Cable testing method and related device

Abstract

The invention discloses a cable testing method and a related device. The method comprises the following steps: acquiring structural stress response data of a cable under the action of multidirectional mechanical stress; determining configuration parameters of a micro charge coupling detection channel according to the structural stress response data; according to the detection configuration data, collecting a transient charge signal in a cable high-frequency signal transmission process; establishing a mapping relation between multi-axis mechanical excitation and electrical interference according to the structural stress response data and the waveform sequence data; executing dynamic adjustment of cable transmission parameters according to the classification data; and recording a corresponding relation between the interference characteristics and the adjustment parameters according to the scheduling data. According to the technical scheme, multi-dimensional signal coupling analysis and self-adaptive scheduling are carried out on micro-charge interference of a novel nonmetal material of a cable, signal disturbance caused by the piezoelectric effect and the electrostatic friction effect of the material can be accurately recognized, real-time compensation is carried out on the interference, and technical support is provided for high-reliability communication.

Description

Technical Field

[0001] The present invention relates to the technical field of cable testing, and in particular to a cable testing method and related devices. Background Art

[0002] In contemporary high-speed data transmission applications, in order to meet the higher demands for cable toughness and durability, many manufacturers have begun to add new non-metallic materials as reinforcement layers or fillers inside the cables, such as modified polymers or nano-scale composite fiber structures. Such materials can provide stronger mechanical support in extreme environments, reduce losses and deformations during stretching or bending, and thus effectively improve the service life and stability of cables in high-frequency communications and precision measurement scenarios. However, since these new materials themselves have certain charge accumulation characteristics, especially under external force impact or long-term vibration, local piezoelectric coupling or electrostatic friction effects will occur, resulting in transient charge accumulation and affecting the signal transmission of the cable. If these subtle interferences cannot be monitored in time and accurately compensated, they will gradually amplify in the high-speed data stream, ultimately leading to a decrease in signal quality, reduced transmission efficiency, and even unforeseen failures.

[0003] Most existing automated testing methods only focus on measuring static or low-frequency parameters such as impedance, insulation, and conduction of cables under normal conditions. They are unable to effectively capture such small and continuous electrical disturbances, and lack the ability to dynamically track across multi-axis stress scenarios. Especially when faced with high reliability and high-bandwidth transmission requirements, any slight signal distortion may cause random fluctuations or instantaneous disconnection, and the mechanical and electrical coupling effects of new non-metallic materials inside the cable are more complex. Traditional testing methods make it difficult to locate the source of interference or analyze its generation mechanism, making it difficult to trace the cause of the fault, and increasing the cost of troubleshooting and repair. What's more serious is that once this type of interference accumulates in a special application environment, it will pose a substantial threat to measurement accuracy and data transmission stability, making it difficult to meet the stringent requirements of contemporary high-speed data transmission and precision measurement for continuous and reliable operation. Summary of the invention

[0004] The main purpose of the present invention is to solve the technical problem that the existing intelligent automatic testing of cables cannot effectively monitor and compensate for the micro-charge interference generated by non-metallic materials under multi-directional stress and high-frequency transmission conditions.

[0005] A first aspect of the present invention provides a cable testing method, the cable testing method comprising: Acquire structural stress response data of the cable under multi-directional mechanical stress, wherein the structural stress response data includes local deformation data of the material and its response data under different frequency excitations; Determining configuration parameters of a micro-charge coupled detection channel according to the structural stress response data, and generating detection configuration data including charge detection sensitivity, signal filtering parameters, and multi-channel switching logic; Acquiring a transient charge signal during the transmission of a high-frequency signal of a cable according to the detection configuration data, performing time correlation processing on the transient charge signal and a differential transmission waveform to obtain waveform sequence data with an interference event mark; According to the structural stress response data and the waveform sequence data, a mapping relationship between multi-axis mechanical excitation and electrical interference is established to generate classification data including interference source types and corresponding mechanical conditions; According to the classification data, when a preset mechanical condition is detected, the cable transmission parameters are dynamically adjusted, and the adjustment parameters are iteratively optimized based on the transmission performance feedback to generate scheduling data including the mechanical state and the electrical coupling relationship; According to the scheduling data, the corresponding relationship between the interference characteristics and the adjustment parameters of the cable under different stress and transmission conditions is recorded to generate dynamic health characteristic data of the cable.

[0006] Optionally, the acquiring of structural stress response data of the cable under multi-directional mechanical stress, wherein the structural stress response data includes local deformation data of the material and response data thereof under excitations at different frequencies, includes: Apply multi-directional mechanical stresses including bending stress and torsional stress to the cable to obtain static stress response data of the cable; Applying vibration excitations of different frequencies to the stress region in the static stress response data to obtain dynamic stress response data of the cable at each frequency; Extracting stress distribution data and local deformation data of each layer of cable material according to the static stress response data and the dynamic stress response data; The stress distribution data and the local deformation data of the material are subjected to time series correlation analysis to obtain structural stress response data including the local deformation data of the material and its response data under different frequency excitations.

[0007] Optionally, determining the configuration parameters of the micro charge coupling detection channel according to the structural stress response data to generate detection configuration data including charge detection sensitivity, signal filtering parameters and multi-channel switching logic includes: According to the local deformation data of the material in the structural stress response data, the piezoelectric effect sensitive area and the electrostatic friction sensitive area of ​​each layer of the cable material are determined respectively to obtain charge characteristic distribution data; Performing frequency domain decomposition processing on the charge characteristic distribution data to obtain piezoelectric effect spectrum data and electrostatic friction spectrum data; According to the piezoelectric effect spectrum data and the electrostatic friction spectrum data, a detection sensitivity threshold of a detection channel is set to obtain charge detection sensitivity data and signal filtering parameter data; Setting a switching timing of a detection channel according to the charge detection sensitivity data, the signal filtering parameter data and the response data in the structural stress response data to obtain multi-channel switching logic data; The charge detection sensitivity data, the signal filtering parameter data and the multi-channel switching logic data are integrated and processed to generate detection configuration data including charge detection sensitivity, signal filtering parameters and multi-channel switching logic.

[0008] Optionally, the step of collecting a transient charge signal during the transmission of a high-frequency signal of a cable according to the detection configuration data, and performing time correlation processing on the transient charge signal and a differential transmission waveform to obtain waveform sequence data with an interference event marker includes: According to the charge detection sensitivity data and signal filtering parameters in the detection configuration data, respectively collecting the charge response data and differential transmission data of the cable at different transmission rates; Performing time domain segmentation processing on the charge response data, extracting transient charge signal features according to the multi-channel switching logic in the detection configuration data, and obtaining transient charge signal sequence data; Extracting waveform features from the differential transmission data, identifying amplitude mutation points and phase mutation points during signal transmission, and obtaining differential transmission waveform feature data; A time correspondence is established according to the transient charge signal sequence data and the differential transmission waveform characteristic data, and the timing matching points of the charge disturbance and the signal anomaly are marked to obtain waveform sequence data with interference event marks.

[0009] Optionally, establishing a mapping relationship between multi-axis mechanical excitation and electrical interference according to the structural stress response data and the waveform sequence data, and generating classification data including interference source types and corresponding mechanical conditions, includes: According to the local deformation data of the material in the structural stress response data, the deformation amount of each layer of the cable material under the action of the composite stress is calculated to obtain multi-axis stress coupling data; Classify and count the electrical interference according to the interference event markers in the waveform sequence data to obtain piezoelectric effect interference feature data and electrostatic friction interference feature data; Based on the correspondence between the multi-axis stress coupling data and the piezoelectric effect interference characteristic data, the mechanical excitation conditions of the piezoelectric effect are extracted to obtain the piezoelectric effect excitation mapping data; Based on the correspondence between the multi-axis stress coupling data and the electrostatic friction interference characteristic data, the mechanical excitation conditions of electrostatic friction are extracted to obtain electrostatic friction excitation mapping data; According to the piezoelectric effect excitation mapping data and the electrostatic friction excitation mapping data, mechanical triggering modes of different types of interference are extracted to generate classification data including interference source types and corresponding mechanical conditions.

[0010] Optionally, the dynamically adjusting the cable transmission parameters when a preset mechanical condition is detected according to the classification data, and iteratively optimizing the adjustment parameters based on transmission performance feedback to generate scheduling data including the relationship between the mechanical state and the electrical coupling, including: Extracting critical trigger conditions of interference sources from the classified data to obtain mechanical condition warning threshold data; Performing real-time mechanical state monitoring according to the mechanical condition warning threshold data, and generating mechanical trigger event data when a preset mechanical condition is detected; Dynamically adjust the cable transmission parameters based on the mechanical trigger event data to obtain transmission parameter adjustment sequence data; Performing performance evaluation on the transmission state corresponding to the transmission parameter adjustment sequence data to obtain transmission performance feedback data; Optimizing and calculating the transmission parameter adjustment amount according to the transmission performance feedback data to obtain parameter optimization adjustment data; The mechanical trigger event data, the transmission performance feedback data and the parameter optimization adjustment data are associated and integrated to generate scheduling data including the mechanical state and electrical coupling relationship.

[0011] Optionally, recording the correspondence between interference characteristics and adjustment parameters of the cable under different stress and transmission conditions according to the scheduling data to generate dynamic health characteristic data of the cable includes: Extracting interference records of cables under bending stress, torsional stress and vibration stress in the scheduling data to obtain interference data under multiple stress conditions; The interference data under the multiple stress conditions are grouped according to the transmission rate to obtain interference distribution data under different transmission conditions; Corresponding to the interference distribution data and adjustment parameter records under the different transmission conditions, the suppression characteristics of the piezoelectric effect and the electrostatic friction effect are extracted to obtain interference-adjustment mapping data; Analyzing the cumulative effects of various types of interferences according to the interference-adjustment mapping data to obtain material performance degradation data; Based on the material performance decay data, aging characteristics of the materials of each layer of the cable are identified to obtain material state evolution data; The interference-regulation mapping data and the material state evolution data are correlated and analyzed to generate cable dynamic health characteristic data.

[0012] A second aspect of the present invention provides a cable testing device, the cable testing device comprising: A structural stress response module is used to obtain structural stress response data of the cable under multi-directional mechanical stress, wherein the structural stress response data includes local deformation data of the material and its response data under different frequency excitations; A detection channel configuration module, used to determine the configuration parameters of the micro-charge coupled detection channel according to the structural stress response data, and generate detection configuration data including charge detection sensitivity, signal filtering parameters and multi-channel switching logic; A signal acquisition and processing module, used to acquire a transient charge signal during the transmission of a high-frequency signal of a cable according to the detection configuration data, and to perform time correlation processing on the transient charge signal and the differential transmission waveform to obtain waveform sequence data with an interference event mark; A mapping analysis module, used to establish a mapping relationship between multi-axis mechanical excitation and electrical interference according to the structural stress response data and the waveform sequence data, and generate classification data including interference source types and their corresponding mechanical conditions; A parameter adjustment module, for dynamically adjusting the cable transmission parameters when a preset mechanical condition is detected according to the classification data, and iteratively optimizing the adjustment parameters based on transmission performance feedback to generate scheduling data including the relationship between the mechanical state and the electrical coupling; The health monitoring module is used to record the corresponding relationship between the interference characteristics and adjustment parameters of the cable under different stress and transmission conditions according to the scheduling data, and generate dynamic health characteristic data of the cable.

[0013] A third aspect of the present invention provides a cable testing device, comprising: a memory and at least one processor, wherein instructions are stored in the memory, and the memory and the at least one processor are interconnected via a line; the at least one processor calls the instructions in the memory so that the cable testing device executes the steps of the above-mentioned cable testing method.

[0014] A fourth aspect of the present invention provides a computer-readable storage medium, wherein the computer-readable storage medium stores instructions, which, when executed on a computer, enable the computer to execute the steps of the above-mentioned cable testing method.

[0015] This solution can more carefully identify and dynamically compensate for the micro-charge effect caused by new non-metallic reinforcement layers or fillers by collecting the material deformation and high-frequency transmission characteristics of the cable in a multi-directional stress environment. When the cable is subjected to external forces such as tension, torsion or vibration, these non-metallic materials will produce transient charge accumulation due to the rearrangement of their internal molecular structure. If only conventional low-frequency or static measurement methods are relied upon, it is often difficult to locate such micro-charge interference, which ultimately leads to random distortion or instability of the cable under high-speed data transmission. To this end, this solution first obtains the deformation distribution and dynamic stress response information of the cable under different mechanical excitations, and then determines the parameters of the micro-charge coupling detection channel based on these distribution data, including detection sensitivity and filtering logic, so as to ensure that the transient pulse signal generated by the non-metallic material can be detected in time during high-speed signal transmission. At the same time, the high-frequency differential waveform and the transient charge signal will be time-correlated. Once it is found that there is an obvious synchronization relationship between the charge disturbance and the waveform distortion, the potential interference source can be marked and classified. Through this meticulous procedure, any subtle discharge or charge coupling caused by material characteristics can be accurately captured without being masked by ordinary test noise or background environmental interference.

[0016] After detecting these transient interferences, this solution also distinguishes which interferences are caused by piezoelectric effect and which are caused by electrostatic friction based on the corresponding relationship between mechanical excitation and electrical interference. Since the two interference mechanisms are different in signal performance and triggering conditions, it is necessary to locate the interference source and adjust the transmission parameters separately. For example, if the material is prone to piezoelectric induced transient spikes in the high frequency band, the gain and terminal matching parameters of the adjacent line pairs or differential transmission channels can be corrected according to the pre-established dynamic stress threshold when the corresponding mechanical trigger condition is detected, so that the distortion from the material layer is suppressed or corrected before entering the main signal path. Similarly, if there is significant electrostatic friction interference during mechanical vibration, the system will automatically increase the filtering protection of the key frequency band, or start the multi-channel switching strategy when the mechanical stress exceeds a certain value, and temporarily switch the susceptible signal to a safer channel. In this way, random charge discharge is no longer an untraceable interference noise, but can be captured, judged and compensated quickly in real time. Ultimately, these mechanical data, interference types, and dynamic scheduling related information will be written into a special record file to evaluate the performance evolution of the cable as it is used for a long time or the environment changes, providing a complete reference for long-term operation and maintenance and failure analysis. It is precisely because of the above multi-dimensional information collection and real-time scheduling that this solution can effectively solve the previously difficult to handle micro-charge accumulation and discharge problems, and successfully achieve accurate protection of high-speed signal quality, effectively meeting the needs of large bandwidth and high-reliability transmission. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on the structures shown in these drawings without paying creative work.

[0018] Figure 1 A schematic diagram of an embodiment of a cable testing method in an embodiment of the present invention; Figure 2 A schematic diagram of an embodiment of a cable testing device in an embodiment of the present invention; Figure 3 The figure is a schematic diagram of an embodiment of a cable testing device in an embodiment of the present invention.

[0019] The realization of the purpose, functional features and advantages of the present invention will be further explained in conjunction with embodiments and with reference to the accompanying drawings. DETAILED DESCRIPTION

[0020] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0021] It should be noted that if the embodiments of the present invention involve directional indications (such as up, down, left, right, front, back...), the directional indications are only used to explain the relative position relationship, movement status, etc. between the components under a certain specific posture (as shown in the accompanying drawings). If the specific posture changes, the directional indication will also change accordingly.

[0022] In addition, the descriptions of "first", "second", etc. in the present invention are only used for descriptive purposes and cannot be understood as indicating or implying their relative importance or implicitly indicating the number of the indicated technical features. Therefore, the features defined as "first" and "second" may explicitly or implicitly include at least one of the features. In addition, "and / or" in the full text includes three solutions. Taking A and / or B as an example, it includes technical solution A, technical solution B, and technical solution that satisfies both A and B. In addition, the technical solutions between the various embodiments can be combined with each other, which must be based on the ability of ordinary technicians in the field to implement. When the combination of technical solutions is contradictory or cannot be implemented, it should be considered that such combination of technical solutions does not exist and is not within the scope of protection required by the present invention.

[0023] An embodiment of the present application provides a cable testing method. Figure 1 A flowchart of a cable testing method provided in one embodiment of the present application.

[0024] refer to Figure 1 , obtaining structural stress response data of the cable under multi-directional mechanical stress, wherein the structural stress response data includes local deformation data of the material and its response data under different frequency excitations; In one embodiment of the present application, the structural stress response data of the cable under the action of multi-directional mechanical stress is obtained, and the structural stress response data includes local deformation data of the material and its response data under different frequency excitations, including: applying multi-directional mechanical stress including bending stress and torsional stress to the cable to obtain static stress response data of the cable; applying vibration excitation of different frequencies to the stress area in the static stress response data to obtain dynamic stress response data of the cable at each frequency; extracting stress distribution data and local deformation data of the material of each layer of the cable according to the static stress response data and the dynamic stress response data; performing time series correlation analysis on the stress distribution data and the local deformation data of the material to obtain structural stress response data including local deformation data of the material and its response data under different frequency excitations.

[0025] Specifically, in order to obtain stress response data after applying multi-directional mechanical stresses such as bending stress and torsion stress to the cable, loads of different directions and magnitudes can be applied to the cable on a set of multi-axis loading platforms, and the deformation process of the cable can be recorded in real time using stress sensors and deformation measurement devices. Static stress response data consists of the deformation amount after bending or torsion and the stress distribution of each material layer at different force application points, including the mechanical response of the modified polymer layer or nanocomposite fiber layer in the local area. In order to achieve in-depth observation of these material layers, an optical scanning device or a high-precision displacement sensor can be arranged at a specific cross section to detect information such as bending radius, torsion angle and cable radius change, and the location where the deformation occurs and the corresponding stress value are marked during the recording process. For example, if the inner layer of the modified polymer layer cracks at a high torsion stress, a continuously rising stress curve and obvious coordinate changes will appear in the stress recording table. By comparing these values ​​with the axial and circumferential loading of the cable, the potential weak points of the material layer can be more intuitively located. This detailed collection of cable deformation and stress distribution after load is applied can not only preserve the true condition of each material layer under static pressure, but also lay a reliable baseline data for subsequent dynamic analysis under vibration excitation, making troubleshooting more directional.

[0026] After obtaining the static stress response data, vibration excitations of different frequencies can be applied to the static stress area on the aforementioned multi-axis loading platform or the supporting vibration table, and the dynamic stress response of the cable at each frequency can be continuously observed. The frequency range of the vibration excitation can be set in advance according to the use environment and material properties of the cable. Some modified polymer layers are prone to repeated elastic deformation in the medium frequency band, while the nanocomposite fiber layer is more likely to produce obvious deformation accumulation in the high frequency band. The sensor will record the real-time deformation data of the cable at different vibration frequencies in the form of timestamps, thereby forming a dynamic stress response sequence. In order to associate these dynamic sequences with the static stress response, the stress increment and displacement curves of the same material layer or the same stress area at different frequencies can be concentrated and compared in the analysis software, and then the characteristic points such as deformation peak value and recovery delay can be found using the time series correlation analysis method. Time series correlation analysis refers to the one-by-one pairing of the stress and deformation amount generated by the same material layer at different excitation times. When it is found that there is a large difference between the stress peak value of the same layer of material at a certain excitation frequency and the previous static stress value, it can be determined that the mechanical properties of the material layer in this frequency range are quite different from the static state. By quantifying the difference and marking it in the analysis results, structural stress response data including local deformation data of the material and its response data under different frequency excitations can be obtained. Combined with the scenario where cables in a data center are often subjected to high-frequency vibration, if this analysis result shows that the peak value of the deformation of the modified polymer layer at certain higher frequencies is continuously larger, it means that the material of this layer faces a more obvious fatigue risk, and the subsequent high-frequency data transmission process will be more prone to force-induced micro-charge coupling or transient discharge. This time-series correlation method can accurately identify the deformation coupling characteristics between different material layers and vibration frequencies in a relatively short period of time, so that engineering and technical personnel have a clear decision-making basis when optimizing cable laying methods, adjusting data transmission parameters, or arranging maintenance measures in advance, and avoid general judgments such as "material fatigue may occur". Through this multi-dimensional stress recording and frequency analysis, it is possible to expose the material hidden dangers that were originally difficult to detect in continuous measurement data, and no longer just stay at the theoretical inference level. Most importantly, these deformation and stress data from static and dynamic scenarios will provide accurate input for the sensitivity setting of the filter channel and the time correlation of the differential waveform in the subsequent micro-charge detection strategy, thereby helping to capture and even compensate for the micro-charge disturbances caused by modified polymers or nano-composite fiber layers in real time, and directly improving the overall reliability and stability of high-speed data transmission and precision measurement.

[0027] Please continue to refer to Figure 1 , determining configuration parameters of a micro charge coupling detection channel according to the structural stress response data, and generating detection configuration data including charge detection sensitivity, signal filtering parameters, and multi-channel switching logic; In one embodiment of the present application, the configuration parameters of the micro-charge coupling detection channel are determined according to the structural stress response data to generate detection configuration data including charge detection sensitivity, signal filtering parameters and multi-channel switching logic, including: according to the local deformation data of the material in the structural stress response data, the piezoelectric effect sensitive areas and electrostatic friction sensitive areas of each layer of the cable material are determined respectively to obtain charge characteristic distribution data; the charge characteristic distribution data is subjected to frequency domain decomposition processing to obtain piezoelectric effect spectrum data and electrostatic friction spectrum data; the detection sensitivity threshold of the detection channel is set according to the piezoelectric effect spectrum data and the electrostatic friction spectrum data to obtain charge detection sensitivity data and signal filtering parameter data; the switching timing of the detection channel is set according to the charge detection sensitivity data, the signal filtering parameter data and the response data in the structural stress response data to obtain multi-channel switching logic data; the charge detection sensitivity data, the signal filtering parameter data and the multi-channel switching logic data are integrated and processed to generate detection configuration data including charge detection sensitivity, signal filtering parameters and multi-channel switching logic.

[0028] Specifically, according to the local deformation data of the material in the structural stress response data, it is first necessary to correspond the stress concentration areas of the modified polymer layer, nanocomposite fiber layer and other metal or non-metal conductor layers to the electrical characteristics based on the known stress distribution and deformation characteristics, and divide the parts that are prone to charge accumulation or discharge into piezoelectric effect sensitive areas and electrostatic friction sensitive areas. In order to clarify the response of each material layer to external force excitation, the stress curves and charge coupling signs at the same position at different bending angles, torsion amplitudes or vibration frequencies can be compared during the early stress collection and deformation monitoring process, so as to determine whether the polymer material has polar rearrangement at the microscopic molecular chain level (i.e., piezoelectric effect), or whether charge friction coupling (i.e., electrostatic friction effect) occurs at the contact interface between the fiber and the conductor. For example, in a scenario that requires high-reliability data transmission, if a nanofiber layer somewhere shows an obvious charge enhancement signal at a lower vibration frequency, and the signal increase is relatively limited in the higher frequency range, it can be judged that this fiber layer is more inclined to produce piezoelectric coupling through changes in material polarity; if in the opposite case, charge pulses often appear near the woven layer with frequent bending and friction contact, it indicates that electrostatic friction interference is more significant. Through this detailed division, the charge characteristic distribution data is refined, further providing a targeted reference for subsequent frequency domain decomposition processing. The advantage of this process is that the material layers and stress concentration locations that are most likely to induce electromechanical distortion can be identified at an early stage, thereby improving the accuracy of interference positioning and reducing repeated detection of irrelevant parts.

[0029] After the charge characteristic distribution data is extracted, the data needs to be decomposed in the frequency domain to obtain the piezoelectric effect spectrum data and electrostatic friction spectrum data respectively. To achieve this operation, digital signal processing methods such as fast Fourier transform or discrete wavelet transform can be used to map the relationship between the charge coupling amplitude and phase of each material layer and the change of the external force excitation frequency to the spectrum, and mark the characteristic peaks with polarity change or friction contact amplification in the spectrum curve. In this process, the low-frequency band of bending excitation and the medium and high-frequency bands of vibration excitation can be analyzed separately. If a sharp peak is observed in the low-frequency band spectrum and it corresponds closely to the deformation time window, it can be judged that the piezoelectric mechanism has a high sensitivity in this frequency range; if multiple peaks overlap at the fiber contact interface corresponding to the higher frequency band, it indicates that electrostatic friction is more likely to cause charge accumulation during vibration excitation. For example, in a cable layout scenario that needs to cope with repeated handling by warehouse logistics robots, if multiple peaks with increased amplitude and large phase drift are found in the braided layer within the medium frequency range, it can be determined that this braided layer is susceptible to frictional charging induced by mechanical vibration, and a higher alert threshold can be set for this frequency band to avoid random signal distortion. By decomposing the charge characteristic distribution data in the frequency domain in this way, the originally complex and mixed electrical noise information can be orderly split, and a clearer guiding significance can be obtained in the subsequent separation of piezoelectric and electrostatic interference, providing solid data support for dynamic scheduling or compensation strategies.

[0030] Subsequently, the detection sensitivity threshold of the detection channel is set according to the piezoelectric effect spectrum data and the electrostatic friction spectrum data, and the charge detection sensitivity data and the signal filtering parameter data can be obtained. The detection sensitivity threshold here refers to the amplitude range in which the charge detector can reliably identify the minimum interference, while the signal filtering parameter data is responsible for determining which filtering algorithm the signal channel should start when encountering the corresponding frequency band. Setting this threshold can be specifically graded according to the response peak of the charge coupling of different material layers. For example, the high-precision measurement mode is triggered immediately after the piezoelectric effect peak exceeds a certain value, and the transient pulse filter is activated after the electrostatic friction effect exceeds another threshold, thereby ensuring that the test resources are not wasted unnecessarily when the interference is low, and avoiding high interference from being buried in the ordinary measurement mode. Through this refined division of the sensitivity threshold, each key charge coupling interval can be accurately captured, and the most suitable detection method can be automatically matched in the test strategy, which significantly improves the detection efficiency and accuracy of transient interference in complex scenarios.

[0031] Next, according to the response information contained in the charge detection sensitivity data, signal filtering parameter data, and structural stress response data, it is necessary to set a specific switching sequence for the detection channel, and integrate the switching sequence with the detection priority and trigger conditions corresponding to the channel, and finally obtain multi-channel switching logic data. The switching sequence refers to when the system chooses to start or pause which detection channel in different time periods or mechanical excitation states. It can be combined with the mechanical loading cycle of the cable and the window for sampling high-frequency transmission signals to accurately match. Therefore, when bending, torsion or vibration is about to occur or is about to end, the system will pre-arrange the switching operation to ensure that the most appropriate detection state is always in place when interference is most likely to occur. The switching logic goes a step further on this basis. In addition to specifying the time node for switching, it also specifies how to allocate processing priorities between different channels, and whether a backup channel needs to be triggered when a channel samples an abnormal signal. For example, if a modified polymer layer at a certain place shows an obvious piezoelectric peak under high-frequency vibration, the switching logic will enable the high-sensitivity piezoelectric detection channel before the vibration starts, and switch the recording mode of the electrostatic friction-related channel to avoid missing key data; if the cable enters a large-angle bending state after the vibration ends, the switching logic will shift the focus to the channel monitoring the electrostatic friction effect at the preset time, so that the friction charge that may appear in the bending state can be captured in time. By combining the trigger conditions of the switching timing with the multi-channel coordination mechanism, multi-channel switching logic data can be formed, so that the charge acquisition system can easily cope with the diverse electrical interference caused by different mechanical excitations. In this way, each interference can be sampled and recorded by the most suitable detection method in the time period when it is most likely to occur, rather than opening all channels at the same time or taking turns to collect. The beneficial effect of this method is to save data bandwidth and reduce equipment energy consumption, while significantly improving the accuracy of capturing interference peaks, and also laying a solid data foundation for subsequent fault tracing and differential compensation strategies.

[0032] Finally, the charge detection sensitivity data, signal filtering parameter data and multi-channel switching logic data are integrated and processed to generate detection configuration data including charge detection sensitivity, signal filtering parameters and multi-channel switching logic. Once the detection configuration data is completed, it can be directly called in the test system to achieve integrated and efficient operation from mechanical stress monitoring to electrical interference acquisition without repeatedly setting each parameter. The charge detection sensitivity contained in this configuration data can cope with transient charge effects of different frequencies and amplitudes, the signal filtering parameters can reduce the interference of meaningless noise, and the multi-channel switching logic can conduct a more comprehensive observation of high-risk material areas through timing management. After the above information is comprehensively applied, if it is in a high-bandwidth scenario such as a data center, the modified polymer layer or nanocomposite fiber layer that produces significant interference under different mechanical excitations will be monitored in real time. Once an unexpected deformation peak or charge anomaly occurs, it can immediately switch to the corresponding high-sensitivity channel and enable targeted filtering algorithms, which not only ensures the overall test efficiency but also effectively reduces the probability of interference misjudgment. In general, these steps fully combine the two clues of material properties and mechanical excitation under the premise of subdividing piezoelectric and electrostatic coupling, and implement them through executable detection configuration data. This not only makes the identification and compensation of high-frequency interference more purposeful, but also can continuously accumulate dynamic monitoring data on the health status of the cable, ultimately significantly improving the stable transmission performance of the cable in critical environments and reducing the difficulty and risk of maintenance.

[0033] Please continue to refer to Figure 1 , collecting a transient charge signal during the transmission of a high-frequency signal of a cable according to the detection configuration data, performing time correlation processing on the transient charge signal and the differential transmission waveform to obtain waveform sequence data with interference event markers; In one embodiment of the present application, the transient charge signal in the high-frequency signal transmission process of the cable is collected according to the detection configuration data, and the transient charge signal is time-correlated with the differential transmission waveform to obtain waveform sequence data with interference event marks, including: according to the charge detection sensitivity data and signal filtering parameters in the detection configuration data, the charge response data and differential transmission data of the cable at different transmission rates are collected respectively; the charge response data is subjected to time domain segmentation processing, and the transient charge signal characteristics are extracted according to the multi-channel switching logic in the detection configuration data to obtain transient charge signal sequence data; the waveform feature extraction is performed on the differential transmission data to identify the amplitude mutation point and the phase mutation point in the signal transmission process to obtain the differential transmission waveform feature data; a time correspondence is established according to the transient charge signal sequence data and the differential transmission waveform feature data, and the timing matching points of the charge disturbance and the signal anomaly are marked to obtain the waveform sequence data with interference event marks.

[0034] Specifically, according to the charge detection sensitivity data and signal filtering parameters in the detection configuration data, the charge response data and differential transmission data of the cable need to be collected separately at different transmission rates. To achieve this step, the cable can be connected to a multi-rate signal generator, and then the transmission rate can be gradually increased or decreased in a pre-planned order, so that the modified polymer layer or the nanocomposite fiber layer is subjected to different degrees of electrical excitation under various bandwidth environments. The charge acquisition module will automatically filter out signals with too low amplitude or not within the filtering parameter range according to the amplitude threshold set in the charge detection sensitivity data, ensuring that subsequent analysis only focuses on charge events that truly have interference potential. By performing acquisition at multiple rates, on the one hand, it is possible to make more detailed records of sudden transient charge coupling during high-speed transmission, and on the other hand, it can reduce the amount of redundant data accumulated at low speed or irrelevant bandwidth, thereby significantly improving data analysis efficiency.

[0035] After the charge response data is collected, the entire sampling period needs to be segmented in the time domain according to the multi-channel switching logic recorded in the detection configuration data. The meaning of time domain segmentation is to split a continuous acquisition time into several time slices that match the mechanical excitation or transmission frequency switching. Each time slice corresponds to a specific external force excitation mode or signal bandwidth setting, and then in this time slice, the amplitude bulge, pulse spike or phase distortion and other features are selected through threshold detection to extract the transient charge signal characteristics and summarize them as transient charge signal sequence data. For example, in a high-bandwidth data center, in a scenario where the vibration of the cabinet fan and the transmission rate of the cable change together, if the torsion force or bending force continues to increase, the modified polymer layer may generate high-amplitude charge pulses in a specific time slice. Through the time domain segmentation method, these pulses can be quickly located in a relatively accurate time window and separated from ordinary background fluctuations. The advantage of this is that it can effectively distinguish the interference sources under different mechanical and transmission modes, improve the accuracy of interference positioning, and bring higher feasibility to subsequent timing matching and classification analysis.

[0036] When extracting waveform features from differential transmission data, it is necessary to apply amplitude and phase monitoring algorithms. In the order of increasing or decreasing transmission rates, the areas where distortion may occur are screened from the entire waveform collected, and the corresponding amplitude mutation points or phase mutation points are identified. Amplitude mutation points refer to the moment when the signal strength rises or falls sharply in a very short time, and phase mutation points represent the moment when the phase shifts significantly in adjacent sampling cycles. When the cable is discharged under the action of external forces (for example, the modified polymer layer is subjected to high-frequency vibration or large-angle bending), these discharge behaviors will cause perceptible jumps in the amplitude or phase of the differential transmission waveform. After these jump points are uniformly refined into differential transmission waveform feature data, the system can intuitively understand the trend of signal changes over time. By identifying anomalies at the amplitude level and phase level respectively, it is possible to capture the impact of high-amplitude interference on transient waveforms, and observe data errors caused by phase drift in continuous transmission. The advantage of this is that it covers the possible manifestations of various interferences to the greatest extent, thereby avoiding missed detection or misjudgment.

[0037] After obtaining the transient charge signal sequence data and differential transmission waveform characteristic data, it is necessary to unify the time base of the two first, and then compare the sampling moments one by one to determine whether obvious charge pulses and waveform mutations occur simultaneously in the same time period. When the abnormal points of the transient charge signal and the differential transmission waveform coincide on the time axis, they will be marked as the timing matching points of the interference event, and labels such as "charge interference" or "signal abnormality" will be added to the waveform sequence data. If in the test scenario of large-angle bending operation, the modified polymer layer accumulates a large charge and releases it instantly at the most violent bending moment, and the differential transmission waveform also records the amplitude mutation or phase jump at the same time, the two can be aligned and marked as "bending triggered" interference labels. The advantage of this is that a clear causal or correlation relationship can be established between the charge effect generated by the internal material of the cable and the external differential signal distortion, abandoning the previous method of relying on speculation or hypothesis to locate the interference source, and also providing accurate data support for the subsequent classification of interference types and tracing of fault causes. Once the system confirms in multiple tests that large-angle bending and high-amplitude charge disturbances are strictly synchronized, it can proactively improve the charge collection sensitivity or deploy real-time compensation strategies in advance in subsequent tests, thereby reducing or avoiding the recurrence of similar problems and greatly enhancing the cable's stable transmission capabilities in high-reliability communication scenarios.

[0038] Please continue to refer to Figure 1 , establishing a mapping relationship between multi-axis mechanical excitation and electrical interference according to the structural stress response data and the waveform sequence data, and generating classification data including interference source types and their corresponding mechanical conditions; In one embodiment of the present application, a mapping relationship between multi-axis mechanical excitation and electrical interference is established based on the structural stress response data and the waveform sequence data, and classified data including interference source types and their corresponding mechanical conditions are generated, including: calculating the deformation of each layer of cable material under the action of composite stress based on the local deformation data of the material in the structural stress response data to obtain multi-axis stress coupling data; classifying and counting the electrical interference based on the interference event markers in the waveform sequence data to obtain piezoelectric effect interference feature data and electrostatic friction interference feature data; extracting the mechanical excitation conditions of the piezoelectric effect based on the correspondence between the multi-axis stress coupling data and the piezoelectric effect interference feature data to obtain piezoelectric effect excitation mapping data; extracting the mechanical excitation conditions of electrostatic friction based on the correspondence between the multi-axis stress coupling data and the electrostatic friction interference feature data to obtain electrostatic friction excitation mapping data; extracting the mechanical triggering modes of different types of interference based on the piezoelectric effect excitation mapping data and the electrostatic friction excitation mapping data to generate classified data including interference source types and their corresponding mechanical conditions.

[0039] Specifically, according to the local deformation data of the material in the structural stress response data, it is necessary to calculate the deformation of each layer of the cable material under the action of the composite stress to obtain the multi-axis stress coupling data. This calculation process is not limited to simply accumulating the stress of uniaxial bending or uniaxial torsion, but adopts a multi-directional force analysis method to record the comprehensive deformation of the modified polymer layer or the nanofiber layer in multiple dimensions such as bending angle, torsion angle and vibration frequency. To achieve this process, the stress concentration area of ​​each material layer in different directions can be extracted from the bending stress, torsion stress and deformation curve under vibration excitation collected in the early stage, and the local displacement and the overall deformation are unified to the same coordinate system through mechanical field decomposition or finite element calculation methods, so as to obtain the equivalent deformation. For example, if a section of the cable is in a 45-degree bend plus 20-degree torsion situation, and the vibration frequency is 100Hz, the calculation process will first identify the stress peak position of each material layer under this angle and vibration environment, and then integrate these peaks into the same mechanical field analysis model to finally output the equivalent deformation of the modified polymer layer and the nanofiber layer. This step can take into account multiple mechanical states involved in actual usage scenarios without missing any mechanical coupling in any direction, thus avoiding deviations in the subsequent tracing of interference sources.

[0040] After obtaining the multi-axis stress coupling data, it is necessary to classify and count the electrical interference according to the interference event markers in the waveform sequence data to obtain the piezoelectric effect interference characteristic data and electrostatic friction interference characteristic data. The waveform sequence data carries interference event markers, which can accurately indicate the time and amplitude of each charge anomaly or signal distortion. By comparing the event markers with the mechanical state of each layer of the cable material one by one, it is possible to identify which interferences belong to the piezoelectric phenomenon caused by the change of material polarity and which are caused by the charge accumulation or discharge caused by the friction on the surface of the material. If a certain test record shows that under medium and high frequency vibration, the modified polymer layer has continuous amplitude mutations and the phase in the differential transmission waveform is also offset, then these interference events can be marked as piezoelectric effect interference; if the friction area between the nanofiber layer and the braided layer repeatedly triggers charge pulses under large angle bending or high tensile environment, these interference events can be classified as electrostatic friction effect. Through such classification and statistics, a solid foundation can be laid for the subsequent extraction of mechanical excitation conditions, and the system can quickly determine which type of interference may occur when facing the same mechanical environment, so as to carry out differentiated compensation or protection.

[0041] Subsequently, it is necessary to extract the mechanical excitation conditions of the piezoelectric effect based on the correspondence between the multi-axis stress coupling data and the piezoelectric effect interference characteristic data, and obtain the piezoelectric effect excitation mapping data. This step is to find out under what stress combination (bending angle, torsion amplitude, vibration frequency) the modified polymer layer is most likely to produce polarity changes and output high-amplitude charges by matching the interference events previously confirmed as "piezoelectric effect" with the equivalent deformation in detail. If in a long-distance transmission environment, a cable is repeatedly bent and superimposed with medium-frequency vibrations, and high-voltage pulses are observed in the same time period many times, it can be determined that the material is a strong piezoelectric effect area in the corresponding angle and frequency range, and then these characteristic conditions are integrated into mapping data. The beneficial effect of this process is that it can clearly explain in a quantitative way "at what torsion angle or vibration excitation range the most significant piezoelectric charge output will appear", and provide a clear threshold basis for subsequent real-time monitoring or automatic compensation.

[0042] Similarly, it is necessary to extract the mechanical excitation conditions of electrostatic friction based on the correspondence between the multi-axis stress coupling data and the electrostatic friction interference characteristic data to obtain the electrostatic friction excitation mapping data. At this time, we will focus on which mechanical states are most frequent in the relative displacement or friction contact between the material layers of the cable, thereby inducing charge accumulation and instantaneous discharge. If the record shows that in a composite environment of high tensile force and periodic micro-vibration, a certain braided layer and nanofiber layer continue to generate pulse outputs, and phase jumps in the waveform repeatedly appear in this stress range, it means that the friction interface in this area is most prone to charge accumulation. By combing these conditions into electrostatic friction excitation mapping data, the subsequent test system can immediately open specific channels or enhance the filtering level when approaching these mechanical thresholds to reduce the risk of interference with the normal communication of the cable.

[0043] Finally, according to the piezoelectric effect excitation mapping data and electrostatic friction excitation mapping data, the mechanical triggering modes of different types of interference are comprehensively extracted to generate classification data including the types of interference sources and their corresponding mechanical conditions. This step can be regarded as a summary: the system organizes the excitation environment, material layer properties and output characteristics of each interference event into a comparison table of mechanical conditions and interference types. If in some cases, a layer of modified polymer material is more likely to show piezoelectric properties, it will be marked in the corresponding table row; if another braided layer shows electrostatic friction under tension, it will be recorded in the adjacent column. Through this targeted classification data, the triggering mechanism of various interference sources can be efficiently identified, and the corresponding monitoring and compensation strategies can be quickly launched when encountering similar mechanical environments, fundamentally improving the stability and safety of cables under high-reliability transmission. In addition, this mapping classification also provides a quantifiable reference for subsequent production processes or on-site maintenance, and can accurately predict what type of interference will occur under specific external force excitation, saving the time cost of a large number of sampling tests, reflecting the high availability and technical value of the overall solution in a complex stress environment.

[0044] Please continue to refer to Figure 1 , according to the classification data, dynamically adjust the cable transmission parameters when a preset mechanical condition is detected, and iteratively optimize the adjustment parameters based on transmission performance feedback to generate scheduling data including the relationship between the mechanical state and the electrical coupling; In one embodiment of the present application, according to the classification data, dynamic adjustment of cable transmission parameters is performed when a preset mechanical condition is detected, and the adjustment parameters are iteratively optimized based on transmission performance feedback to generate scheduling data including the relationship between mechanical state and electrical coupling, including: extracting critical trigger conditions of interference sources from the classification data to obtain mechanical condition warning threshold data; performing real-time mechanical state monitoring according to the mechanical condition warning threshold data, and generating mechanical trigger event data when a preset mechanical condition is detected; dynamically adjusting cable transmission parameters based on the mechanical trigger event data to obtain transmission parameter adjustment sequence data; performing performance evaluation on the transmission state corresponding to the transmission parameter adjustment sequence data to obtain transmission performance feedback data; optimizing and calculating the transmission parameter adjustment amount according to the transmission performance feedback data to obtain parameter optimization adjustment data; correlating and integrating the mechanical trigger event data, the transmission performance feedback data and the parameter optimization adjustment data to generate scheduling data including the relationship between mechanical state and electrical coupling.

[0045] Specifically, when extracting the critical triggering conditions of the interference source from the classified data, it is necessary to screen out the numerical range that is most likely to trigger a large charge coupling or signal distortion in a composite stress environment, such as the peak interval of the bending angle, torsion amplitude or vibration frequency, based on the previous piezoelectric and electrostatic interference classification. For modified polymer layers or nanofiber layers, if these indicators overlap with higher-intensity interference event markers multiple times, they are regarded as critical triggering conditions for the material layer. After registering it as mechanical condition warning threshold data, the system will immediately issue a warning or enter the corresponding protection mode once it detects that the external force is about to exceed or has exceeded the threshold in subsequent actual tests or usage scenarios. The significance of this process is that the existing interference history can be "quantified" into specific and monitorable mechanical indicators, which facilitates the system to intervene in or adjust the rate of similar stress environments in advance in the next stage, thereby reducing the potential failure rate.

[0046] When performing real-time mechanical state monitoring based on the mechanical condition warning threshold data, the system will continuously track the angle, stretch or vibration amplitude of the cable under different mechanical states. If the actual stress value is found to be close to or exceeds the threshold, the system will generate mechanical trigger event data, indicating that the mechanical excitation has reached or exceeded the critical level. Taking the scenario where the cables in the data center are subjected to torsional stress as an example, if a certain torsional angle happens to be marked as a condition that is easy to trigger piezoelectric spikes by the previous classification data, once the detection result indicates that the torsional amplitude is close to this angle, it will be identified as mechanical trigger event data and passed to the scheduling module. In this way, the corresponding countermeasures can be initiated before the interference actually occurs or even amplified, so as to achieve more timely and accurate defense.

[0047] The process of dynamically adjusting the cable transmission parameters based on the mechanical trigger event data mainly relies on the system's internal ability to automatically adjust the differential amplifier gain, signal filtering level, and high-speed transmission rate. If the test results show that the torsion angle is superimposed on the intermediate frequency vibration, and it is confirmed as a piezoelectric effect-induced source in the previous interference classification, the system will refer to the detailed records of the classification data to decide whether the transmission rate should be reduced or the filtering sensitivity should be increased to avoid the bit error rate surge caused by the instantaneous discharge of the modified polymer layer. If the event data corresponds to the electrostatic friction effect, the system will give priority to adding a stronger shielding potential to the cable section or switching to a differential mode that resists friction interference. After executing these preset operations, the system will form a transmission parameter adjustment sequence data to record each adjustment node and operation time.

[0048] After obtaining the transmission parameter adjustment sequence data, it is necessary to immediately perform a performance evaluation on the transmission state corresponding to the sequence to obtain transmission performance feedback data. Performance evaluation generally involves rapid measurement of signal bit error rate, phase stability, and bandwidth utilization, and comparison with the interference-free state or expected threshold value. If the scheduling strategy significantly reduces the interference peak or phase jump, the operation will be marked as a valid solution; if the interference is still high, it will be marked as there is still room for optimization. Such real-time feedback is of great value: on the one hand, it allows the system to immediately distinguish which parameter combination is more effective in dealing with a certain type of mechanical event; on the other hand, it can prevent repeated attempts at invalid strategies and shorten the troubleshooting and testing cycle.

[0049] When optimizing and calculating the transmission parameter adjustment amount according to the transmission performance feedback data, it is necessary to integrate all previous successful or unsatisfactory scheduling records into an optimization model, comprehensively evaluate the material layer characteristics, the current interference source type and the mechanical excitation intensity, and automatically iterate the new adjustment direction or parameter value. If multiple attempts show that simply reducing the transmission rate is not enough to eliminate high-amplitude discharges, the filter level will be automatically increased or the differential gain matching will be improved in the next scheduling, thereby generating more suitable parameter optimization adjustment data. During this process, the system will continue to remember which combinations are more suitable for dealing with piezoelectric peaks or electrostatic shocks to improve overall adaptability.

[0050] Finally, it is necessary to correlate and integrate the mechanical trigger event data, transmission performance feedback data, and parameter optimization adjustment data to generate scheduling data that includes the relationship between mechanical state and electrical coupling. The scheduling data can be regarded as a summary file, which includes which interference events each mechanical state triggered, what transmission parameter adjustment strategy was used, and what the results were in one or more tests. If a large-angle bend in a certain record triggers a mid-frequency discharge and is successfully suppressed by the scheduling strategy, a clear mapping will be formed in the scheduling data: the torsion amplitude and the frequency band vibration have a significant impact on the material layer, and the following transmission parameter combination can effectively reduce the bit error rate or phase jump. This mapping can not only be reused in subsequent tests, but also provide engineers with a quick judgment basis during on-site operation and maintenance, making cable operation and maintenance more automated and predictive, and ultimately achieving rapid identification and precise compensation of electrical interference in high-stress environments.

[0051] Please continue to refer to Figure 1 , according to the scheduling data, the corresponding relationship between the interference characteristics and the adjustment parameters of the cable under different stress and transmission conditions is recorded to generate dynamic health characteristic data of the cable.

[0052] In one embodiment of the present application, according to the scheduling data, the correspondence between the interference characteristics and the adjustment parameters of the cable under different stresses and transmission conditions is recorded to generate dynamic health characteristic data of the cable, including: extracting the interference records of the cable under bending stress, torsional stress and vibration stress in the scheduling data to obtain interference data under multiple stress conditions; grouping the interference data under multiple stress conditions according to the transmission rate to obtain interference distribution data under different transmission conditions; corresponding to the interference distribution data and adjustment parameter records under the different transmission conditions, extracting the inhibition characteristics of the piezoelectric effect and the electrostatic friction effect to obtain interference-adjustment mapping data; analyzing the cumulative effects of various types of interference according to the interference-adjustment mapping data to obtain material performance degradation data; identifying the aging characteristics of each layer of material of the cable based on the material performance degradation data to obtain material state evolution data; and performing correlation analysis on the interference-adjustment mapping data and the material state evolution data to generate dynamic health characteristic data of the cable.

[0053] Specifically, when extracting interference records of cables under bending stress, torsional stress, and vibration stress from scheduling data, it is necessary to centrally retrieve all interference items with relevant mechanical conditions and put them into a unified interference data set under multiple stress conditions. The early scheduling process usually leaves a mechanical state mark and the time of interference occurrence for each external force excitation (such as bending at a certain angle, torsion of a certain amplitude, or vibration of different frequencies), so that this extraction link can efficiently screen out waveform anomalies or charge pulses for the corresponding scene. If a section of cable records piezoelectric charge peaks multiple times during the superposition of large-angle bending and low-frequency vibration, this information will be marked in the data set. This step clearly distinguishes interference events that occur under different types of external forces, which is convenient for subsequent comparison, grouping, and induction.

[0054] Subsequently, the interference data under multiple stress conditions need to be grouped according to the transmission rate, and thus the interference distribution data under different transmission conditions are formed. This process will group the interference events under high-speed transmission into one group, and the interference events under medium-speed or low-speed transmission into other groups, and each group will retain mechanical triggering information such as bending, torsion or vibration. If the number of discharges caused by the coupling of bending stress and electrostatic friction accounts for a large proportion in high-speed mode, while the piezoelectric effect is more common in low-speed mode, each speed group will show this characteristic distribution separately. The interference distribution data formed in this way can intuitively reflect the composite effect between external force and bandwidth, and provide a comparative basis for the subsequent search for suitable scheduling or compensation strategies.

[0055] For the interference distribution data under different transmission conditions, it is necessary to correspond to the adjustment parameter records to extract the suppression characteristics of the piezoelectric effect and the electrostatic friction effect to obtain the interference-adjustment mapping data. The adjustment parameter records usually contain the differential amplifier gain adjustment, filter level change or other real-time compensation measures taken by the system when a certain mechanical inducement is detected, and the changes in the interference amplitude or phase jump before and after each adjustment will be noted. If the high-amplitude piezoelectric pulse is suppressed by gain management in a large-angle torsion scenario, the mapping data will display related information such as "torsion angle X degrees-gain management-interference amplitude reduction by N%"; if in another environment, the wear of the woven material and the nanofiber layer can prevent the emergence of electrostatic spikes by increasing the filter sensitivity, then the mapping data will record "a certain vibration frequency at high speed-filter enhancement-electrostatic peak reduction" together. The role of this link is to closely combine the interference type with the corresponding adjustment means, so that the system or technicians can more easily track "which measures are suitable for dealing with which mechanical and interference combinations".

[0056] After the interference-adjustment mapping data is formed, the cumulative effects of various types of interference need to be deeply analyzed to obtain material performance degradation data. This analysis focuses on the state changes experienced by the modified polymer layer or nanofiber layer inside the cable after multiple forces and high-frequency use. If the same section of cable still has cumulative charge discharge even if the transmission rate or filtering scheme is adjusted during multiple bends, it means that the material is experiencing local fatigue or microcrack expansion. The system will determine that the material has evolved in the direction of performance degradation by quantifying the growth curve of the interference amplitude over time or the number of tests, and write this judgment into the material performance degradation data. This step can clearly show the mechanical impact resistance level and remaining service capacity of different material layers, providing a reference for determining whether the cable needs to be replaced or the use environment needs to be modified.

[0057] After obtaining the material performance degradation data, it is necessary to identify the aging characteristics of each layer of the cable material based on this information to form material state evolution data. If a layer of modified polymer deteriorates rapidly in a medium-frequency vibration environment, while another layer of nanofiber structure is relatively stable in the same environment, the material state evolution data will give a clear comparison of aging speeds, mechanical strength attenuation curves, or a trend of continued increase in charge coupling for different material layers. This type of differentiated record can directly indicate which part of the material is the most fragile or the most severely aged, laying a data foundation for subsequent more refined maintenance and upgrade decisions, and avoiding the waste of resources caused by treating the entire cable in the same way.

[0058] Finally, the interference-regulation mapping data and the material state evolution data need to be correlated and analyzed to generate the cable dynamic health characteristic data. At this point, the results of all the previous steps will be integrated into a long-term observation framework, including both the interference type and suppression method under a specific mechanical state, as well as the degree and progression rate of aging of the material layer after multiple uses. If the system recognizes that after multiple high-bandwidth uses, the aging curve of the modified polymer layer begins to show a clear upward trend, and the electrostatic spikes are becoming more frequent, it can mark the "high-risk state" in the dynamic health characteristic data and automatically trigger more stringent monitoring or more thorough compensation strategies in subsequent applications. Through the output of this final data, the durability and health level of the cable in various extreme environments can be managed in a traceable, quantifiable and predictable manner, providing all-round prevention and protection for high-reliability communications and precision measurement services.

[0059] The above describes the cable testing method in the embodiment of the present invention. The following describes the cable testing device in the embodiment of the present invention. Figure 2 , an embodiment of a cable testing device in an embodiment of the present invention includes: The structural stress response module 201 is used to obtain the structural stress response data of the cable under the action of multi-directional mechanical stress, wherein the structural stress response data includes the local deformation data of the material and its response data under different frequency excitations; A detection channel configuration module 202, for determining configuration parameters of a micro charge coupling detection channel according to the structural stress response data, and generating detection configuration data including charge detection sensitivity, signal filtering parameters and multi-channel switching logic; The signal acquisition and processing module 203 is used to acquire the transient charge signal during the high-frequency signal transmission of the cable according to the detection configuration data, and perform time correlation processing on the transient charge signal and the differential transmission waveform to obtain waveform sequence data with interference event marks; A mapping analysis module 204 is used to establish a mapping relationship between multi-axis mechanical excitation and electrical interference according to the structural stress response data and the waveform sequence data, and generate classification data including interference source types and their corresponding mechanical conditions; A parameter adjustment module 205 is used to perform dynamic adjustment of cable transmission parameters when a preset mechanical condition is detected according to the classification data, and iteratively optimize the adjustment parameters based on transmission performance feedback to generate scheduling data including a mechanical state and an electrical coupling relationship; The health monitoring module 206 is used to record the corresponding relationship between the interference characteristics and the adjustment parameters of the cable under different stress and transmission conditions according to the scheduling data, and generate dynamic health characteristic data of the cable.

[0060] above Figure 2 The cable testing device in the embodiment of the present invention is described in detail from the perspective of modular functional entities. The cable testing device in the embodiment of the present invention is described in detail from the perspective of hardware processing.

[0061] Figure 33 is a schematic diagram of the structure of a cable test device provided by an embodiment of the present invention. The cable test device 300 may have relatively large differences due to different configurations or performances, and may include one or more processors (central processing units, CPU) 310 (for example, one or more processors) and a memory 320, and one or more storage media 330 (for example, one or more mass storage device terminals) storing application programs 333 or data 332. Among them, the memory 320 and the storage medium 330 may be temporary storage or permanent storage. The program stored in the storage medium 330 may include one or more modules (not shown in the figure), and each module may include a series of instruction operations in the cable test device 300. Furthermore, the processor 310 may be configured to communicate with the storage medium 330, and execute a series of instruction operations in the storage medium 330 on the cable test device 300 to implement the steps of the above-mentioned cable test method.

[0062] The cable test device 300 may also include one or more power supplies 340, one or more wired or wireless network interfaces 350, one or more input and output interfaces 360, and / or one or more operating systems 331, such as Windows Serve, Mac OS X, Unix, Linux, FreeBSD, etc. It will be appreciated by those skilled in the art that Figure 3 The structure of the cable test device shown does not constitute a limitation on the cable test device provided by the present invention, and may include more or less components than shown in the figure, or a combination of certain components, or a different arrangement of components.

[0063] The present invention also provides a computer-readable storage medium, which may be a non-volatile computer-readable storage medium or a volatile computer-readable storage medium. Instructions are stored in the computer-readable storage medium. When the instructions are executed on a computer, the computer executes the steps of the cable testing method.

[0064] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working process of the above-described system, device, or unit can refer to the corresponding process in the aforementioned method embodiment and will not be repeated here.

[0065] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention is essentially or the part that contributes to the prior art or the whole or part of the technical solution can be embodied in the form of a software product. The computer software product is stored in a storage medium, including several instructions to enable a computer device (which can be a personal computer, server, or network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM), random access memory (RAM), disk or optical disk and other media that can store program code.

[0066] The above description is only a preferred embodiment of the present invention, and does not limit the patent scope of the present invention. All equivalent structural changes made by using the contents of the present invention specification and drawings under the inventive concept of the present invention, or directly / indirectly applied in other related technical fields are included in the patent protection scope of the present invention.

Claims

1. A cable testing method, characterized in that: include: Acquire structural stress response data of the cable under multi-directional mechanical stress, wherein the structural stress response data includes local deformation data of the material and its response data under different frequency excitations; Determining configuration parameters of a micro-charge coupled detection channel according to the structural stress response data, and generating detection configuration data including charge detection sensitivity, signal filtering parameters, and multi-channel switching logic; Acquiring a transient charge signal during the transmission of a high-frequency signal of a cable according to the detection configuration data, performing time correlation processing on the transient charge signal and a differential transmission waveform to obtain waveform sequence data with an interference event mark; According to the structural stress response data and the waveform sequence data, a mapping relationship between multi-axis mechanical excitation and electrical interference is established to generate classification data including interference source types and corresponding mechanical conditions; According to the classification data, when a preset mechanical condition is detected, the cable transmission parameters are dynamically adjusted, and the adjustment parameters are iteratively optimized based on the transmission performance feedback to generate scheduling data including the mechanical state and the electrical coupling relationship; According to the scheduling data, the corresponding relationship between the interference characteristics and the adjustment parameters of the cable under different stress and transmission conditions is recorded to generate dynamic health characteristic data of the cable.

2. The cable testing method according to claim 1, characterized in that: The obtaining of structural stress response data of the cable under multi-directional mechanical stress, wherein the structural stress response data includes local deformation data of the material and its response data under different frequency excitations, includes: Apply multi-directional mechanical stresses including bending stress and torsional stress to the cable to obtain static stress response data of the cable; Applying vibration excitations of different frequencies to the stress region in the static stress response data to obtain dynamic stress response data of the cable at each frequency; Extracting stress distribution data and local deformation data of each layer of cable material according to the static stress response data and the dynamic stress response data; The stress distribution data and the local deformation data of the material are subjected to time series correlation analysis to obtain structural stress response data including the local deformation data of the material and its response data under different frequency excitations.

3. The cable testing method according to claim 1, characterized in that: The step of determining the configuration parameters of the micro-charge coupled detection channel according to the structural stress response data and generating detection configuration data including charge detection sensitivity, signal filtering parameters and multi-channel switching logic includes: According to the local deformation data of the material in the structural stress response data, the piezoelectric effect sensitive area and the electrostatic friction sensitive area of ​​each layer of the cable material are determined respectively to obtain charge characteristic distribution data; Performing frequency domain decomposition processing on the charge characteristic distribution data to obtain piezoelectric effect spectrum data and electrostatic friction spectrum data; According to the piezoelectric effect spectrum data and the electrostatic friction spectrum data, a detection sensitivity threshold of a detection channel is set to obtain charge detection sensitivity data and signal filtering parameter data; Setting a switching timing of a detection channel according to the charge detection sensitivity data, the signal filtering parameter data and the response data in the structural stress response data to obtain multi-channel switching logic data; The charge detection sensitivity data, the signal filtering parameter data and the multi-channel switching logic data are integrated and processed to generate detection configuration data including charge detection sensitivity, signal filtering parameters and multi-channel switching logic.

4. The cable testing method according to claim 1, characterized in that: The method of collecting a transient charge signal in the process of high-frequency signal transmission of the cable according to the detection configuration data, and performing time correlation processing on the transient charge signal and the differential transmission waveform to obtain waveform sequence data with interference event markers includes: According to the charge detection sensitivity data and signal filtering parameters in the detection configuration data, respectively collecting the charge response data and differential transmission data of the cable at different transmission rates; Performing time domain segmentation processing on the charge response data, extracting transient charge signal features according to the multi-channel switching logic in the detection configuration data, and obtaining transient charge signal sequence data; Extracting waveform features from the differential transmission data, identifying amplitude mutation points and phase mutation points during signal transmission, and obtaining differential transmission waveform feature data; A time correspondence is established according to the transient charge signal sequence data and the differential transmission waveform characteristic data, and the timing matching points of the charge disturbance and the signal anomaly are marked to obtain waveform sequence data with interference event marks.

5. The cable testing method according to claim 1, characterized in that: The mapping relationship between multi-axis mechanical excitation and electrical interference is established according to the structural stress response data and the waveform sequence data, and classification data including interference source types and corresponding mechanical conditions is generated, including: According to the local deformation data of the material in the structural stress response data, the deformation amount of each layer of the cable material under the action of the composite stress is calculated to obtain multi-axis stress coupling data; Classify and count the electrical interference according to the interference event markers in the waveform sequence data to obtain piezoelectric effect interference feature data and electrostatic friction interference feature data; Based on the correspondence between the multi-axis stress coupling data and the piezoelectric effect interference characteristic data, the mechanical excitation conditions of the piezoelectric effect are extracted to obtain the piezoelectric effect excitation mapping data; Based on the correspondence between the multi-axis stress coupling data and the electrostatic friction interference characteristic data, the mechanical excitation conditions of electrostatic friction are extracted to obtain electrostatic friction excitation mapping data; According to the piezoelectric effect excitation mapping data and the electrostatic friction excitation mapping data, mechanical triggering modes of different types of interference are extracted to generate classification data including interference source types and corresponding mechanical conditions.

6. The cable testing method according to claim 1, characterized in that: According to the classification data, when a preset mechanical condition is detected, the cable transmission parameters are dynamically adjusted, and the adjustment parameters are iteratively optimized based on the transmission performance feedback to generate scheduling data including the relationship between the mechanical state and the electrical coupling, including: Extracting critical trigger conditions of interference sources from the classified data to obtain mechanical condition warning threshold data; Performing real-time mechanical state monitoring according to the mechanical condition warning threshold data, and generating mechanical trigger event data when a preset mechanical condition is detected; Dynamically adjust the cable transmission parameters based on the mechanical trigger event data to obtain transmission parameter adjustment sequence data; Performing performance evaluation on the transmission state corresponding to the transmission parameter adjustment sequence data to obtain transmission performance feedback data; Optimizing and calculating the transmission parameter adjustment amount according to the transmission performance feedback data to obtain parameter optimization adjustment data; The mechanical trigger event data, the transmission performance feedback data and the parameter optimization adjustment data are associated and integrated to generate scheduling data including the mechanical state and electrical coupling relationship.

7. The cable testing method according to claim 1, characterized in that: The method of recording the corresponding relationship between the interference characteristics and the adjustment parameters of the cable under different stress and transmission conditions according to the scheduling data to generate the dynamic health characteristic data of the cable includes: Extracting interference records of cables under bending stress, torsional stress and vibration stress in the scheduling data to obtain interference data under multiple stress conditions; The interference data under the multiple stress conditions are grouped according to the transmission rate to obtain interference distribution data under different transmission conditions; Corresponding to the interference distribution data and adjustment parameter records under the different transmission conditions, the suppression characteristics of the piezoelectric effect and the electrostatic friction effect are extracted to obtain interference-adjustment mapping data; Analyzing the cumulative effects of various types of interferences according to the interference-adjustment mapping data to obtain material performance degradation data; Based on the material performance decay data, aging characteristics of the materials of each layer of the cable are identified to obtain material state evolution data; The interference-regulation mapping data and the material state evolution data are correlated and analyzed to generate cable dynamic health characteristic data.

8. A cable testing device, characterized in that: The cable testing device adopts the cable testing method according to any one of claims 1 to 7, and the cable testing device comprises: A structural stress response module is used to obtain structural stress response data of the cable under multi-directional mechanical stress, wherein the structural stress response data includes local deformation data of the material and its response data under different frequency excitations; A detection channel configuration module, used to determine the configuration parameters of the micro-charge coupled detection channel according to the structural stress response data, and generate detection configuration data including charge detection sensitivity, signal filtering parameters and multi-channel switching logic; A signal acquisition and processing module, used to acquire a transient charge signal during the transmission of a high-frequency signal of a cable according to the detection configuration data, and to perform time correlation processing on the transient charge signal and the differential transmission waveform to obtain waveform sequence data with an interference event mark; A mapping analysis module, used to establish a mapping relationship between multi-axis mechanical excitation and electrical interference according to the structural stress response data and the waveform sequence data, and generate classification data including interference source types and their corresponding mechanical conditions; A parameter adjustment module, for dynamically adjusting the cable transmission parameters when a preset mechanical condition is detected according to the classification data, and iteratively optimizing the adjustment parameters based on transmission performance feedback to generate scheduling data including the relationship between the mechanical state and the electrical coupling; The health monitoring module is used to record the corresponding relationship between the interference characteristics and adjustment parameters of the cable under different stress and transmission conditions according to the scheduling data, and generate dynamic health characteristic data of the cable.

9. A cable testing device, characterized in that: The cable testing device comprises: a memory and at least one processor, wherein instructions are stored in the memory; The at least one processor calls the instructions in the memory to enable the cable testing device to execute the steps of the cable testing method according to any one of claims 1 to 7.

10. A computer-readable storage medium having instructions stored thereon, characterized in that: When the instructions are executed by a processor, the steps of the cable testing method according to any one of claims 1 to 7 are implemented.

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