Ultrasonic Feature Identification and Management Method and System for Broken Strands in Internal Conductors of Energy Storage Cables

Abstract

This invention provides a method and system for ultrasonic feature identification and management of broken strands in the internal conductors of energy storage cables, relating to the field of energy storage system operation and maintenance technology. The method includes: directionally emitting ultrasonic signals with a frequency range of 1MHz to 10MHz into the conductor area of ​​the energy storage cable using an ultrasonic transmitting device, allowing the ultrasonic signals to penetrate the cable insulation layer and act on the conductor; using the structural features of the crimped terminals at both ends of the energy storage cable conductor and the grounding end of the cable shield layer as spatial reference points based on the conductor area affected by the ultrasonic signals; performing three-dimensional coordinate calculation on each spatial reference point to determine the relative spatial coordinates and reference distance within the conductor area, constructing a signal analysis and positioning reference frame; and obtaining a signal acquisition strategy adjustment parameter based on the structural characteristics of the analysis units by setting up regularized analysis units within the positioning reference frame. This invention achieves accurate identification, real-time positioning, and automated operation and maintenance management of broken strand defects in the internal conductors of energy storage cables.

Description

Technical Field

[0001] This invention relates to the field of energy storage system operation and maintenance technology, and in particular to a method and system for ultrasonic feature identification and management of broken strands in the internal conductors of energy storage cables. Background Technology

[0002] With the large-scale application of energy storage power stations, energy storage cables, as the core carriers for energy storage and transmission, are subjected to long-term high-current impacts, temperature cycles, and mechanical vibrations. Internal conductors are prone to hidden single or multiple strand breakage defects. Failure to identify these defects in time can lead to localized overheating, abnormal impedance, or even fires, seriously threatening operational safety. Currently, mainstream testing methods in the industry mostly rely on time-domain reflectometry (TDR), insulation resistance testing, or traditional ultrasonic testing. However, TDR lacks sensitivity to minute strand breaks, insulation resistance testing can only determine the insulation condition but cannot locate internal conductor defects, and traditional ultrasonic testing, due to its fixed acquisition parameters, is difficult to adapt to the signal attenuation differences caused by complex structures such as cable bends and abrupt cross-sectional changes.

[0003] For example, a 35kV DC bus cable of a 200MWh energy storage power station experienced abnormal local temperature rise during operation. The maintenance personnel initially used TDR to detect the defect, but it only showed a slight fluctuation in impedance and could not determine the location of the defect. When they used traditional ultrasonic equipment for subsequent detection, the gain and filtering parameters were not adjusted for the curvature change at the cable joint, and the signal-to-noise ratio of the echo signal was less than 20dB. The characteristic signal of the broken three conductors could not be captured, which ultimately led to the cable melting at the broken strands during heavy load operation, causing a single cluster of batteries to be shut down for 8 hours. This case exposed the core defects of existing technology, such as low accuracy in identifying small broken strands, great influence from cable structure, and difficulty in achieving accurate defect location and operation and maintenance linkage. Summary of the Invention

[0004] The technical problem to be solved by the present invention is to provide an ultrasonic feature identification and management method and system for broken strands in the internal conductors of energy storage cables, so as to realize accurate identification, real-time positioning and automated operation and maintenance management of broken strand defects in the internal conductors of energy storage cables.

[0005] To solve the above-mentioned technical problems, the technical solution of the present invention is as follows:

[0006] A first aspect is a method for ultrasonic feature identification and management of broken strands in the internal conductors of energy storage cables, the method comprising:

[0007] An ultrasonic transmitter directionally emits ultrasonic signals with a frequency range of 1MHz to 10MHz into the conductor area of ​​the energy storage cable, allowing the ultrasonic signals to penetrate the cable insulation layer and act on the conductor.

[0008] Based on the conductor region affected by ultrasonic signals, the structural features of the crimp terminals at both ends of the energy storage cable conductor and the grounding end of the cable shield layer are used as spatial reference points; three-dimensional coordinate calculations are performed on each spatial reference point to determine the relative spatial coordinates and reference distance within the conductor region, and a signal analysis and positioning reference framework is constructed.

[0009] By setting up regularized analysis units for the positioning reference frame, a signal acquisition strategy adjustment parameter is obtained based on the structural characteristics of the analysis units.

[0010] Adjust parameters according to the signal acquisition strategy, configure the working mode of the ultrasonic receiver, and acquire the echo signal returned from the conductor based on the transmitted ultrasonic signal. Simultaneously record the time-domain waveform and spectral response data of the echo signal to obtain an optimized echo signal dataset.

[0011] Based on the optimized echo signal dataset, feature extraction analysis is performed to obtain a set of feature parameters including signal attenuation rate, resonant frequency offset, and echo time delay.

[0012] The set of feature parameters is matched and compared with a preset string breakage feature threshold library to determine whether there is a string breakage defect inside the conductor and generate a corresponding identification signal.

[0013] Based on the broken strand defect identification signal, a defect diagnosis report containing cable location information is automatically generated, and corresponding equipment maintenance and management instructions are triggered accordingly.

[0014] Furthermore, based on the conductor region affected by ultrasonic signals, the structural features of the crimped terminals at both ends of the energy storage cable conductor and the grounding end of the cable shield layer are used as spatial reference points; three-dimensional coordinate calculations are performed on each spatial reference point to determine the relative spatial coordinates and reference distances within the conductor region, constructing a signal analysis and positioning reference framework, including:

[0015] The geometric center points of the crimped terminals at both ends of the energy storage cable corresponding to the ultrasonic signal acting on the conductor region, and the connection point of the grounding end of the cable shield, are identified and calibrated, and are collectively defined as spatial reference points.

[0016] Using a spatial reference point as input, the absolute coordinates of the spatial reference point in a three-dimensional coordinate system with the detection device as the origin are calculated by a positioning device integrated on the ultrasonic testing device.

[0017] Using absolute coordinates as input, a coordinate transformation algorithm is used to map the absolute coordinates to the local space of the cable conductor region to obtain the mapping result; based on the mapping result, the relative spatial coordinates of each reference point in the conductor region and the reference distance between adjacent reference points are calculated, thereby establishing the relative coordinate system of the conductor region;

[0018] Based on the relative coordinate system and the calculated reference spacing, a signal analysis and localization reference frame covering the entire area of ​​the conductor to be detected is constructed.

[0019] Furthermore, by setting up regularized analysis units for the positioning reference frame, a signal acquisition strategy adjustment parameter is obtained based on the structural characteristics of the analysis units, including:

[0020] Based on the constructed signal analysis and localization reference framework, the structural characteristics of each analysis unit within the framework are quantized to obtain the structural quantization parameters of each analysis unit. The structural quantization parameters include the unit radius of curvature, the unit axial position coordinates, and the unit cross-sectional morphological features.

[0021] The structural quantization parameters of each analysis unit are input into a preset ultrasonic propagation characteristic analysis algorithm. Based on the acoustic propagation law of ultrasonic waves, the theoretical propagation path and expected signal attenuation distribution of ultrasonic waves corresponding to each analysis unit are calculated.

[0022] Based on the calculated theoretical propagation path of ultrasound and the expected signal attenuation distribution of each analysis unit, the signal acquisition optimization parameters corresponding to each analysis unit are calculated by the parameter optimization algorithm. The signal acquisition optimization parameters include the receiver gain compensation value, the signal filtering frequency band selection, and the sampling time window setting.

[0023] The calculated signal acquisition optimization parameters of all analysis units are integrated and processed to obtain unified signal acquisition strategy adjustment parameters.

[0024] Furthermore, parameters are adjusted according to the signal acquisition strategy to configure the operating mode of the ultrasonic receiver. Based on the transmitted ultrasonic signal, the echo signal returned from the conductor is acquired, and the time-domain waveform and spectral response data of the echo signal are recorded simultaneously to obtain an optimized echo signal dataset, including:

[0025] Based on the obtained signal acquisition strategy adjustment parameters, the operating parameters of the ultrasonic receiver are configured, including the receiving gain, filter center frequency and bandwidth, and signal sampling rate, to obtain the configured operating parameters of the ultrasonic receiver.

[0026] Based on the configured operating parameters of the ultrasonic receiver, a synchronous acquisition command is generated; based on the synchronous acquisition command, the ultrasonic receiver is controlled to synchronously acquire the echo signal returned from the conductor after the ultrasonic transmitter transmits the signal.

[0027] During the synchronous acquisition process, the time-domain waveform data and spectral response data of the echo signal are recorded synchronously to obtain the initial echo signal dataset;

[0028] The obtained initial echo signal dataset is subjected to signal optimization processing, which includes gain compensation and frequency band filtering based on the signal acquisition strategy adjustment parameters, to obtain an optimized echo signal dataset.

[0029] Furthermore, feature extraction analysis is performed on the optimized echo signal dataset to obtain a set of feature parameters including signal attenuation rate, resonant frequency offset, and echo time delay, including:

[0030] Based on the obtained optimized echo signal dataset, time-domain feature analysis is performed on the time-domain waveform data of the optimized echo signal dataset to extract the echo time delay corresponding to each analysis unit, so as to obtain the time-domain waveform data after the analysis is completed.

[0031] The analyzed time-domain waveform data is transformed in the frequency domain to obtain the spectral characteristics of each analysis unit. Peak detection and frequency component analysis are performed on the spectral characteristics to extract the resonant frequency offset corresponding to each analysis unit, so as to obtain the processed frequency domain response characteristics.

[0032] Based on the frequency domain response characteristics obtained from the processing, and combined with the intensity parameters of the initial transmitted signal, the signal attenuation rate corresponding to each analysis unit is calculated by the energy attenuation algorithm. The signal attenuation rate is obtained by comparing the energy difference between the received signal and the transmitted signal.

[0033] The extracted echo time delay, the extracted resonant frequency offset, and the calculated signal attenuation rate are integrated and organized according to the location identifier of the analysis unit to obtain a feature parameter set containing multi-dimensional feature parameters.

[0034] Furthermore, the set of feature parameters is matched and compared with a preset strand breakage feature threshold library to determine whether there is a strand breakage defect inside the conductor and to generate a corresponding identification signal, including:

[0035] Based on the set of characteristic parameters, the signal attenuation rate, resonant frequency offset and echo time delay contained in the set of characteristic parameters are normalized and converted into standardized characteristic parameters with unified dimensions.

[0036] The standardized feature parameters are matched and compared with the preset broken stock feature threshold library. By calculating the similarity between the standardized feature parameters of each analysis unit and each broken stock feature pattern in the threshold library, the defect similarity index of each analysis unit is obtained.

[0037] Based on the defect similarity index of each analysis unit, the pre-set judgment rules are applied to determine the broken strand defect status of each analysis unit. The judgment rules include similarity threshold comparison rules and multi-parameter joint judgment rules to obtain the judgment analysis results.

[0038] Based on the judgment and analysis results, a broken strand defect identification signal containing defect location identifiers and defect level information is generated.

[0039] Furthermore, based on the broken strand defect identification signal, a defect diagnosis report containing cable location information is automatically generated, and corresponding equipment maintenance management instructions are triggered accordingly, including:

[0040] Based on the strand breakage defect identification signal, the defect location identifier and defect level information contained in the strand breakage defect identification signal are extracted; the extracted defect information is associated and integrated with the spatial positioning information in the established conductor region relative coordinate system to form complete defect positioning data.

[0041] The integrated defect location data is input into the preset report generation device, which automatically generates a defect diagnosis report containing defect type, defect level, spatial location coordinates and suggested handling measures.

[0042] Perform integrity verification and standardized formatting on the defect diagnosis report, and output the final version of the defect diagnosis report that conforms to the preset specifications;

[0043] Based on the verified defect diagnosis report, and according to the preset maintenance strategy rule base, the corresponding equipment maintenance management instructions are automatically matched and triggered.

[0044] Secondly, the ultrasonic feature identification and management system for broken strands in the internal conductors of energy storage cables includes:

[0045] The acquisition module is used to directionally transmit ultrasonic signals with a frequency range of 1MHz to 10MHz to the conductor area of ​​the energy storage cable through an ultrasonic transmitting device, so that the ultrasonic signals penetrate the cable insulation layer and act on the conductor.

[0046] The optimization module is used to optimize the conductor region based on the action of ultrasonic signals. It uses the structural features of the crimp terminals at both ends of the energy storage cable conductor and the grounding end of the cable shield as spatial reference points. Three-dimensional coordinate calculations are performed on each spatial reference point to determine its relative spatial coordinates and reference spacing within the conductor region, constructing a signal analysis and positioning reference frame. By setting regularized analysis units within the positioning reference frame, a signal acquisition strategy adjustment parameter is obtained based on the structural characteristics of the analysis units. Based on the signal acquisition strategy adjustment parameter, the operating mode of the ultrasonic receiver is configured, and based on the transmitted ultrasonic signal, the echo signal returned from the conductor is acquired. The time-domain waveform and spectral response data of the echo signal are recorded simultaneously to obtain an optimized echo signal dataset.

[0047] The extraction module is used to perform feature extraction analysis based on the optimized echo signal dataset to obtain a set of feature parameters including signal attenuation rate, resonant frequency offset and echo time delay.

[0048] The comparison module is used to match and compare the set of feature parameters with the preset strand breakage feature threshold library to determine whether there is a strand breakage defect inside the conductor and generate a corresponding identification signal.

[0049] The processing module is used to automatically generate a defect diagnosis report containing cable location information based on the broken strand defect identification signal, and trigger corresponding equipment maintenance management instructions accordingly.

[0050] The above-described solution of the present invention has at least the following beneficial effects:

[0051] This method employs a technique that involves directional transmission of 1MHz to 10MHz ultrasonic signals to penetrate the cable insulation layer, using the crimped terminals at both ends of the cable and the grounding end of the shielding layer as reference points to construct a three-dimensional coordinate calculation and signal analysis and positioning reference framework, dynamically optimizing signal acquisition parameters according to the structural characteristics of the analysis unit, extracting multi-dimensional features such as signal attenuation rate, resonant frequency offset, and echo time delay, and performing similarity matching with a broken strand feature threshold library, automatically generating a defect diagnosis report containing spatial positioning information and triggering corresponding operation and maintenance instructions. This overcomes the technical problems of traditional TDR detection's insufficient sensitivity to minor broken strands, traditional ultrasonic detection's low signal-to-noise ratio due to fixed acquisition parameters being affected by cable bending or cross-sectional changes, inability to accurately locate broken strands, and the need for manual intervention in operation and maintenance after defect identification, leading to delayed response. Ultimately, this method achieves high accuracy in identifying broken strands in the internal conductors of energy storage cables, broken strand location accuracy of less than or equal to 5mm, automated closed-loop process from detection to identification to reporting to operation and maintenance, reduced downtime due to cable broken strand faults, and ensured the safe, stable, and reliable operation of energy storage cables. Attached Figure Description

[0052] Figure 1 This is a schematic flowchart of the ultrasonic feature identification and management method for broken strands of internal conductors in energy storage cables provided by an embodiment of the present invention.

[0053] Figure 2 This is a schematic diagram of an ultrasonic feature identification and management system for broken strands of the internal conductor of an energy storage cable provided in an embodiment of the present invention. Detailed Implementation

[0054] Exemplary embodiments of the present disclosure will now be described in more detail with reference to the accompanying drawings. While exemplary embodiments of the present disclosure are shown in the drawings, it should be understood that the present disclosure may be implemented in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the disclosure to those skilled in the art.

[0055] like Figure 1As shown, an embodiment of the present invention proposes an ultrasonic feature identification and management method for broken strands in the internal conductors of energy storage cables. The method includes the following steps:

[0056] Step 1: Directly transmit ultrasonic signals with a frequency range of 1MHz to 10MHz to the conductor area of ​​the energy storage cable through an ultrasonic transmitting device, so that the ultrasonic signals penetrate the cable insulation layer and act on the conductor.

[0057] Step 2: Based on the conductor region affected by the ultrasonic signal, the structural features of the crimp terminals at both ends of the energy storage cable conductor and the grounding end of the cable shield layer are used as spatial reference points; the three-dimensional coordinates of each spatial reference point are calculated to determine the relative spatial coordinates and reference spacing within the conductor region, and a signal analysis and positioning reference framework is constructed.

[0058] Step 3: By setting up regularized analysis units for the positioning reference frame, a signal acquisition strategy adjustment parameter is obtained based on the structural characteristics of the analysis units;

[0059] Step 4: Adjust parameters according to the signal acquisition strategy, configure the working mode of the ultrasonic receiver, and acquire the echo signal returned from the conductor based on the transmitted ultrasonic signal. Simultaneously record the time-domain waveform and spectral response data of the echo signal to obtain an optimized echo signal dataset.

[0060] Step 5: Perform feature extraction analysis based on the optimized echo signal dataset to obtain a set of feature parameters including signal attenuation rate, resonant frequency offset, and echo time delay.

[0061] Step 6: Match and compare the set of feature parameters with the preset strand breakage feature threshold library to determine whether there is a strand breakage defect inside the conductor and generate the corresponding identification signal.

[0062] Step 7: Based on the broken strand defect identification signal, automatically generate a defect diagnosis report containing cable location information, and trigger corresponding equipment maintenance management instructions accordingly.

[0063] In this embodiment of the invention, the following technical means are employed: directional transmission of 1MHz to 10MHz ultrasonic signals to penetrate the cable insulation layer and act on the conductor; three-dimensional coordinate calculation and signal analysis positioning reference framework are constructed using the crimped terminals at both ends of the energy storage cable and the grounding end of the shielding layer as spatial reference points; the positioning reference framework is divided into regularized analysis units, and signal acquisition strategy adjustment parameters are determined according to structural characteristics; an ultrasonic receiving device is configured based on the parameters to obtain an optimized echo signal dataset; a set of characteristic parameters, including signal attenuation rate, resonant frequency offset, and echo time delay, are extracted from the dataset and matched with a preset broken strand feature threshold library to determine defects; and a diagnostic report containing positioning information is automatically generated based on the defect identification signal, triggering maintenance instructions. Therefore, this invention overcomes the technical problems of traditional detection methods, such as insufficient sensitivity to minor broken strands, inability to accurately locate broken strands, low signal-to-noise ratio due to fixed acquisition parameters in complex cable structures, and delayed maintenance response requiring manual intervention after defect determination. This achieves the technical effects of accurately identifying broken strands inside the energy storage cable conductor, precisely locking the broken strand location, automating the entire process from detection to judgment to reporting to maintenance, improving the accuracy of broken strand identification and positioning, shortening downtime due to cable broken strand faults, and ensuring stable and safe operation.

[0064] In a preferred embodiment of the present invention, step 1 above may include:

[0065] Step 1.1: Perform cable connection status detection. Based on the detection results, determine the detectable sections of the cable conductor area. Configure the transmission parameters of the ultrasonic transmitter according to the physical characteristics of the detectable sections. The transmission parameters include the center frequency, transmission power, and waveform modulation mode selected within the range of 1MHz to 10MHz. Control the ultrasonic transmitter to transmit ultrasonic signals directionally to the detectable sections according to the configured transmission parameters. Confirm that the ultrasonic signal has penetrated the cable insulation layer and acted on the conductor through a signal penetration verification algorithm. Specifically, this includes: First, perform cable connection status detection. Personnel use dedicated connection status detection equipment to check the connection points between the two ends of the energy storage cable and the energy storage device to see if there is any looseness, oxidation, or poor contact. At the same time, check the sealing status and connection stability of the cable intermediate joint to eliminate situations where connection problems may interfere with the propagation of ultrasonic signals. Based on these detection results, select sections with good connection status, no connection faults, and where the conductor can normally receive and conduct ultrasonic signals. These sections are determined as the detectable sections of the cable conductor area to avoid invalid detection of sections where abnormal connections may affect signal propagation. Analyze the physical characteristics of the detectable sections, including the thickness and material of the cable insulation layer and the cross-sectional dimensions of the conductor in that section. Based on these physical characteristics, the transmission parameters of the ultrasonic transmitter are configured. If the insulation layer of the detectable section is thick or the material density is high, a relatively high center frequency is selected from the range of 1 MHz to 10 MHz, while the transmission power is appropriately increased to ensure that the ultrasonic signal has sufficient energy to penetrate the insulation layer. If the insulation layer is thin and the conductor cross-section is small, a moderate center frequency and transmission power are selected to prevent excessive signal attenuation or unnecessary damage to the conductor. The waveform modulation mode is determined according to the length of the detectable section. Longer detectable sections use continuous wave modulation mode to ensure continuous signal coverage, while shorter detectable sections use pulse wave modulation mode to improve signal resolution.

[0066] The configured center frequency, transmission power, and waveform modulation mode parameters are input into the control terminal of the ultrasonic transmitter. The control terminal generates corresponding control commands based on these parameters, driving the transducer of the ultrasonic transmitter to transmit ultrasonic signals directionally to the previously determined detectable section according to the commands. During transmission, the transducer maintains stable contact with the cable surface to ensure that the signal propagates to the cable conductor area in the set direction. The signal penetration verification process is then initiated. The ultrasonic receiver first collects the initial signal reflected from the cable surface, and then collects the feedback signal after propagation through the cable. These two types of signals are transmitted to the signal processing unit of the ultrasonic testing equipment. The amplitude changes and propagation time of the initial signal and the feedback signal are compared. If the amplitude of the feedback signal is within the expected range for the ultrasonic wave to penetrate the insulation layer and act on the conductor, and the propagation time is consistent with the theoretical time calculated based on the insulation layer thickness and conductor position, it is confirmed that the ultrasonic signal has penetrated the cable insulation layer and acted on the conductor. If it does not meet the requirements, the transmission parameters are adjusted and the signal transmission and verification are repeated until the signal is confirmed to meet the testing requirements.

[0067] In this embodiment of the invention, the technical means of performing cable connection status detection to determine the detectable section of the conductor area, configuring the center frequency, transmission power and waveform modulation mode of the ultrasonic transmitting device from 1MHz to 10MHz according to the physical characteristics of the detectable section, directionally transmitting signals according to the configured parameters, and confirming the signal penetration through the insulation layer and acting on the conductor through the signal penetration verification algorithm, overcomes the technical problems in traditional ultrasonic testing, such as the blind detection range caused by not pre-locking the effective detection section, and the signal being unable to penetrate the insulation layer or act accurately on the conductor due to not adapting the fixed transmission parameters to the physical characteristics of the cable. Thus, it achieves accurate delineation of the effective detection range, ensures that the transmission parameters are highly matched with the cable characteristics, and ensures that the ultrasonic signal actually acts on the conductor.

[0068] In a preferred embodiment of the present invention, step 2 above may include:

[0069] Step 2.1: Identify and mark the geometric center points of the crimped terminals at both ends of the energy storage cable corresponding to the ultrasonic signal acting on the conductor area, as well as the connection point of the grounding end of the cable shield. These points are collectively defined as spatial reference points. Specifically, this involves: First, determining the conductor area of ​​the energy storage cable affected by the current ultrasonic signal. Then, processing the crimped terminals at both ends of the cable corresponding to the area. Using a high-definition industrial camera, taking an image of the appearance of the crimped terminals, and observing the geometric contour of the crimped terminals by magnifying the image, finding the longest horizontal axis and the longest vertical axis of the terminal end face. The intersection of the two axes is the geometric center point of the crimped terminal, and marking it clearly with a special marker pen. Next, locate the grounding end of the cable shield and confirm the connection position between the grounding wire and the cable shield. This is usually the contact point between the grounding bolt and the shield or the welding point between the grounding wire and the shield. This contact point or welding point is the connection point of the grounding end of the cable shield, and it is also marked with a marker pen. Finally, the marked geometric center points of the crimped terminals at both ends and the connection point of the grounding end of the shield are collectively determined as spatial reference points for subsequent positioning, ensuring that all reference points directly correspond to the conductor area affected by the current ultrasonic signal, and avoiding the misalignment of the reference points with the detection area.

[0070] Step 2.2: Using the spatial reference point as input, the absolute coordinates of the spatial reference point in a three-dimensional coordinate system with the testing device as the origin are calculated through the positioning device integrated on the ultrasonic testing device. Specifically, this includes: the operator activating the positioning device integrated on the ultrasonic testing device, which includes a laser positioning component and an inertial measurement unit; first, placing the ultrasonic testing device on a stable plane next to the cable to be tested, and establishing a three-dimensional coordinate system with the center position of the testing device as the origin, where the x-axis is along the length of the testing device, the y-axis is perpendicular to the front testing surface of the testing device, and the z-axis is perpendicular to the plane formed by the x-axis and y-axis; then controlling the laser positioning component to emit a laser beam, aiming at each marked spatial reference point respectively, the laser positioning component measuring the straight-line distance from the origin to each reference point, and the inertial measurement unit measuring the angle between the laser beam and each coordinate axis of the three-dimensional coordinate system; based on the measured straight-line distance and angle, the x-axis coordinate, y-axis coordinate, and z-axis coordinate of each spatial reference point in the three-dimensional coordinate system are obtained through geometric calculation. These coordinates are the absolute coordinates of the spatial reference point. After the calculation is completed, all absolute coordinate data are stored in the storage component of the ultrasonic testing device.

[0071] Step 2.3: Using absolute coordinates as input, a coordinate transformation algorithm maps the absolute coordinates to the local space of the cable conductor area, obtaining the mapping result. Based on the mapping result, the relative spatial coordinates of each reference point within the conductor area and the reference distance between adjacent reference points are calculated, thereby establishing the relative coordinate system of the conductor area. Specifically, this includes: the staff retrieving the absolute coordinates of each spatial reference point from the storage component of the ultrasonic testing device and inputting the absolute coordinates into the coordinate transformation processing stage; the stage runs the coordinate transformation algorithm according to the actual laying path and structural form of the cable conductor area. For example, when the cable conductor is bent, the algorithm will adjust the coordinate mapping relationship according to the curvature of the bend, and the absolute coordinates with the testing device as the origin will be transformed. The coordinates are converted into local spatial coordinates with the cable conductor area as the core. After mapping, the coordinate values ​​of each reference point in the local space are extracted from the mapping results. These values ​​are the relative spatial coordinates of each reference point in the conductor area. Then, the straight-line distance between two adjacent reference points is calculated. For example, the distance between the geometric center point of one crimp terminal and the connection point of the shielding layer grounding end, and the distance between the connection point of the shielding layer grounding end and the geometric center point of the other crimp terminal are calculated. The distance is the reference spacing between adjacent reference points. Finally, taking one of the reference points, usually the geometric center of one crimp terminal, as the local origin, and combining the relative spatial coordinates of other reference points and the reference spacing, a relative coordinate system covering only the cable conductor area is established.

[0072] Step 2.4: Based on the relative coordinate system and the calculated reference spacing, construct a signal analysis and positioning reference frame covering the entire conductor region to be detected. Specifically, this includes: using the established relative coordinate system of the conductor region as a basis, and combining it with the calculated reference spacing, planning the coverage area of ​​the signal analysis and positioning reference frame; first, determining the overall length of the frame according to the reference spacing, ensuring that the starting point of the frame is aligned with the geometric center point of one crimping terminal and the ending point is aligned with the geometric center point of the other crimping terminal, completely encompassing the entire conductor region to be detected; then, according to the detection accuracy requirements, dividing the frame along the axis of the relative coordinate system into several uniform analysis units. For example, if the reference spacing is 5 meters and the required detection accuracy is 5 millimeters, then the frame is divided into 1000 analysis units, each unit corresponding to a 5-millimeter conductor segment. Labeling the corresponding relative coordinate range for each analysis unit, for example, the coordinate range of the first unit is from the local origin to 5 millimeters, the second unit is from 5 millimeters to 10 millimeters, and so on. Simultaneously, the position information of each reference point is recorded in the framework to ensure that the coordinates of the reference points and the analysis unit can correspond to each other, ultimately forming a signal analysis and positioning reference framework with a clear structure, well-defined coordinates, and coverage of the entire conductor area to be detected.

[0073] In this embodiment of the invention, a technical approach is adopted, which involves identifying and calibrating the connection point between the geometric center point of the crimped terminals at both ends of the energy storage cable and the grounding point of the cable shield as a spatial reference point; calculating the absolute coordinates of the reference point in a three-dimensional coordinate system with the detection device as the origin using a positioning device integrated on the ultrasonic testing device; mapping the absolute coordinates to the local space of the conductor using a coordinate transformation algorithm and calculating the relative coordinates and the reference distance to establish a relative coordinate system for the conductor region; and constructing a signal analysis positioning reference frame covering the entire conductor region to be tested based on the relative coordinate system and the reference distance. Therefore, this approach overcomes the technical problems of traditional detection methods, such as the lack of a reliable spatial reference, the inability to establish a dedicated positioning system for the conductor region leading to ambiguity in the location of strand breakage defects, and the lack of a unified reference frame for signal analysis affecting positioning accuracy. As a result, this approach achieves the technical effect of providing accurate spatial coordinate references for echo signal analysis, realizing precise location locking of strand breakage defects within the conductor region, and improving the positioning accuracy of strand breakage defects.

[0074] In a preferred embodiment of the present invention, step 3 above may include:

[0075] Step 3.1: Based on the constructed signal analysis and positioning reference framework, the structural characteristics of each analysis unit within the framework are quantified to obtain the structural quantification parameters of each analysis unit. These parameters include the unit's radius of curvature, axial position coordinates, and cross-sectional morphological features. Specifically, this involves: retrieving the constructed signal analysis and positioning reference framework to determine the number and distribution range of all analysis units within the framework; scanning the surface of each analysis unit using a laser contour scanner to obtain its curvature data; calculating the radius of curvature of the unit using the obtained curve contour, recording the radius of curvature as infinite if the unit is a straight line segment; then, comparing the relative coordinate system within the signal analysis and positioning reference framework, reading the axial coordinate values ​​of each analysis unit in the coordinate system, which are the unit's axial position coordinates, ensuring precise correspondence between the position of each unit and the coordinate system; finally, using an ultrasonic imaging device to image the cross-section of each analysis unit, observing its shape, and measuring its diameter, area, and other dimensions; and combining the shape and size information to determine the cross-sectional morphological features of the unit.

[0076] Step 3.2 involves inputting the acquired structural quantization parameters of each analysis unit into a pre-set ultrasonic propagation characteristic analysis algorithm. Based on the acoustic propagation law of ultrasound, the algorithm calculates the theoretical propagation path and expected signal attenuation distribution of ultrasound for each analysis unit. Specifically, this includes: inputting the acquired structural quantization parameters of each analysis unit into the ultrasonic propagation characteristic analysis algorithm pre-set in the ultrasonic detection device; the algorithm calculates based on the acoustic propagation law of ultrasound in different media and structures. For example, when the analysis unit is curved, i.e., has a radius of curvature, the algorithm simulates the reflection and refraction process of ultrasound in the curved path to determine the complete path of the sound wave from emission to contact conductor and back to the receiving device, which is the theoretical propagation path of ultrasound; at the same time, the algorithm combines the cross-sectional morphological characteristics of the unit, such as the size of the cross-sectional area, whether the shape is regular, and the acoustic impedance data of the cable conductor and insulation layer, to calculate the energy loss of ultrasound during propagation due to medium absorption, interface reflection, etc., and thus obtain the expected energy attenuation of the ultrasonic signal from emission to reception in the analysis unit, presented in the form of an attenuation curve or attenuation value range, forming the expected signal attenuation distribution.

[0077] Step 3.3: Based on the calculated theoretical ultrasonic propagation path and expected signal attenuation distribution of each analysis unit, the signal acquisition optimization parameters for each analysis unit are calculated using a parameter optimization algorithm. These parameters include the receiver gain compensation value, signal filtering frequency band selection, and sampling time window setting. Specifically, based on the calculated theoretical ultrasonic propagation path and expected signal attenuation distribution of each analysis unit, the parameter optimization algorithm is initiated. For the receiver gain compensation value, if the expected signal attenuation distribution of a certain analysis unit shows a large attenuation (e.g., exceeding 15 dB), the algorithm calculates the required gain increase to compensate for the signal attenuation and ensure sufficient received signal strength; if the attenuation is small... To avoid signal overload, the gain is appropriately reduced. For signal filtering frequency band selection, the algorithm combines the interference frequencies that may appear in the theoretical propagation path, such as the low-frequency interference that is easily generated by the bending section of the cable, and selects the frequency band range of 1 MHz to 10 MHz that can retain the effective ultrasonic signal and filter the interference frequencies, and determines the center frequency and bandwidth of the filter. For sampling time window setting, the algorithm calculates the time required for the ultrasonic wave to travel to and from the source based on the length of the theoretical propagation path, and sets the sampling time window to 1.2 to 1.5 times that time to ensure that the returned echo signal can be completely captured and to avoid signal truncation or omission. Each analysis unit obtains the corresponding receiver gain compensation value, signal filtering frequency band selection and sampling time window setting through the above calculations.

[0078] Step 3.4 integrates the calculated signal acquisition optimization parameters of all analysis units to obtain unified signal acquisition strategy adjustment parameters. Specifically, this includes: collecting the signal acquisition optimization parameters of all analysis units and arranging them according to the axial position coordinates of each analysis unit in the signal analysis positioning reference frame; during the arrangement process, checking the continuity of parameters between adjacent analysis units; if there are significant differences in gain compensation values ​​or filtering frequency bands between adjacent units, such as a gain difference exceeding 8 dB or a filtering center frequency difference exceeding 1 MHz, then the parameters in the intermediate transition region are smoothly adjusted to avoid parameter abrupt changes that could lead to instability in the receiving device's operating state; simultaneously, the sampling time windows of all units are integrated according to the time variation pattern of the propagation path to form a continuous time window sequence corresponding to the unit position; finally, all adjusted parameters are organized into a table or parameter instruction sequence according to the correspondence between the analysis unit position, gain compensation value, filtering frequency band, and sampling time window. This table or sequence constitutes the unified signal acquisition strategy adjustment parameters.

[0079] In this embodiment of the invention, the structural characteristics of each analysis unit are quantified based on a signal analysis and positioning reference framework to obtain the unit's radius of curvature, axial position coordinates, and cross-sectional morphological features. These quantified structural parameters are input into a preset ultrasonic propagation characteristic analysis algorithm to calculate the theoretical ultrasonic propagation path and expected signal attenuation distribution of each unit. Through parameter optimization algorithms, signal acquisition optimization parameters such as receiver gain compensation value, signal filtering frequency band selection, and sampling time window setting for each unit are obtained. Finally, the optimized parameters of all units are integrated and processed to obtain a unified signal acquisition strategy adjustment parameter. This overcomes the technical problem of traditional ultrasonic testing using fixed acquisition parameters, which cannot adapt to the structural differences of different analysis units in the cable, resulting in inaccurate ultrasonic propagation analysis and the acquisition signal being easily affected by the structure, leading to abnormal attenuation or noise interference. Thus, it achieves precise matching between signal acquisition parameters and the structural characteristics of each analysis unit, ensuring the accuracy of ultrasonic signal propagation analysis and the high quality of the acquired signal.

[0080] In a preferred embodiment of the present invention, step 4 above may include:

[0081] Step 4.1: Based on the obtained signal acquisition strategy adjustment parameters, configure the operating parameters of the ultrasonic receiver. These parameters include receiver gain, filter center frequency and bandwidth, and signal sampling rate. This process involves retrieving the previously obtained signal acquisition strategy adjustment parameters from the ultrasonic testing device's storage unit, specifying the exact values ​​for receiver gain, filter center frequency and bandwidth, and signal sampling rate for each analysis unit. Then, operate the ultrasonic receiver's parameter configuration interface, inputting the receiver gain value from the strategy adjustment parameters into the receiver's gain adjustment module. This is done by rotating the gain knob on the device or inputting the value on the interface, ensuring the actual receiver gain matches the strategy parameters. For example, if a certain value in the strategy parameters... If the receiver gain of the analysis unit needs to be compensated by 5 dB, adjust the gain value to the corresponding level. Next, in the filter setting interface of the receiver, input the filter center frequency and bandwidth values ​​in the strategy parameters, such as setting the center frequency to 5 MHz and the bandwidth to 2 MHz, to ensure that the filter only allows signals within this frequency band to pass through and filters out external interference frequencies. Finally, according to the signal sampling rate requirements in the strategy parameters, adjust the data acquisition component of the receiver to ensure that the sampling rate meets the requirements for capturing the details of the ultrasonic signal. Usually, the sampling rate is set to more than twice the highest frequency of the signal. For example, if the highest frequency of the signal is 10 MHz, the sampling rate should be set to more than 20 MHz. After all parameters are configured, start the parameter self-check function of the receiver to check whether each working parameter is completely matched with the strategy adjustment parameters to ensure that there are no configuration errors.

[0082] Step 4.2: Generate a synchronous acquisition command based on the configured operating parameters of the ultrasonic receiver. Based on this command, control the ultrasonic receiver to synchronously acquire the echo signal returning from the conductor after the ultrasonic transmitter emits a signal. Specifically, on the control interface of the ultrasonic testing device, click the synchronous acquisition command generation button. The device will automatically read the configured operating parameters of the ultrasonic receiver and combine them with the transmission parameters of the ultrasonic transmitter, such as the duration and interval of the transmitted signal, to generate a synchronous acquisition command. The command includes the transmitter's trigger signal and the receiver's acquisition start time, ensuring that the receiver can start acquisition within a preset time after the transmitter emits the ultrasonic signal, avoiding missed echo signals due to time differences. Subsequently, the operator sends the synchronous acquisition command to the control components of both the ultrasonic transmitter and receiver. After receiving the command, the transmitter begins directional transmission of the ultrasonic signal according to the preset transmission parameters. After receiving the command, the receiver starts acquisition preparation simultaneously with the transmitter's signal transmission. Once the ultrasonic signal acts on the conductor and returns, it immediately begins acquiring the echo signal. Throughout the process, the device's built-in clock synchronization module maintains consistency between transmission and acquisition time, preventing invalid signals from being acquired due to asynchrony.

[0083] Step 4.3: During the synchronous acquisition process, the time-domain waveform data and spectral response data of the echo signal are recorded simultaneously to obtain the initial echo signal dataset. Specifically, during the synchronous acquisition process, the data acquisition card of the ultrasonic receiver records the voltage value of the echo signal changing over time in real time according to the configured signal sampling rate, forming the time-domain waveform data of the echo signal. During the recording process, a voltage data point is stored at fixed time intervals to ensure that the time-domain waveform can completely reflect the time-varying characteristics of the signal. At the same time, the frequency domain analysis component built into the receiver continuously processes the real-time acquired time-domain signal, converting the time-domain signal into spectral data corresponding to the frequency and signal amplitude, forming the spectral response data of the echo signal. This data can clearly show the distribution of different frequency components in the signal. The staff monitors the recording status of the time-domain waveform data and spectral response data in real time through the display interface of the detection device to ensure that the two types of data are stored synchronously and without loss. After the acquisition is completed, the two types of data are classified and labeled according to the corresponding analysis units. For example, a certain group of data is labeled as the third analysis unit in the signal analysis and positioning reference frame. Finally, all labeled time-domain waveform data and spectral response data are integrated to form the initial echo signal dataset.

[0084] Step 4.4 involves signal optimization processing of the obtained initial echo signal dataset. This processing includes gain compensation and band filtering based on the signal acquisition strategy adjustment parameters, resulting in an optimized echo signal dataset. Specifically, this includes: activating the signal optimization processing function of the ultrasonic detection device; firstly, performing gain compensation processing on the time-domain waveform data in the initial echo signal dataset; adjusting the voltage amplitude of each data point in the time-domain waveform data of each analysis unit according to the receiving gain compensation value corresponding to each analysis unit in the signal acquisition strategy adjustment parameters. For example, if the gain compensation value of an analysis unit is 8 dB, then the amplitude of all time-domain data points of the unit is amplified proportionally to compensate for the energy attenuation of ultrasonic waves during propagation, restoring the signal amplitude to a reasonable range; subsequently, performing band filtering processing by calling a digital filter with the same center frequency and bandwidth as the filter in the signal acquisition strategy adjustment parameters to filter the gain-compensated time-domain waveform data, removing interference signals outside the band, such as filtering out low-frequency interference below 2 MHz and high-frequency noise above 8 MHz, retaining the effective ultrasonic signal in the range of 1 MHz to 10 MHz. After filtering, the data is analyzed again to check whether the interference frequency components in the spectral response data have been removed. At the same time, the signal-to-noise ratio of the optimized signal is measured to ensure that the signal-to-noise ratio is improved to above 25 dB to meet the requirements of subsequent feature extraction. Finally, the time-domain waveform data after gain compensation and frequency band filtering are integrated with the spectral response data to form an optimized echo signal dataset.

[0085] In this embodiment of the invention, the receiving gain, filter center frequency and bandwidth, and signal sampling rate of the ultrasonic receiving device are configured based on the signal acquisition strategy. A synchronous acquisition command is generated to control the receiving device to synchronously acquire the echo signal after the transmitting device transmits the signal. The time-domain waveform and spectral response data of the echo signal are recorded synchronously to form an initial dataset. Then, the initial dataset is optimized by adjusting the parameters based on the signal acquisition strategy. Therefore, this method overcomes the technical problems in traditional ultrasonic testing, such as fixed operating parameters of the receiving device, asynchronous acquisition and transmission leading to easy omission or interference of the echo signal, and low signal-to-noise ratio and lack of prominent effective features due to the lack of targeted optimization of the initial data. This method achieves precise matching of the operating parameters of the receiving device with the testing requirements, complete synchronous acquisition of the echo signal, and improved signal-to-noise ratio and clearer features in the optimized data.

[0086] In a preferred embodiment of the present invention, step 5 above may include:

[0087] Step 5.1: Based on the obtained optimized echo signal dataset, perform time-domain feature analysis on the time-domain waveform data of the optimized echo signal dataset, extract the echo time delay corresponding to each analysis unit, and obtain the analyzed time-domain waveform data. Specifically, this includes: first, retrieving the optimized echo signal dataset and separating the time-domain waveform data corresponding to each analysis unit, ensuring that each data file is labeled with the corresponding analysis unit number; then, starting the time-domain waveform analysis tool, first determining the start time of the ultrasonic transmission signal, using the first obvious voltage inflection point of the output signal of the transmitting device as a reference, and recording this moment as time. Zero point; next, in the time domain waveform of each analysis unit, find the effective feature point of the echo signal, usually the moment when the echo signal amplitude reaches 50% of the maximum value, and record the moment as the echo arrival time; calculate the difference between the echo arrival time and the zero point, the difference is the echo time delay corresponding to the analysis unit; during the calculation process, if there is slight noise interference in the waveform, smoothing is used to remove fluctuations before determining the feature point, ensuring that the echo time delay of each analysis unit is accurate to the microsecond level, and finally record the delay amount with the analysis unit number to form a time domain analysis result table, and obtain the time domain waveform data after the analysis is completed.

[0088] Step 5.2 involves performing frequency domain transformation on the analyzed time-domain waveform data to obtain the spectral characteristics of each analysis unit. Peak detection and frequency component analysis are then performed on the spectral characteristics to extract the resonant frequency offset corresponding to each analysis unit, thus obtaining the processed frequency domain response characteristics. Specifically, this includes: importing the time-domain waveform data of each analyzed unit into the frequency domain transformation tool one by one. The tool converts the voltage-time variation data in the time domain into spectral data where the frequency varies with the amplitude, thus obtaining the spectral characteristics of each analysis unit; subsequently, the peak detection function is activated to search for amplitude in the spectral characteristics. The frequency point with the highest value is the conductor's resonant frequency, while excluding small-amplitude noise peaks caused by environmental interference in the spectrum. Standard resonant frequency data of normal energy storage cable conductors of the same model and under the same operating conditions are retrieved from the historical database of the ultrasonic testing device. The difference between the resonant frequency detected in the spectrum of the current analysis unit and the standard resonant frequency is calculated; this difference is the resonant frequency offset corresponding to the analysis unit. If an analysis unit has multiple broken strands, its resonant frequency offset will be greater than the offset of a single broken strand. The specific values ​​of the offsets need to be recorded separately, ultimately forming the frequency domain response characteristic table for each analysis unit.

[0089] Step 5.3: Based on the processed frequency domain response characteristics and combined with the intensity parameters of the initial transmitted signal, calculate the signal attenuation rate corresponding to each analysis unit using an energy attenuation algorithm. The signal attenuation rate is obtained by comparing the energy difference between the received and transmitted signals. Specifically, this includes: retrieving the initial transmitted signal intensity parameters from the parameter record of the ultrasonic transmitter, typically the peak amplitude or total energy value of the transmitted signal; then extracting the energy data of the received signal for each analysis unit from the obtained frequency domain response characteristics: calculating the total energy of the received signal by integrating the amplitude from 1 MHz to 10 MHz within the effective frequency range of the frequency domain characteristics; and then starting the energy attenuation algorithm. The total energy of the received signal is compared with the initial transmitted signal energy, and the difference between the two is calculated. Then, the difference is divided by the initial transmitted signal energy to obtain the energy attenuation ratio, which is the signal attenuation rate. If expressed in decibels, it is calculated through a specific conversion relationship. For example, if the initial transmitted energy is 100 units and the received energy is 80 units, the energy difference is 20 units, and the signal attenuation rate is 20%. During the calculation process, normal attenuation caused by differences in cable insulation thickness must be excluded. The normal attenuation range of this type of cable should be recorded in advance, such as within 5%, to ensure that the final signal attenuation rate only reflects the energy loss caused by conductor strand breakage. The attenuation rate of each analysis unit is recorded in correspondence with its number.

[0090] Step 5.4 integrates the extracted echo time delay, the extracted resonant frequency offset, and the calculated signal attenuation rate, organizing them according to the location identifier of the analysis unit to obtain a feature parameter set containing multi-dimensional feature parameters. Specifically, this includes: creating a feature parameter integration table, with the first column set as the analysis unit location identifier, such as sorting from 1 to N according to the unit number in the signal analysis positioning reference frame; then adding three new columns to the table, named echo time delay, resonant frequency offset, and signal attenuation rate respectively; filling the recorded echo time delay, resonant frequency offset, and signal attenuation rate of each unit into the corresponding cells according to the analysis unit location identifier; for example, for the analysis unit with location identifier 3, the corresponding data should be filled in as 0.8 microsecond echo time delay, 0.2 MHz resonant frequency offset, and 15% signal attenuation rate; after filling in the data, verifying the table data to check for missing parameters or mismatches with the unit number, ensuring that the three feature parameters of each analysis unit are complete and accurately correspond; finally, a feature parameter set containing the analysis unit location and multi-dimensional feature parameters is formed.

[0091] In this embodiment of the invention, time-domain feature analysis is performed on time-domain waveform data based on an optimized echo signal dataset to extract the echo time delay of each analysis unit. The analyzed time-domain data is then transformed in the frequency domain and the resonant frequency offset is extracted through peak detection and frequency component analysis. The signal attenuation rate is calculated using an energy attenuation algorithm in combination with the initial transmitted signal strength parameters. Finally, these three types of parameters are integrated according to the analysis unit position identifier to form a multi-dimensional feature parameter set. Therefore, this method overcomes the technical problems of traditional detection, such as the single feature extraction dimension, inability to fully reflect the signal characteristics of conductor strand breakage defects, resulting in insufficient basis for strand breakage judgment and low identification accuracy. Thus, it achieves the technical effect of obtaining feature parameters that can characterize strand breakage defects in multiple dimensions and improving the technical accuracy of identifying small strand breakage defects inside energy storage cables.

[0092] In a preferred embodiment of the present invention, step 6 above may include:

[0093] Step 6.1: Based on the feature parameter set, normalize the signal attenuation rate, resonant frequency offset, and echo time delay contained in the feature parameter set, converting them into standardized feature parameters with unified dimensions. Specifically, this includes: first, extracting three types of parameters—signal attenuation rate, resonant frequency offset, and echo time delay—from the feature parameter set for all analysis units, and then calculating the value range of each type of parameter. For example, calculate the signal attenuation rate for all analysis units, determining its minimum value (e.g., 5% in the normal range) and maximum value (e.g., 30% in the severely fragmented range); similarly, determine the range of the resonant frequency offset (e.g., 0 MHz to 1.5 MHz) and the range of the echo time delay. For example, 0.2 microseconds to 3 microseconds; then, normalization is performed on each type of parameter: taking the signal attenuation rate as an example, the actual value of the parameter is subtracted from the minimum value, and then divided by the difference between the maximum and minimum values ​​to obtain the standardized value of the parameter; the resonant frequency offset and echo time delay are calculated in the same way, and finally the three types of parameters are converted into standardized characteristic parameters between 0 and 1; during the processing, it is necessary to ensure that the three types of parameters of each analysis unit are normalized synchronously to avoid distortion of the standardization results due to statistical deviations in the value range, especially for the small broken section mentioned in the background, by accurately statistically measuring the value range, it is ensured that the small parameter differences can still be clearly reflected after standardization.

[0094] Step 6.2: Match and compare the standardized feature parameters with the preset strand breakage feature threshold library. Calculate the similarity between the standardized feature parameters of each analysis unit and the strand breakage feature patterns in the threshold library to obtain the defect similarity index for each analysis unit. Specifically, this includes: first, retrieving the preset strand breakage feature threshold library, which stores feature patterns of different strand breakage states and their corresponding standardized parameter ranges, including normal conductor patterns (e.g., standardized attenuation rate 0.1 to 0.2, frequency offset 0.1 to 0.2, delay 0.1 to 0.2), single-strand strand breakage patterns (e.g., standardized attenuation rate 0.3 to 0.5, frequency offset 0.3 to 0.5, delay 0.2 to 0.4), and multi-strand strand breakage patterns (e.g., standardized attenuation rate 0.6 to 1.0, frequency offset 0.6 to 1.0, delay...). The standardization parameters of each analysis unit are then compared with the various stock breakage feature patterns in the threshold library. The deviation between the standardized parameters of the analysis unit and the center value of the parameter range of a certain type of pattern is calculated. For example, if the standardized attenuation rate of an analysis unit is 0.4, the center value of the attenuation rate of the single stock breakage pattern is 0.4, and the deviation is 0; the standardized frequency offset is 0.4, the center value of the single stock pattern is 0.4, and the deviation is 0; the standardized delay is 0.3, the center value of the single stock pattern is 0.3, and the deviation is 0. The similarity between the analysis unit and the stock breakage pattern is obtained by summing the deviations of the three types of parameters and taking the reciprocal. The smaller the deviation, the higher the similarity. Finally, each analysis unit will correspond to multiple similarity values, and the highest similarity is taken as the defect similarity index of the unit.

[0095] Step 6.3: Based on the defect similarity index of each analysis unit, apply preset judgment rules to determine the breakage defect status of each analysis unit. The judgment rules include similarity threshold comparison rules and multi-parameter joint judgment rules to obtain the judgment analysis results. Specifically, this includes: first, retrieving the preset judgment rules. The similarity threshold comparison rule sets the following: when the defect similarity index is greater than or equal to 0.7, the analysis unit is suspected of having a breakage defect; when the similarity index is less than 0.7, it is temporarily judged as normal. The multi-parameter joint judgment rule sets the following: if at least two types of parameters in the standardized feature parameters of the analysis unit have similarity indices greater than or equal to 0.7, or the weighted sum of three types of parameters (signal attenuation rate weight 40%, resonance frequency offset weight 30%, echo time delay weight 30%) is greater than or equal to 0.7, then it is finally judged as having a breakage defect; if only a single parameter has a similarity greater than or equal to 0.7, or the weighted sum is less than 0.7, it is judged as normal, excluding misjudgments caused by fluctuations in a single parameter. Subsequently, for each analysis unit... These two types of rules are used: for example, if the defect similarity index of a certain analysis unit is 0.75, and the similarity of both the standardized attenuation rate and frequency offset parameters is greater than or equal to 0.7, the weighted sum is 0.72, which satisfies both rules and is judged as a single-share breakage defect; if the similarity index of a certain analysis unit is 0.71, but only the echo time delay parameter meets the standard, the weighted sum is 0.68, then it is judged as normal; through dual rule verification, the problem of misjudgment due to a single indicator in traditional detection in the background is avoided, ensuring the accuracy of the judgment of minor breakage.

[0096] Step 6.4: Based on the judgment and analysis results, generate a strand breakage defect identification signal containing defect location identifiers and defect level information. Specifically, this includes: First, extracting the location identifier corresponding to the analysis unit with the strand breakage defect, i.e., the unit number in the signal analysis and positioning reference frame, such as analysis unit number 8; then, classifying the defect level according to the defect similarity index: a similarity index of 0.7 to 0.8 corresponds to a minor defect, a single strand breakage, which does not affect short-term operation; 0.8 to 0.9 corresponds to a moderate defect, with 2 to 3 strand breaks, requiring maintenance within a specified period; 0.9 and above corresponds to a severe defect, with 4 or more strand breaks, requiring immediate shutdown for maintenance; subsequently, integrating the defect location identifiers and defect level information to generate a strand breakage defect identification signal. The signal contains core information such as the cable number, analysis unit location identifier, defect type, and defect level. For example, energy storage cable number DC-05, analysis unit 8, single strand breakage, minor defect.

[0097] In this embodiment of the invention, the signal attenuation rate, resonant frequency offset, and echo time delay in the feature parameter set are normalized to convert them into standardized feature parameters with unified dimensions. The standardized feature parameters are matched and compared with a preset broken strand feature threshold library, and the defect similarity index of each analysis unit is calculated. A preset judgment rule including similarity threshold comparison rules and multi-parameter joint judgment rules is applied to determine the broken strand defect status of each analysis unit. Based on the judgment and analysis results, a broken strand defect identification signal containing defect location identifier and defect level information is generated. Therefore, this method overcomes the technical problems in traditional detection, such as inconsistent comparison benchmarks due to inconsistent dimensions of feature parameters, the simplistic judgment rules that easily lead to minor false positives and false negatives in broken strands, and the inability to simultaneously determine the defect location and severity. This results in more accurate feature parameter comparison, more reliable broken strand defect judgment results, and the ability to simultaneously lock the specific location of the defect and distinguish the defect level.

[0098] In a preferred embodiment of the present invention, step 7 above may include:

[0099] Step 7.1: Based on the strand breakage defect identification signal, extract the defect location identifier and defect level information contained in the strand breakage defect identification signal; integrate the extracted defect information with the spatial positioning information in the established conductor area relative coordinate system to form complete defect positioning data. Specifically, this includes: after obtaining the strand breakage defect identification signal, extracting key information from it using a signal analysis tool, including the defect location identifier, i.e., the number of the corresponding analysis unit, such as analysis unit number 12, and the defect level, such as mild, moderate, or severe; then retrieving the previously established conductor area relative coordinate system to find the spatial positioning information corresponding to the location identifier, i.e., the specific coordinate values ​​of the analysis unit in the relative coordinate system, such as 3.5 meters on the x-axis, 0.2 meters on the y-axis, and 0.1 meters on the z-axis; associating the extracted defect level with the corresponding spatial coordinates, for example, analysis unit number 12 corresponds to a moderate strand breakage defect at coordinate 3.5 meters, integrating to form complete defect positioning data containing defect location number, level, and precise coordinates, ensuring that each defect corresponds one-to-one with a specific physical location on the cable conductor.

[0100] Step 7.2: Input the integrated defect location data into the preset report generation device. The device will automatically generate a defect diagnosis report containing the defect type, defect level, spatial coordinates, and suggested handling measures. Specifically, this includes: importing the integrated defect location data into the preset report generation device; the device has a built-in report template that automatically extracts information from the location data; the defect type is determined as a single strand break or multiple strand break based on the strand breakage characteristics; the defect level is directly based on the extracted level information; the spatial coordinates are filled with the associated relative coordinate coefficient values; and the suggested handling measures are automatically matched according to the defect level, for example, for minor defects, it is recommended to retest regularly; for moderate defects, it is recommended to arrange maintenance within 72 hours; and for severe defects, it is recommended to immediately shut down and replace the defect. The device automatically fills in the information according to the template structure to generate an initial defect diagnosis report containing all the information.

[0101] Step 7.3 involves verifying the completeness of the defect diagnosis report and standardizing its formatting to output a final version that conforms to preset specifications. This includes: activating the report verification function to check the completeness of the initial defect diagnosis report, confirming whether it contains all necessary information, such as whether the defect type is clearly defined, whether the level is marked, whether the coordinates are complete, and whether the suggested measures are reasonable. If there is missing information, such as the absence of spatial coordinates, the report is returned to the report generation device for supplementation and improvement. After verification, the report is standardized and formatted, unifying the font, font size, layout format, and terminology, such as standardizing the description of broken strands as "conductor broken strands," to ensure that the report conforms to the document specifications stipulated in the operation and maintenance management regulations for energy storage power stations. After processing, the final version of the defect diagnosis report is output.

[0102] Step 7.4: Based on the verified defect diagnosis report, and according to the preset maintenance strategy rule base, automatically match and trigger the corresponding equipment maintenance management instructions. Specifically, this includes: connecting the verified final version of the defect diagnosis report to the maintenance management platform; the platform automatically retrieves the preset maintenance strategy rule base; the rule base stores the processing rules corresponding to different defect levels, such as minor defects triggering periodic monitoring instructions, retesting every 24 hours; moderate defects triggering maintenance dispatch instructions, automatically assigned to the maintenance team and marked with priority; severe defects triggering emergency shutdown instructions, immediately cutting off the power supply to the circuit where the cable is located and pushing an alarm to the maintenance manager; the platform matches the corresponding rules according to the defect level in the report, automatically generates and triggers the corresponding equipment maintenance management instructions.

[0103] In this embodiment of the invention, defect location identifiers and grade information are extracted from the strand breakage defect identification signal. These are then integrated with the spatial positioning information of the conductor region relative to the coordinate system to form complete defect location data. The data is input into a report generation device to automatically generate a diagnostic report containing the defect type, grade, location coordinates, and suggested measures. After integrity verification and standardization processing, the final report is output. Based on the report, the corresponding operation and maintenance management instructions are automatically matched and triggered according to the preset maintenance strategy rule base. This overcomes the technical problems of vague defect location, low efficiency and non-standardization due to manual compilation of defect reports, and delayed response due to manual intervention in operation and maintenance after defect determination in traditional detection. As a result, it achieves the technical effects of accurate spatial positioning of strand breakage defects, automatic generation of standardized and complete defect diagnostic reports, rapid triggering of targeted operation and maintenance instructions, significantly shortening the response time from defect identification to operation and maintenance processing, reducing downtime due to cable strand breakage faults, and improving operation and maintenance efficiency and operational safety.

[0104] like Figure 2 As shown, embodiments of the present invention also provide an ultrasonic feature identification and management system for broken strands in the internal conductors of energy storage cables, including:

[0105] The acquisition module is used to directionally transmit ultrasonic signals with a frequency range of 1MHz to 10MHz to the conductor area of ​​the energy storage cable through an ultrasonic transmitting device, so that the ultrasonic signals penetrate the cable insulation layer and act on the conductor.

[0106] The optimization module is used to optimize the conductor region based on the action of ultrasonic signals. It uses the structural features of the crimp terminals at both ends of the energy storage cable conductor and the grounding end of the cable shield as spatial reference points. Three-dimensional coordinate calculations are performed on each spatial reference point to determine its relative spatial coordinates and reference spacing within the conductor region, constructing a signal analysis and positioning reference frame. By setting regularized analysis units within the positioning reference frame, a signal acquisition strategy adjustment parameter is obtained based on the structural characteristics of the analysis units. Based on the signal acquisition strategy adjustment parameter, the operating mode of the ultrasonic receiver is configured, and based on the transmitted ultrasonic signal, the echo signal returned from the conductor is acquired. The time-domain waveform and spectral response data of the echo signal are recorded simultaneously to obtain an optimized echo signal dataset.

[0107] The extraction module is used to perform feature extraction analysis based on the optimized echo signal dataset to obtain a set of feature parameters including signal attenuation rate, resonant frequency offset and echo time delay.

[0108] The comparison module is used to match and compare the set of feature parameters with the preset strand breakage feature threshold library to determine whether there is a strand breakage defect inside the conductor and generate a corresponding identification signal.

[0109] The processing module is used to automatically generate a defect diagnosis report containing cable location information based on the broken strand defect identification signal, and trigger corresponding equipment maintenance management instructions accordingly.

[0110] The above description represents the preferred embodiments of the present invention. It should be noted that those skilled in the art can make various improvements and modifications without departing from the principles of the present invention, and these improvements and modifications should also be considered within the scope of protection of the present invention.

Claims

1. A method for ultrasonic signature recognition management of broken strands of internal conductors of energy storage cables, characterized in that, The method includes: An ultrasonic transmitter directionally emits ultrasonic signals with a frequency range of 1MHz to 10MHz into the conductor area of ​​the energy storage cable, allowing the ultrasonic signals to penetrate the cable insulation layer and act on the conductor. Based on the conductor region affected by ultrasonic signals, the structural features of the crimp terminals at both ends of the energy storage cable conductor and the grounding end of the cable shield layer are used as spatial reference points; three-dimensional coordinate calculations are performed on each spatial reference point to determine the relative spatial coordinates and reference distance within the conductor region, and a signal analysis and positioning reference framework is constructed. By setting up regularized analysis units within the signal analysis and localization reference frame, a signal acquisition strategy adjustment parameter is obtained based on the structural characteristics of the analysis units, including: Based on the constructed signal analysis and localization reference framework, the structural characteristics of each analysis unit within the framework are quantized to obtain the structural quantization parameters of each analysis unit. The structural quantization parameters include the unit radius of curvature, the unit axial position coordinates, and the unit cross-sectional morphological features. The structural quantization parameters of each analysis unit are input into a preset ultrasonic propagation characteristic analysis algorithm. Based on the acoustic propagation law of ultrasonic waves, the theoretical propagation path and expected signal attenuation distribution of ultrasonic waves corresponding to each analysis unit are calculated. Based on the calculated theoretical propagation path of ultrasound and the expected signal attenuation distribution of each analysis unit, the signal acquisition optimization parameters corresponding to each analysis unit are calculated by the parameter optimization algorithm. The signal acquisition optimization parameters include the gain compensation value of the ultrasound receiving device, the selection of the signal filtering frequency band, and the setting of the sampling time window. The calculated signal acquisition optimization parameters of all analysis units are integrated and processed to obtain unified signal acquisition strategy adjustment parameters. The parameters are adjusted according to the signal acquisition strategy, the working mode of the ultrasonic receiver is configured, and the echo signal returned from the conductor is acquired based on the transmitted ultrasonic signal. The time-domain waveform and spectral response data of the echo signal are recorded simultaneously to obtain an optimized echo signal dataset. Based on the optimized echo signal dataset, feature extraction analysis is performed to obtain a set of feature parameters including signal attenuation rate, resonant frequency offset, and echo time delay. The set of feature parameters is matched and compared with a preset string breakage feature threshold library to determine whether there is a string breakage defect inside the conductor and generate a corresponding identification signal. Based on the broken strand defect identification signal, a defect diagnosis report containing cable location information is automatically generated, and corresponding equipment maintenance and management instructions are triggered accordingly.

2. The ultrasonic feature recognition management method of energy storage cable internal conductor strand breaks according to claim 1, characterized in that, Based on the conductor region affected by ultrasonic signals, the structural features of the crimp terminals at both ends of the energy storage cable conductor and the grounding end of the cable shield layer are used as spatial reference points. Three-dimensional coordinate calculations are performed on each spatial reference point to determine its relative spatial coordinates and reference spacing within the conductor region, thus constructing a signal analysis and positioning reference framework, including: The geometric center points of the crimped terminals at both ends of the energy storage cable corresponding to the ultrasonic signal acting on the conductor region, and the connection point of the grounding end of the cable shield, are identified and calibrated, and are collectively defined as spatial reference points. The absolute coordinates of the spatial reference points in a three-dimensional coordinate system with the ultrasonic detection device as the origin are calculated by a positioning device integrated on the ultrasonic detection device; The absolute coordinates are inputted, and the absolute coordinates are mapped to a local space of the cable conductor area by a coordinate transformation algorithm to obtain a mapping result; the relative spatial coordinates of each spatial reference point in the conductor area and the reference distance between adjacent spatial reference points are calculated based on the mapping result, so as to establish a relative coordinate system of the conductor area; Based on the relative coordinate system and the calculated reference distance, a signal analysis and positioning reference framework covering the entire conductor area to be detected is constructed.

3. The ultrasonic feature recognition management method of energy storage cable internal conductor strand breaks according to claim 2, characterized in that, According to the signal acquisition strategy adjustment parameters, the working mode of the ultrasonic receiving device is configured, and based on the transmitted ultrasonic signals, the echo signals returned from the conductor are collected, and the time domain waveform and spectrum response data of the echo signals are recorded synchronously to obtain an optimized echo signal data set, including: Based on the obtained signal acquisition strategy adjustment parameters, the working parameters of the ultrasonic receiving device are configured, including the receiving gain, filter center frequency and bandwidth, and signal sampling rate, to obtain the working parameters of the configured ultrasonic receiving device; According to the working parameters of the configured ultrasonic receiving device, a synchronous acquisition instruction is generated; based on the synchronous acquisition instruction, the ultrasonic receiving device is controlled to synchronously collect the echo signals returned from the conductor after the ultrasonic transmitting device transmits signals; During the synchronous acquisition process, the time domain waveform data and spectrum response data of the echo signals are recorded synchronously to obtain an initial echo signal data set; The obtained initial echo signal data set is subjected to signal optimization processing, including gain compensation and band filtering based on the signal acquisition strategy adjustment parameters, to obtain an optimized echo signal data set.

4. The ultrasonic feature recognition management method of energy storage cable internal conductor strand breaks according to claim 3, characterized in that, According to the optimized echo signal data set, feature extraction analysis is performed to obtain a feature parameter set including signal attenuation rate, resonance frequency offset and echo time delay, including: Based on the obtained optimized echo signal data set, time domain feature analysis is performed on the time domain waveform data of the optimized echo signal data set, and the echo time delay corresponding to each analysis unit is extracted to obtain analyzed time domain waveform data; The analyzed time domain waveform data is subjected to frequency domain transformation processing to obtain the spectral features of each analysis unit; by peak value detection and frequency component analysis on the spectral features, the resonance frequency offset corresponding to each analysis unit is extracted to obtain frequency domain response features; Based on the frequency domain response features, combined with the intensity parameters of the initial transmitted signals, the signal attenuation rate corresponding to each analysis unit is calculated by an energy attenuation algorithm; the signal attenuation rate is obtained by comparing the energy difference between the received signals and the transmitted signals; The extracted echo time delay, extracted resonance frequency offset and calculated signal attenuation rate are integrated and organized according to the position identifiers of the analysis units to obtain a feature parameter set containing multi-dimensional feature parameters.

5. The ultrasonic feature recognition management method of broken strands of the energy storage cable internal conductor according to claim 4, characterized in that, The feature parameter set is matched and compared with a preset broken strand feature threshold library to determine whether there is a broken strand defect in the conductor and generate a corresponding recognition signal, including: Based on the feature parameter set, the signal attenuation rate, resonance frequency offset and echo time delay contained in the feature parameter set are normalized to convert into standardized feature parameters of uniform dimension; The standardized feature parameters are matched and compared with the preset strand feature threshold library, the similarity of each analysis unit is obtained by calculating the similarity of each analysis unit and each strand feature mode in the strand feature threshold library, and the defect similarity index of each analysis unit is obtained; Based on the defect similarity index of each analysis unit, the preset judgment rule is applied to judge the strand defect state of each analysis unit, and the judgment rule includes similarity threshold comparison rule and multi-parameter joint judgment rule to obtain the judgment analysis result; According to the judgment analysis result, the strand defect recognition signal containing the defect position identifier and the defect level information is generated.

6. The ultrasonic feature recognition management method of energy storage cable internal conductor strand breaks according to claim 5, characterized in that, According to the strand defect recognition signal, a defect diagnosis report containing cable positioning information is automatically generated, and corresponding equipment maintenance management instructions are triggered, including: Based on the strand defect recognition signal, the defect position identifier and the defect level information contained in the strand defect recognition signal are extracted; the extracted defect information is associated and integrated with the spatial positioning information in the established conductor region relative coordinate system to form complete defect positioning data; The integrated defect positioning data is input into the preset report generation device to automatically generate a defect diagnosis report containing defect type, defect level, spatial position coordinates and recommended treatment measures; The integrity of the defect diagnosis report is verified and standardized formatting processing is performed, and the final version of the defect diagnosis report meeting the preset specification is output; Based on the verified defect diagnosis report, the corresponding equipment maintenance management instructions are automatically matched and triggered according to the preset maintenance strategy rule library.

7. An ultrasonic signature recognition management system for broken strands of internal conductors of an energy storage cable, the system implementing the method of any one of claims 1 to 6, characterized in that, The acquisition module is used to direct the ultrasonic wave signal with a frequency range of 1MHz to 10MHz to the conductor region of the energy storage cable through the ultrasonic wave emitting device, so that the ultrasonic wave signal penetrates the cable insulation layer and acts on the conductor; The optimization module is used to take the structure characteristics of the crimping terminals at both ends of the conductor of the energy storage cable and the grounding end of the cable shielding layer as spatial reference points based on the conductor region acted on by the ultrasonic wave signal; The three-dimensional coordinate of each spatial reference point is calculated to determine the relative spatial coordinates and reference distance in the conductor region, and a signal analysis positioning reference frame is constructed; the signal analysis positioning reference frame is set by regular analysis unit, a signal acquisition strategy adjustment parameter is obtained according to the structure characteristics of the analysis unit, the working mode of the ultrasonic wave receiving device is configured according to the signal acquisition strategy adjustment parameter, and the optimized echo signal data set is obtained based on the emitted ultrasonic wave signal and the echo signal returned from the conductor, and the time domain waveform and spectrum response data of the echo signal are recorded synchronously; The extraction module is used to perform feature extraction analysis according to the optimized echo signal data set to obtain a feature parameter set including signal attenuation rate, resonance frequency offset and echo time delay; The comparison module is used to match and compare the feature parameter set with the preset strand feature threshold library to determine whether there is a strand defect in the conductor and generate a corresponding recognition signal. ​ The processing module is used for generating a defect diagnosis report containing cable positioning information automatically according to the broken strand defect identification signal, and triggering corresponding equipment maintenance management instructions accordingly.

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