disadvantages. Among them, the pulse current method has high sensitivity, but it requires non-powered detection, which will affect the normal power supply of the cable; the electromagnetic wave method and the acoustic wave method are both non-invasive detection, which will not affect the normal operation of the cable, but will affect the accuracy of the measurement in a strong electromagnetic interference or noise environment. Summary of the invention

[0004] In order to solve the above technical problems, the purpose of this application is to provide a method, system and device for detecting insulation faults of flexible signal cables. The technical solutions adopted are as follows: In a first aspect, an embodiment of the present application provides a method for detecting insulation faults of a flexible signal cable, comprising the following steps: Deploy ultra-high frequency sensors at various positions of the flexible signal cable to obtain the electromagnetic wave intensity at various positions at different sampling times during the working process of the flexible signal cable, and perform low-frequency filtering to obtain the high-frequency sequence of each ultra-high frequency sensor; Each local pulse segment is extracted through the minimum value in the high-frequency sequence, and the pulse steepness coefficient of each local pulse segment is constructed by combining the change degree of electromagnetic wave intensity and pulse duration in each local pulse segment; Perform frequency domain conversion on each high-frequency sequence, analyze the frequency range and phase difference of the electromagnetic wave intensity in each high-frequency sequence in the frequency domain, and construct the local discharge frequency coefficient of each ultra-high frequency sensor in combination with the average amplitude level and phase fluctuation degree of each frequency in the frequency domain. Construct the local discharge characterization value of each ultra-high frequency sensor according to the pulse steepness coefficient of all local pulse segments and the local discharge frequency coefficient; Detect insulation faults in flexible signal cables based on partial discharge characterization values ​​for all UHF sensors.

[0005] Preferably, the construction of the high frequency sequence of each ultra-high frequency sensor includes: forming each electromagnetic wave sequence with the electromagnetic wave intensity of each ultra-high frequency sensor at all sampling moments, and using a high-pass filter to filter out the low frequency of each electromagnetic wave sequence to obtain the high frequency sequence of each ultra-high frequency sensor.

[0006] Preferably, the determination of each local pulse segment includes: forming a local pulse segment with the electromagnetic wave intensity between any two adjacent minimum values ​​in the high-frequency sequence.

[0007] Preferably, the calculation method of the pulse steepness coefficient of each local pulse segment is: ; In the formula, is the pulse steepness coefficient of the kth local pulse segment; is the change speed of the kth local pulse segment, wherein the change speed of each local pulse segment is constructed by the change of the electromagnetic wave intensity of each local pulse segment; is the pulse duration of the kth local pulse segment, wherein the time interval between two boundary points of the local pulse segment is taken as the pulse duration of the local pulse segment.

[0008] Preferably, the calculation method of the change speed of each local pulse segment is further as follows: ;in, is the changing speed of the kth local pulse segment; are the durations of the rising edge and falling edge in the kth local pulse segment respectively; Indicates the extreme difference of the electromagnetic wave intensity corresponding to the rising edge of the kth local pulse segment; It represents the extreme difference of the electromagnetic wave intensity corresponding to the falling edge of the kth local pulse segment, wherein the slope of the falling edge stage is less than zero, and the slope of the rising edge stage is greater than zero.

[0009] Preferably, the calculation method of the partial discharge frequency coefficient of each ultra-high frequency sensor is: ; represents the partial discharge frequency coefficient of the i-th UHF sensor; and Respectively represent the maximum frequency and minimum frequency of the high-frequency sequence in the frequency domain; They respectively represent the sequence composed of the phases of each frequency in the frequency domain of the high-frequency preamble sequence and the high-frequency postamble sequence of the i-th ultra-high frequency sensor; represents the dtw distance; represents the phase variance of all frequencies of the high frequency sequence of the i-th UHF sensor in the frequency domain; represents the average value of the amplitude of all frequencies of the high frequency sequence of the i-th UHF sensor in the frequency domain; The first preset number of electromagnetic wave intensities in the high-frequency sequence form a high-frequency pre-sequence, and all remaining electromagnetic wave intensities form a high-frequency post-sequence.

[0010] Preferably, the calculation method of the partial discharge characterization value of each ultra-high frequency sensor is: ; In the formula, represents the partial discharge characterization value of the i-th UHF sensor; represents the partial discharge frequency coefficient of the high frequency sequence of the i-th UHF sensor; represents the pulse steepness coefficient of the kth local pulse segment; r is the number of local pulse segments.

[0011] Preferably, the method of detecting insulation failure of the flexible signal cable further comprises: The partial discharge characterization values ​​of all UHF sensors are detected for abnormality, and each discrete value is extracted. Based on each discrete value, the insulation fault detection and positioning of the flexible signal cable is performed.

[0012] In a second aspect, an embodiment of the present application further provides an insulation fault detection system for a flexible signal cable, comprising a memory, a processor, and a computer program stored in the memory and running on the processor, wherein when the processor executes the computer program, the steps of any one of the above-mentioned insulation fault detection methods for a flexible signal cable are implemented.

[0013] In a third aspect, an embodiment of the present application further provides an insulation fault detection device for a flexible signal cable, wherein a computer program is stored in the device, and when the computer program is executed by a processor, the insulation fault detection method for a flexible signal cable described in any one of the above items is implemented.

[0014] It can be seen from the above that the insulation fault detection method, system and device of a flexible signal cable provided by the present application have at least the following beneficial effects: This application proposes a method for detecting insulation faults of flexible signal cables to address the problem that the electromagnetic wave method is easily affected by other electromagnetic interferences, resulting in inaccurate insulation fault detection. By analyzing the difference characteristics of the electromagnetic waves generated by the partial discharge of the cable and the electromagnetic waves generated by the electromagnetic interference in the pulse waveform and frequency domain, and constructing the partial discharge characterization value, it is possible to determine whether the collected electromagnetic wave signal contains the electromagnetic waves generated by the partial discharge, thereby reducing the impact of electromagnetic interference on insulation fault detection and improving the accuracy of insulation fault detection of flexible signal cables. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] In order to more clearly illustrate the technical solutions and advantages in the embodiments of the present application or the prior art, the drawings required for use in the embodiments or the prior art descriptions are briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0016] Figure 1 A flowchart of the steps of a method for detecting insulation faults of a flexible signal cable provided in the present application; Figure 2 The figure is a comparison of the fault location detection effect of the fault detection method of the present application and the existing capacitive detection technology. DETAILED DESCRIPTION

[0017] In order to further explain the technical means and effects adopted by the present application to achieve the predetermined invention purpose, the following is a detailed description of the insulation fault detection method, system and device of a flexible signal cable proposed in the present application, its specific implementation, structure, features and effects in combination with the accompanying drawings and preferred embodiments. In the following description, different "one embodiment" or "another embodiment" does not necessarily refer to the same embodiment. In addition, specific features, structures or characteristics in one or more embodiments may be combined in any suitable form.

[0018] Unless otherwise specified and limited, terms such as "comprises", "comprising" or any other variants thereof are intended to cover non-exclusive inclusion, so that a circuit structure, article or device including a series of elements includes not only those elements, but also includes other elements not explicitly listed, or also includes elements inherent to such articles or devices. In the absence of further restrictions, an element defined by the sentence "comprising a ..." does not exclude the presence of other identical elements in the article or device including the element. In addition, the term "and\or" used herein includes any and all combinations of one or more related listed items. All technical and scientific terms used herein have the same meaning as those commonly understood by technicians in the technical field of this application.

[0019] The following describes in detail a method, system and device for detecting insulation faults of a flexible signal cable provided by the present application in conjunction with the accompanying drawings.

[0020] See also Figure 1 , which shows a flowchart of a method for detecting insulation fault of a flexible signal cable provided by an embodiment of the present application, comprising the following steps: Step 1: Deploy UHF sensors at various positions of the flexible signal cable to obtain the electromagnetic wave intensity at various positions at different sampling times during the operation of the flexible signal cable, and perform low-frequency filtering to obtain the high-frequency sequence of each UHF sensor.

[0021] In the chemical industry, safety performance is crucial. Flexible signal cables have good electrical and insulation properties and can provide stable power and signal transmission while ensuring the safety of personnel and equipment. Therefore, flexible signal cables are widely used in the chemical industry.

[0022] According to the power supply direction of the flexible signal cable in a chemical plant, an ultra-high frequency (UHF) sensor is arranged at a distance c, and a total of m ultra-high frequency sensors are arranged. The m ultra-high frequency sensors are used to collect electromagnetic wave signals radiated during the normal operation of the flexible signal cable, and the collection frequency is 3GHz. There is no need to power off the flexible signal cable during the collection process to maintain its normal working state. In this embodiment, the number of high-frequency sensors m is 8, and the interval distance c between the ultra-high frequency sensors is 0.5 meters. In actual application scenarios, the implementer can set it according to the actual situation.

[0023] Further, the collected electromagnetic wave signal is preprocessed to improve data purity. In this embodiment, the collected electromagnetic wave signal is used as the input of the median filter algorithm to denoise the electromagnetic wave signal. The median filter algorithm is a well-known technology, and the specific process is not repeated here.

[0024] In chemical plants, flexible signal cables are used in various chemical equipment. However, since corrosive gases and liquids are often present in the chemical industry, and some chemical processes need to be operated under high temperature conditions, the flexible signal cables may be damaged, resulting in reduced insulation performance. When using the electromagnetic wave method to detect insulation failures of flexible signal cables, many devices in chemical plants will generate strong electromagnetic interference, resulting in interference waveforms in the collected electromagnetic wave signals. Therefore, it is necessary to distinguish between partial discharge waveforms and other interference waveforms in the collected electromagnetic wave signals.

[0025] The local discharge position in the flexible signal cable usually produces a steep current pulse, which radiates electromagnetic waves to the surrounding area, so the electromagnetic wave signal generated by the local discharge often presents a pulse waveform. Since the current pulse generated by the local discharge is very steep, the corresponding pulse waveform also has a fast rising and falling edge and a short duration. The electromagnetic wave signal generated by the local discharge is mainly concentrated in the high frequency band, usually 3MHz-3GHz or higher, and contains rich frequency components in the frequency domain, which makes the electromagnetic wave signal have a wide bandwidth. In addition, the phase correlation at different times is very strong.

[0026] Since there are a large number of power transformers and high-frequency transmitters in chemical plants, when these devices are close to the flexible signal cable, they will cause electromagnetic interference to the partial discharge test system. The electromagnetic interference generated by the power transformer will appear as a combination of sine waves and their harmonics or a pulse waveform. The frequencies of sine waves and their harmonics are mainly concentrated in the low frequency band, and the frequency range of the pulse waveform has both low and high frequency bands. The pulse waveform has a longer duration and slower rising and falling edges; the electromagnetic interference waveform generated by the high-frequency transmitter usually presents a pulse waveform, the frequency is concentrated in the high frequency band, has a narrow bandwidth, the phase difference of the signal measured at different times is large, and the amplitude may also be large.

[0027] Therefore, for further analysis, in this embodiment, the electromagnetic wave signal collected by the i-th UHF sensor is recorded as the electromagnetic wave sequence of the i-th UHF sensor ,in, , and Represent the electromagnetic wave intensity at the first, second and nth sampling moments respectively. As the input of the high-pass filter, the cut-off frequency is set to a MHz. In this embodiment, a is 3. The low-frequency signal in is filtered out to obtain the high-frequency sequence of the i-th ultra-high frequency sensor , where the high frequency sequence It only contains high-frequency electromagnetic wave intensity.

[0028] Step 2: Extract each local pulse segment through the minimum value in the high-frequency sequence, and construct the pulse steepness coefficient of each local pulse segment based on the change degree of electromagnetic wave intensity and pulse duration in each local pulse segment.

[0029] Further, the change of the high-frequency information of the electromagnetic wave signal is analyzed. In this embodiment, the high-frequency sequence is detected for minimum and maximum values, and the electromagnetic wave intensity between any two adjacent minimum values ​​is used to form a local pulse segment, and the time interval between the two boundary points of the local pulse segment is used as the pulse duration of the corresponding local pulse segment. In this embodiment, for each local pulse segment, from left to right, the electromagnetic wave intensity from the minimum value to the maximum value is used as the rising edge, and the electromagnetic wave intensity from the maximum value to another minimum value is used as the falling edge, that is, the stage with a slope greater than zero is the rising edge, and the stage with a slope less than zero is the falling edge. It should be noted that in actual application scenarios, the implementer can select the method in the prior art to identify each local pulse segment in the high-frequency sequence, and divide each local pulse segment into a rising edge and a falling edge. There is no special restriction on this in this embodiment.

[0030] Therefore, in this embodiment, the change speed of each local pulse segment is analyzed in combination with the change degree and change time of the electromagnetic wave intensity of each local pulse segment. In this embodiment, the specific calculation formula is: ;in, is the variation speed of the kth local pulse segment, which is used to characterize the high-frequency sequence The changing speed of the rising and falling edges of the kth pulse in; are the durations of the rising edge and falling edge in the kth local pulse segment respectively; Indicates the extreme difference of the electromagnetic wave intensity corresponding to the rising edge of the kth local pulse segment; It represents the extreme difference of electromagnetic wave intensity corresponding to the falling edge of the kth local pulse segment.

[0031] Furthermore, the pulse steepness coefficient of each local pulse segment is constructed by combining the change speed of each local pulse segment and the pulse duration of each local pulse segment to characterize the high-frequency sequence. The probability that each local pulse segment belongs to a pulse signal generated by a local discharge. In this embodiment, the specific calculation formula is: ;in, is the pulse steepness coefficient of the kth local pulse segment; is the pulse duration of the kth local pulse segment.

[0032] According to the above formula, it can be understood that The larger the value, the higher the frequency of the sequence. The larger the amplitude of the kth pulse. The smaller the value, the higher the frequency of the sequence. The shorter the duration of the rising and falling edges of the kth pulse.

[0033] at the same time, The larger the value, the higher the frequency of the sequence. The faster the rising and falling edges of the kth pulse change; The smaller the value, the higher the frequency of the sequence. The shorter the duration of the kth pulse. The larger the value, the higher the frequency of the sequence. The kth pulse has fast rising and falling edges and a shorter duration, the more likely it is that the kth pulse is a pulse signal caused by partial discharge.

[0034] Step three: Perform frequency domain conversion on each high-frequency sequence, analyze the frequency range and phase difference of the electromagnetic wave intensity in each high-frequency sequence in the frequency domain, and construct the local discharge frequency coefficient of each ultra-high frequency sensor based on the average amplitude level and phase fluctuation degree of each frequency in the frequency domain. Construct the local discharge characterization value of each ultra-high frequency sensor based on the pulse steepness coefficient of all local pulse segments and the local discharge frequency coefficient.

[0035] Furthermore, the high-frequency sequence As the input of the discrete Fourier transform (DLT) algorithm, the amplitude spectrum and phase spectrum of the sequence are obtained. Discrete Fourier transform is a well-known technology, and the specific process is not repeated here. The amplitude of various frequencies can be obtained from the amplitude spectrum, and the phase corresponding to various frequencies can be obtained from the phase spectrum. The front The sequence of electromagnetic wave intensities is used as the high-frequency preamble sequence of the i-th ultra-high frequency sensor, j represents the total number of electromagnetic wave intensities in the high-frequency sequence, and int() is a rounding function used to round the input data to an integer. The sequence consisting of all the remaining electromagnetic wave intensities after removing the high-frequency preamble sequence is used as the high-frequency post-sequence of the i-th ultra-high frequency sensor. Further, in this embodiment, the high-frequency preamble sequence and the high-frequency post-sequence sequence are respectively used as inputs of the discrete Fourier transform algorithm to obtain the frequency domain information corresponding to the high-frequency preamble sequence and the high-frequency post-sequence sequence, including the amplitude spectrum and the phase spectrum.

[0036] Based on the analysis of the frequency range and phase difference of the electromagnetic wave intensity in the high-frequency sequence in the frequency domain, combined with the average amplitude level and phase fluctuation degree of each frequency in the frequency domain, the partial discharge frequency coefficient of each ultra-high frequency sensor is constructed to characterize the high-frequency sequence. The similarity between the frequency domain characteristics of the pulse signal caused by partial discharge and the frequency domain characteristics of the pulse signal caused by partial discharge. In this embodiment, the calculation formula of the partial discharge frequency coefficient is: ; represents the partial discharge frequency coefficient of the i-th UHF sensor; and Respectively represent the maximum frequency and minimum frequency of the high-frequency sequence in the frequency domain; They respectively represent the sequence composed of the phases of each frequency in the frequency domain of the high-frequency preamble sequence and the high-frequency postamble sequence of the i-th ultra-high frequency sensor; represents the dtw distance; represents the phase variance of all frequencies of the high frequency sequence of the i-th UHF sensor in the frequency domain; Represents the average value of the amplitude of all frequencies of the high frequency sequence of the i-th ultra-high frequency sensor in the frequency domain.

[0037] Understandably, The larger the value, the higher the frequency of the sequence. The larger the bandwidth, the higher the frequency sequence. The more similar the signal in is to the pulse signal caused by partial discharge; The smaller the value, the higher the frequency of the sequence. The phase difference between the front and back data is small, which represents the high-frequency sequence The more similar the phase characteristics in the pulse signal are to those caused by partial discharge; The smaller the value, the higher the frequency of the sequence. The difference in the phase of each frequency is small, which shows that the high-frequency sequence The more similar it is to the pulse signal caused by partial discharge; The smaller the value, the higher the frequency sequence. The amplitude of each frequency is small, thus representing the high-frequency sequence The more similar the amplitude characteristics of the pulse signal are to those caused by partial discharge.

[0038] Furthermore, according to the pulse steepness coefficients of all local pulse segments and the local discharge frequency coefficient, a local discharge characterization value is constructed to characterize the possibility that the electromagnetic signal collected by the i-th ultra-high frequency sensor contains a pulse signal caused by local discharge. In this embodiment, the specific calculation formula of the local discharge characterization value of each ultra-high frequency sensor is: ; In the formula, represents the partial discharge characterization value of the i-th UHF sensor; represents the partial discharge frequency coefficient of the high frequency sequence of the i-th UHF sensor; represents the pulse steepness coefficient of the kth local pulse segment; r is the number of local pulse segments.

[0039] It can be understood that when the local discharge frequency coefficient of the high frequency sequence of the i-th UHF sensor The larger the value, the more similar the frequency characteristics of the high-frequency sequence are to the frequency characteristics of the pulse signal caused by partial discharge, and the greater the possibility that the electromagnetic signal collected by the i-th ultra-high frequency sensor contains the pulse signal caused by partial discharge; when the pulse steepness coefficient of the k-th local pulse segment is The larger the value is, the steeper the rising and falling edges characterizing the kth local pulse segment are, and the shorter the duration of the pulse is. Therefore, it is more likely that the electromagnetic signal of the i-th UHF sensor contains a pulse signal caused by local discharge.

[0040] So far, according to the above process of this embodiment, the partial discharge characterization value of each ultra-high frequency sensor is obtained.

[0041] Step 4: Detect insulation faults of flexible signal cables based on partial discharge characterization values ​​of all UHF sensors.

[0042] Furthermore, according to the above process of this embodiment, the partial discharge characterization values ​​of all ultra-high frequency sensors are calculated, and abnormality detection is performed on the partial discharge characterization values ​​of all ultra-high frequency sensors, and each discrete value is extracted, and insulation fault detection and positioning of the flexible signal cable is performed based on each discrete value.

[0043] Specifically, in this embodiment, all local discharge characterization values ​​are used as inputs of the Z-Score algorithm, the z-score of each local discharge characterization value is calculated, and the local discharge characterization value with a z-score greater than a preset threshold is used as an outlier. In this embodiment, in order to reflect the test effect, the preset threshold is set to 1.657, and the implementer can also set it by himself in the actual application scenario. The Z-Score algorithm is a well-known technology, and the specific process will not be repeated. It should be noted that for all local discharge characterization values, the implementer can also use other outlier detection algorithms in the prior art to obtain outliers, such as the LOF (Local Outlier Factor) anomaly detection algorithm, etc., and there is no special restriction on this in this embodiment. Furthermore, in this embodiment, the location of the ultra-high frequency sensor corresponding to the discrete value is used as the insulation fault location.

[0044] Specifically, in this embodiment, the z-score test results of the partial discharge characterization values ​​corresponding to multiple groups of sensors and the insulation fault detection results corresponding to each sensor are specifically shown in Table 1. In Table 1, the sensors are numbered 1-8 from top to bottom. The above method of this embodiment is used to analyze the data of each sensor, calculate the partial discharge frequency coefficient corresponding to each sensor, and obtain the partial discharge characterization value corresponding to each sensor through the calculation formula of the partial discharge characterization value in this embodiment, simulate the data collected by each sensor and obtain the z-score of the corresponding partial discharge characterization value. In order to show the test results, during the test process of this embodiment, the z-score threshold is set to 1.657. When the calculated z-score is greater than 1.657, it indicates that an insulation fault occurs at the location of the sensor. It can be obtained from Table 1 that the z-score of the partial discharge characterization value obtained by collecting data from sensor 8 is 2.07986007, which is greater than the preset z-score threshold. Therefore, an insulation fault occurs at the location of sensor 8, and the abnormal mark of sensor 8 is yes, indicating that an insulation fault exists at the location of sensor 8.

[0045] Table 1 Sensor No. Partial discharge frequency coefficient Partial discharge characterization value Average value of pulse steepness factor Maximum value of pulse steepness factor Number of local pulse segments z-score Exception Marking 1 2.34198564 0.18288039 0.078 0.723 309 0.91331036 no 2 2.27567844 0.17408617 0.076 0.536 301 0.77333078 no 3 2.99082250 0.09935403 0.033 0.244 293 -0.41619706 no 4 2.79766440 0.08414408 0.03 0.208 288 -0.65829725 no 5 2.56203911 0.07616453 0.029 0.204 310 -0.78530946 no 6 3.01319027 0.10074778 0.033 0.275 298 -0.39401238 no 7 2.34090764 0.06432226 0.027 0.302 313 -0.97380537 no 8 3.27938930 0.25616893 0.078 0.528 294 2.07986007 yes So far, according to the above process of this embodiment, the insulation fault detection of the flexible signal cable can be performed, and the location of the insulation fault can be obtained.

[0046] At the same time, if Figure 2This is a comparison chart of the detection accuracy of the data of known fault locations using the detection method of this embodiment and the existing capacitive detection technology. The specific process of insulation fault detection using capacitive detection technology is an existing technology and will not be repeated in this embodiment. During the test process of this embodiment, 30 test groups were prepared, each with 500 test instances. Each test instance contained 8 sets of sensor acquisition data. The detection accuracy was obtained by testing and analyzing each group of 500 test instances. Figure 2 It can be clearly seen that in most test processes, the detection accuracy obtained by using the method of this embodiment to perform fault testing is better than that of the existing method. Among them, the existing method uses existing capacitive detection technology in this test process. In actual application scenarios, implementers can choose it by themselves.

[0047] Based on the same inventive concept as the above method, an embodiment of the present application also provides an insulation fault detection system for a flexible signal cable, comprising a memory, a processor, and a computer program stored in the memory and running on the processor, wherein the processor implements the steps of any one of the above-mentioned insulation fault detection methods for a flexible signal cable when executing the computer program.

[0048] At the same time, an embodiment of the present application also provides an insulation fault detection device for a flexible signal cable, wherein a computer program is stored in the device, and when the computer program is executed by a processor, the insulation fault detection method for a flexible signal cable described in any one of the above items is implemented.

[0049] It is to be understood that the sequence of the embodiments of the present application described above is for description only and does not represent the advantages and disadvantages of the embodiments. The above describes specific embodiments of the present specification. In addition, the processes depicted in the accompanying drawings do not necessarily require the specific order or continuous order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0050] The various embodiments in this specification are described in a progressive manner, and the same or similar parts between the various embodiments can be referenced to each other, and each embodiment focuses on the differences from other embodiments.

[0051] The above content is only an implementation method of the present application and is not intended to limit the scope of the present application. Any equivalent structure or equivalent process transformation made using the contents of the present application specification and drawings, or directly or indirectly used in other related technical fields, are also included in the protection scope of the present application.

Claims

1. A method for detecting insulation faults of a flexible signal cable, characterized in that: The following steps are involved: Deploy ultra-high frequency sensors at various positions of the flexible signal cable to obtain the electromagnetic wave intensity at various positions at different sampling times during the working process of the flexible signal cable, and perform low-frequency filtering to obtain the high-frequency sequence of each ultra-high frequency sensor; Each local pulse segment is extracted through the minimum value in the high-frequency sequence, and the pulse steepness coefficient of each local pulse segment is constructed by combining the change degree of electromagnetic wave intensity and pulse duration in each local pulse segment; Perform frequency domain conversion on each high-frequency sequence, analyze the frequency range and phase difference of the electromagnetic wave intensity in each high-frequency sequence in the frequency domain, and construct the local discharge frequency coefficient of each ultra-high frequency sensor in combination with the average amplitude level and phase fluctuation degree of each frequency in the frequency domain. Construct the local discharge characterization value of each ultra-high frequency sensor according to the pulse steepness coefficient of all local pulse segments and the local discharge frequency coefficient; Detect insulation faults in flexible signal cables based on partial discharge characterization values ​​for all UHF sensors.

2. The method for detecting insulation fault of a flexible signal cable according to claim 1, characterized in that: The construction of the high frequency sequence of each ultra-high frequency sensor includes: forming each electromagnetic wave sequence from the electromagnetic wave intensity of each ultra-high frequency sensor at all sampling moments, and using a high-pass filter to filter out the low frequency of each electromagnetic wave sequence to obtain the high frequency sequence of each ultra-high frequency sensor.

3. The method for detecting insulation fault of a flexible signal cable according to claim 1, characterized in that: The determination of each local pulse segment includes: forming a local pulse segment with the electromagnetic wave intensity between any two adjacent minimum values ​​in the high-frequency sequence.

4. The method for detecting insulation fault of a flexible signal cable according to claim 1, characterized in that: The calculation method of the pulse steepness coefficient of each local pulse segment is: ; In the formula, is the pulse steepness coefficient of the kth local pulse segment; is the change speed of the kth local pulse segment, wherein the change speed of each local pulse segment is constructed by the change of the electromagnetic wave intensity of each local pulse segment; is the pulse duration of the kth local pulse segment, wherein the time interval between two boundary points of the local pulse segment is taken as the pulse duration of the local pulse segment.

5. The method for detecting insulation fault of a flexible signal cable according to claim 4, characterized in that: The calculation method of the change speed of each local pulse segment is further as follows: ;in, is the changing speed of the kth local pulse segment; are the durations of the rising edge and falling edge in the kth local pulse segment respectively; Indicates the extreme difference of the electromagnetic wave intensity corresponding to the rising edge of the kth local pulse segment; It represents the extreme difference of the electromagnetic wave intensity corresponding to the falling edge of the kth local pulse segment, wherein the slope of the falling edge stage is less than zero, and the slope of the rising edge stage is greater than zero.

6. The method for detecting insulation fault of a flexible signal cable according to claim 1, characterized in that: The calculation method of the partial discharge frequency coefficient of each ultra-high frequency sensor is: ; represents the partial discharge frequency coefficient of the i-th UHF sensor; and Respectively represent the maximum frequency and minimum frequency of the high-frequency sequence in the frequency domain; They respectively represent the sequence composed of the phases of each frequency in the frequency domain of the high-frequency preamble sequence and the high-frequency postamble sequence of the i-th ultra-high frequency sensor; represents the dtw distance; represents the phase variance of all frequencies of the high frequency sequence of the i-th UHF sensor in the frequency domain; represents the average value of the amplitude of all frequencies of the high frequency sequence of the i-th UHF sensor in the frequency domain; The first preset number of electromagnetic wave intensities in the high-frequency sequence form a high-frequency pre-sequence, and all remaining electromagnetic wave intensities form a high-frequency post-sequence.

7. The method for detecting insulation fault of a flexible signal cable according to claim 1, characterized in that: The calculation method of the partial discharge characterization value of each ultra-high frequency sensor is: ; In the formula, represents the partial discharge characterization value of the i-th UHF sensor; represents the partial discharge frequency coefficient of the high frequency sequence of the i-th UHF sensor; represents the pulse steepness coefficient of the kth local pulse segment; r is the number of local pulse segments.

8. The method for detecting insulation fault of a flexible signal cable according to claim 1, characterized in that: The method of detecting an insulation fault in a flexible signal cable further comprises: The partial discharge characterization values ​​of all UHF sensors are detected for abnormality, and each discrete value is extracted. Based on each discrete value, the insulation fault detection and positioning of the flexible signal cable is performed.

9. An insulation fault detection system for a flexible signal cable, comprising a memory, a processor, and a computer program stored in the memory and running on the processor, characterized in that: When the processor executes the computer program, the steps of the insulation fault detection method for a flexible signal cable as described in any one of claims 1 to 8 are implemented.

10. An insulation fault detection device for a flexible signal cable, wherein a computer program is stored in the device, characterized in that: When the computer program is executed by a processor, the method for detecting insulation faults of a flexible signal cable as described in any one of claims 1 to 8 is implemented.

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