A Method and System for Detecting the Anti-slip Performance of Cable Clamps Based on Multi-point Stress-Strain Monitoring

Abstract

The present invention provides a method and system for detecting the anti-slip performance of a cable clamp based on multi-point stress and strain monitoring, which relates to the technical field of cable net structural components. The method includes: applying graded loads to the target cable body through a hydraulic tensioning module to perform strain monitoring and obtain a dynamic strain data set; calculating the strain difference between the contact surface of the cable clamp and the main cable to obtain strain difference accumulation data, performing change identification calculation to obtain a local strain parameter set, including local strain gradient distribution parameters and local slip parameters; identifying the slip starting position and determining the anti-slip safety factor interval; performing cable clamp slip analysis, generating a slip distribution diagram for safety assessment, performing cable clamp anti-slip performance testing, and constructing a performance test report. The present invention solves the technical problem that the prior art often evaluates the anti-slip performance of the cable clamp by applying static loads to the cable clamp and recording its displacement, which cannot fully grasp the evolution process of the cable clamp's anti-slip performance, thus affecting the reliability assessment of the cable clamp.

Description

Technical Field

[0001] This invention relates to the field of cable net structure components, specifically to a method and system for detecting the anti-slip performance of cable clamps based on multi-point stress and strain monitoring. Background Technology

[0002] In modern engineering structures, especially cable-stayed mesh structures, the cable net is one of the core components supporting the superstructure, and the cable clamp is a key node in the cable net that plays a connecting and securing role, directly affecting the reliability and safety of the entire structure. The cable clamp ensures the stability and load-bearing capacity of the structure by connecting the cable body to the main cable. Existing methods for testing the performance of cable clamps typically employ static loading tests or dynamic tests, applying static loads to the cable clamps and recording their displacements to evaluate their anti-slip performance. However, these methods often only provide static or macroscopic load-displacement relationship curves, failing to reveal the minute deformations and slippage behavior at the contact surface between the cable clamp and the main cable. Therefore, existing cable clamp anti-slip performance testing technologies have limitations in terms of accuracy and real-time performance, and cannot effectively monitor the slippage behavior of cable clamps in complex environments, resulting in the failure to detect potential structural safety hazards in a timely manner. Summary of the Invention

[0003] This application provides a method and system for detecting the anti-slip performance of cable clamps based on multi-point stress and strain monitoring. It aims to solve the technical problem that existing technologies often evaluate the anti-slip performance of cable clamps by applying static loads and recording their displacements. This method can only reflect the anti-slip performance at a certain moment and cannot fully grasp the evolution process of the anti-slip performance of cable clamps, thus affecting the reliability assessment of cable clamps.

[0004] The first aspect disclosed in this application provides a method for detecting the anti-slip performance of cable clamps based on multi-point stress-strain monitoring. The method includes: applying graded loads to a target cable body using a hydraulic tensioning module to monitor strain and obtain a dynamic strain dataset; calculating the strain difference between the cable clamp and the main cable contact surface based on the dynamic strain dataset to obtain cumulative strain difference data; performing change identification calculations based on the cumulative strain difference data to obtain a local strain parameter set, which includes local strain gradient distribution parameters and local slippage parameters; identifying the slippage initiation position based on the local strain gradient distribution parameters and determining an anti-slip safety factor range based on the local slippage parameters; performing cable clamp slippage analysis according to the anti-slip safety factor range, generating a slippage distribution map for safety assessment, determining the slippage performance safety level, detecting the anti-slip performance of the cable clamp, and constructing a performance detection report.

[0005] The second aspect of this application discloses a cable clamp anti-slip performance testing system based on multi-point stress-strain monitoring. The system is used in the aforementioned cable clamp anti-slip performance testing method based on multi-point stress-strain monitoring. The system includes: a strain monitoring module for applying graded loads to the target cable body via a hydraulic tensioning module to monitor strain and obtain a dynamic strain dataset; a change identification and calculation module for calculating the strain difference between the cable clamp and the main cable contact surface based on the dynamic strain dataset, obtaining cumulative strain difference data, and performing change identification calculations based on the cumulative strain difference data to obtain a local strain parameter set, which includes local strain gradient distribution parameters and local slippage parameters; a coefficient interval determination module for identifying the slip initiation position based on the local strain gradient distribution parameters and determining an anti-slip safety factor interval based on the local slippage parameters; and a performance testing module for performing cable clamp slippage analysis according to the anti-slip safety factor interval, generating a slippage distribution map for safety assessment, determining the slippage performance safety level for cable clamp anti-slip performance testing, and constructing a performance testing report.

[0006] One or more technical solutions provided in this application have at least the following beneficial effects:

[0007] A hydraulic tensioning module is used to apply graded loads to the target cable, enabling precise control of the load application process. Strain monitoring captures the cable's strain response under different load conditions, providing a dynamic strain dataset that offers more realistic and comprehensive cable strain information. This data helps analyze the contact between the cable clamp and the main cable, as well as the strain variation patterns, thus providing a reliable data foundation for subsequent performance evaluation. Strain difference calculation reveals minute differences on the contact surface between the cable clamp and the main cable, allowing for the acquisition of cumulative strain difference data. This process identifies potential strain accumulation areas on the contact surface, providing early warning information for slippage analysis. This method effectively complements traditional strain monitoring methods, revealing subtle changes in the cable clamp during load bearing. Change identification calculations based on the cumulative strain difference data yield a local strain parameter set, enabling a more precise analysis of the microscopic slippage behavior at the cable clamp and main cable contact surface. Local strain gradient distribution parameters and local slippage parameters can reflect the strain and slippage in detail within the local area. By analyzing the slip distribution of cable clamps, the location and trend of slippage can be revealed, enhancing the ability to identify slippage behavior. Compared to traditional testing methods, this process can provide earlier predictions and more refined risk analysis. By identifying the slippage initiation location and combining it with local slippage parameters to determine the slippage safety factor range, the area where slippage may begin and its corresponding safety level can be accurately identified. This provides a scientific basis for the anti-slip design and maintenance of the structure, ensuring that the structure can effectively resist slippage risks in the actual working environment and enhancing the safety and reliability of the system. By generating a slippage distribution map through cable clamp slippage analysis, the slippage risk of each area of ​​the cable clamp can be clearly shown, facilitating a safety assessment of the structure's slippage performance. Through the safety assessment, the slippage performance safety level can be reasonably classified. Through the above series of analyses, the final performance test report provides complete data support for design, maintenance, and monitoring. The scientific and systematic nature of the report provides strong support for engineering decision-makers, enabling timely risk control and optimization at different stages.

[0008] The above description is only an overview of the technical solution of this application. In order to better understand the technical means of this application and to implement it in accordance with the contents of the specification, and to make the above and other objects, features and advantages of this application more obvious and understandable, the following are specific embodiments of this application. Attached Figure Description

[0009] Figure 1 This is a schematic flowchart of a cable clamp anti-slip performance testing method based on multi-point stress-strain monitoring, provided in an embodiment of this application.

[0010] Figure 2 This is a schematic diagram of the anti-slip performance testing system for cable clamps based on multi-point stress-strain monitoring, provided in an embodiment of this application.

[0011] Figure labeling: Strain monitoring module 10, Change identification and calculation module 20, Coefficient range determination module 30, Performance testing module 40. Detailed Implementation

[0012] This application provides a method and system for detecting the anti-slip performance of cable clamps based on multi-point stress and strain monitoring. It solves the technical problem that the existing technology often evaluates the anti-slip performance of cable clamps by applying static loads and recording their displacements. This method can only reflect the anti-slip performance at a certain moment and cannot fully grasp the evolution process of the anti-slip performance of cable clamps, thus affecting the reliability assessment of cable clamps.

[0013] After introducing the basic principles of this application, various non-limiting embodiments of this application will be described in detail below with reference to the accompanying drawings. It should be understood that the specific embodiments described herein are merely illustrative of this application and are not intended to limit this application.

[0014] Example 1, as Figure 1 As shown in the embodiments of this application, a method for detecting the anti-slip performance of cable clamps based on multi-point stress-strain monitoring is provided. The method includes:

[0015] The target cable is subjected to graded loads by a hydraulic tensioning module to monitor strain and obtain a dynamic strain dataset.

[0016] The target cable is a structural element used to bear and transmit forces, commonly found in bridges, large structures, or cableway equipment. The hydraulic tensioning module is a device used to apply precisely controlled loads to the target cable, using a hydraulic system to achieve tension. In this step, the hydraulic tensioning module applies graded loads to the target cable. Graded loads mean that the applied load increases gradually, rather than being applied all at once, to comprehensively monitor strain changes. After applying the graded loads, the strain data of the target cable is monitored. Strain data reflects the degree of deformation of the material under stress. To monitor strain, sensors, such as fiber optic sensors or strain gauge arrays, are installed on the target cable, which can sense strain changes in real time at different locations. The dynamic strain dataset is the strain data collected in real time by these sensors, reflecting the strain of the target cable under different loads. The dynamic strain dataset contains multi-dimensional time-series data.

[0017] Based on the dynamic strain dataset, the strain difference between the cable clamp and the main cable contact surface is calculated to obtain the cumulative strain difference data. Based on the cumulative strain difference data, change identification calculation is performed to obtain a local strain parameter set, which includes local strain gradient distribution parameters and local slip parameters.

[0018] The strain difference refers to the strain difference between the contact surfaces of the cable clamp and the main cable. By calculating these differences, we can analyze the interaction between the cable clamp and the main cable, whether the cable clamp slips, and other phenomena. Specifically, we decompose the dynamic strain dataset and obtain the strain value sequences on the cable clamp side and the main cable side, respectively. These sequences refer to the strain values ​​measured at different locations on the cable clamp side and the main cable side. We retrieve the data acquisition timestamps to ensure that each data point in the strain value sequence corresponds one-to-one with its timestamp. Using these timestamps, we can ensure that the comparison of strain values ​​is in chronological order, thereby calculating the difference more accurately. We traverse the strain value sequences on the cable clamp side and the main cable side in chronological order and perform the difference calculation. The purpose of the difference is to clarify the strain difference between the two sides at the same time point, thereby inferring the contact behavior between the two.

[0019] After obtaining the strain difference value at each time point, the cumulative amount is calculated to track the change of the strain difference value over time, identify whether there is an accumulation trend, and then analyze whether there are phenomena such as slippage. The cumulative amount is calculated by integrating the strain difference value along the time axis within the sliding time window. As time goes by, the cumulative amount of the difference value gradually increases. In this way, the cumulative amount of strain difference value is obtained through the change of strain difference value, providing a basis for subsequent analysis.

[0020] By performing spatial feature analysis on the cumulative strain difference data, the spatial distribution characteristics of strain can be obtained. For example, the strain differences at different locations and their changes over time can be analyzed. Using the results of spatial feature analysis, the cumulative strain difference data can be spatially decomposed into multiple calculation units. These calculation units can be divided based on the axial direction of the contact surface. By calculating the rate of change of the cumulative strain difference in each calculation unit, the local strain gradient distribution parameters and local slip parameters can be obtained. The local strain gradient distribution parameters reflect the distribution of the strain gradient (i.e., the rate of change of strain per unit length) and can reveal the potential location of slip behavior. The local slip parameters describe the degree of slip in the local area and help to determine the severity of slip.

[0021] Finally, by integrating the local strain gradient distribution parameters and the local slip parameters, a complete set of local strain parameters is generated. This set of parameters provides a basis for subsequent slip initiation location identification and anti-slip safety analysis.

[0022] The slip initiation position is identified based on the local strain gradient distribution parameters, and the anti-slip safety factor range is determined by combining the local slip amount parameters.

[0023] Based on the local strain gradient distribution parameters, multiple gradient values ​​in the strain data are scanned to identify high gradient points. These high gradient points represent significant relative motion between the cable clamp and the main cable, and may be the starting points of slippage. Through cluster analysis and maximum value localization methods, these high gradient points are divided into multiple high gradient regions, and the core points of each region are determined. These core points are the slippage initiation locations. After determining the slippage initiation locations, the degree and velocity of slippage at that location can be assessed by combining local slippage parameters. Based on the slippage initiation location and its corresponding slippage amount, a slippage resistance safety factor range is calculated. This range sets multiple safety factors according to the severity of slippage to determine the slippage resistance capacity of that region.

[0024] According to the stated anti-slip safety factor range, cable clamp slippage analysis is performed, a slippage distribution map is generated for safety assessment, the slippage performance safety level is determined, the anti-slip performance of the cable clamp is tested, and a performance test report is constructed.

[0025] Based on the anti-slip safety factor range, cable clamp slippage analysis is conducted. The purpose of this analysis is to determine whether slippage has occurred at different locations and the extent of slippage. Slippage distribution maps visualize the slippage information at different locations. For example, a spatial model of the cable clamps is constructed using a three-dimensional coordinate system, and the safety factor range is further mapped into three-dimensional space for rendering and analysis. After generating the slippage distribution map, a safety assessment is conducted through dynamic impact assessment. Based on the hazardous areas shown in the slippage distribution map, different safety level judgment criteria are set, and slippage performance is scored according to these criteria. During the assessment process, factors such as the spatial characteristics of slippage and the hazardous coverage area of ​​slippage are considered to determine the slippage performance safety level. Finally, the slippage performance safety level is correlated with the corresponding slippage distribution. Figure 1 We will compile and construct a detailed test report on the anti-slip performance of the cable clamps. This report includes the slip risk assessment, anti-slip capability, and local strain analysis results of the cable clamps, providing engineers with comprehensive test results on the anti-slip performance of the cable clamps and helping to formulate subsequent maintenance or replacement plans.

[0026] Furthermore, by applying graded loads to the target cable using a hydraulic tensioning module and monitoring the strain, a dynamic strain dataset is obtained. The methods include:

[0027] Distributed fiber optic sensors are pre-embedded inside the target cable, and multiple strain gauge arrays are deployed on the outer surface of the cable clamp. A stepped load is applied to the target cable using a hydraulic tensioning module to determine multi-level load data. Stress and strain data are acquired and monitored based on the fiber optic sensors and the multi-level load data to obtain strain distribution data for the entire cable segment. Stress and strain data are also acquired and monitored using the multiple strain gauge arrays and the multi-level load data to obtain strain gauge array data. The strain distribution data for the entire cable segment and the strain gauge array data are integrated to obtain an initial strain dataset. Temperature data from the target cable is retrieved and used to compensate and correct the initial strain dataset to obtain the dynamic strain dataset.

[0028] Fiber optic sensors are sensors based on the principle of fiber optic transmission. They can measure stress and strain along the entire length of the fiber. The purpose of pre-embedding distributed fiber optic sensors inside the target cable is to monitor the stress and strain distribution of the target cable throughout its length, especially under load, enabling real-time sensing of minute changes in various parts. Distributed fiber optic sensors can achieve continuous monitoring over long distances in the target cable, not limited to specific points. A strain gauge array is an array of multiple strain gauges installed on the outer surface of the cable clamp. A strain gauge is a sensor based on the principle of resistance change, reflecting the strain of the cable clamp under different loads by measuring minute deformations on the cable clamp surface. By deploying multiple strain gauge arrays on the outer surface of the cable clamp, strain data can be acquired in real time at multiple locations. This data can reveal the contact state between the cable clamp and the main cable, as well as potential slippage phenomena.

[0029] Hydraulic tensioning modules are devices used to apply precisely controlled loads, widely used in cable tensioning and prestressed structures. By controlling the tension force through a hydraulic system, precise and controllable loads can be applied to the cable. Hydraulic tensioning devices apply stepped loads to the target cable by gradually increasing the load. Stepped loads mean that the load is applied in specific increments, used to study the stress-strain response of the cable under different loads. During the application of stepped loads, the hydraulic tensioning device records the stress and strain data of the cable at each load level. These data form multi-level load data, which can reflect the deformation of the target cable under different loads.

[0030] Fiber optic sensors provide continuous strain data throughout the entire cable length, acquiring strain information. Multi-level load data provides information on the stress and deformation of the cable under different loads. Combining the data from fiber optic sensors with the multi-level load data yields strain distribution data for the entire cable segment, including the strain at various locations under different load conditions.

[0031] Multiple strain gauge arrays monitor strain changes on the cable clamp surface, providing detailed data on the contact mechanics between the cable clamp and the main cable. Combined with multi-level load data—specifically, the stepped loads applied by the hydraulic tensioning device—strain information is collected under different load conditions. The strain data provided by the strain gauge array at each load level reflects the impact of the load on the cable clamp's outer surface. By monitoring and recording strain data at different locations on the cable clamp's outer surface at each load stage, strain gauge array data is obtained. This data provides local strain information for assessing the cable clamp's deformation and potential slippage behavior.

[0032] The strain distribution data of the entire cable segment and the strain gauge array data are integrated to generate an initial strain dataset. This dataset can comprehensively reflect the strain of the cable and cable clamps under different load conditions and provide basic data for subsequent analysis.

[0033] Strain data is typically affected by changes in ambient temperature. Temperature variations cause materials to expand or contract, leading to deviations in strain values. Therefore, temperature compensation needs to be considered during strain data analysis. Temperature data related to the target strain body is retrieved. This data can be obtained through temperature sensors installed on the strain body or in the environment. The temperature data reflects the temperature environment of the target strain body during testing and helps identify the impact of temperature changes on strain data. The initial strain dataset is then compensated and corrected based on the acquired temperature data. Typically, the effect of temperature on materials is linear; therefore, this effect can be eliminated by establishing a correction relationship between temperature and strain, ensuring that the final data accurately reflects the material's deformation rather than errors caused by temperature variations. After temperature compensation, the resulting dynamic strain dataset is an accurate strain dataset, eliminating the influence of ambient temperature changes.

[0034] Furthermore, based on the dynamic strain dataset, the strain difference between the cable clamp and the main cable contact surface is calculated to obtain the cumulative strain difference data. The method includes:

[0035] The dynamic strain dataset is disassembled according to the contact surface between the cable clamp and the main cable to determine the strain value sequence on the cable clamp side and the strain value sequence on the main cable side. The data acquisition timestamps of the dynamic strain dataset are retrieved, and the strain value sequences on the cable clamp side and the main cable side are sequentially traversed according to the data acquisition timestamps to perform difference calculations to generate a strain difference sequence. A sliding time window is set along the cable length direction, and the strain difference sequence is accumulated along the time axis according to the sliding time window to obtain an accumulated amount time sequence. The strain difference sequence is integrated according to the accumulated amount time sequence to generate the accumulated strain difference data.

[0036] The dynamic strain dataset is decomposed according to the contact surface between the cable clamp and the main cable, and the strain values ​​of the cable clamp side and the main cable side are obtained separately to form two independent strain value sequences. Each sequence contains the strain data of the corresponding position, reflecting the strain performance of the two contact surfaces under different time and load conditions. The strain value sequence of the cable clamp side represents the strain data of the cable clamp under different loads, and the strain value sequence of the main cable side reflects the strain change of the main cable (the area where the cable body contacts the main cable).

[0037] Each strain value has a corresponding timestamp, indicating the time point when the strain value was collected. The timestamp ensures accurate alignment of strain data from different locations (clip side and main cable side), enabling effective comparative analysis. The strain values ​​corresponding to the timestamps on the clip side and main cable side are subtracted. For each timestamp, the strain values ​​on the clip side and main cable side are iterated and compared, and the differences between them are calculated. This process helps identify the relative deformation between the clip and the main cable. The generated strain difference sequence represents the relative deformation between the clip and the main cable at each time point, reflecting whether slippage or deformation has occurred at the contact surface.

[0038] A sliding time window is set along the cable length. This window is a time range used for calculation and analysis. As time progresses, the window moves along the time axis. Each time the window moves, the difference data within the window is recalculated. In this way, the changes in strain difference over time can be identified more precisely, and slippage and other local deformation behaviors can be better captured. Within each sliding time window, the strain difference sequence is accumulated. The accumulation operation, by adding the differences within the time window, reflects how the strain difference between the cable clamp and the main cable accumulates over time. The resulting accumulated time series shows the change and accumulation of strain difference over time, which helps to determine whether slippage has occurred in the cable clamp and the extent of slippage.

[0039] Integrating the strain difference sequence based on the cumulative time series yields the total accumulated strain difference over time. Integration is equivalent to mathematically summing the accumulation process, resulting in the total accumulated strain difference. This operation reveals the overall trend of relative deformation between the cable clamp and the main cable, quantifying the overall degree of slippage or localized deformation. The resulting accumulated strain difference data provides crucial quantitative evidence for subsequent slippage behavior analysis. It reflects the cumulative strain difference at the contact surface between the cable clamp and the main cable throughout the monitoring process, providing data support for further slippage identification and anti-slip analysis.

[0040] Furthermore, based on the accumulated strain difference data, a change identification calculation is performed to obtain a set of local strain parameters. The method includes:

[0041] Spatial feature analysis is performed based on the accumulated strain difference data to determine the spatial distribution characteristics. Multiple calculation units are divided according to the axial direction of the main cable contact surface. The accumulated strain difference data is calculated according to the spatial distribution characteristics within these multiple calculation units to obtain multiple spatial change rates of the accumulated values. These multiple spatial change rates correspond to the multiple calculation units. Local identification is performed based on the multiple spatial change rates of the accumulated values ​​to determine local strain gradient distribution parameters. Slip behavior is identified based on the strain gradient change pattern, and local slip parameters are calculated. The local strain gradient distribution parameters and the local slip parameters are integrated to generate the local strain parameter set.

[0042] Spatial feature analysis based on cumulative strain difference data aims to determine the spatial distribution of strain differences. This helps identify areas with significant strain variations, potentially leading to slip or other forms of damage. Spatial distribution characteristics include the magnitude of strain differences, concentrated areas of strain differences, and the directionality of strain changes. For example, large strain differences in certain areas indicate significant slip or deformation. Methods for spatial feature analysis include spatial statistics, local mean calculation, and surface fitting. These methods allow for the classification and summarization of strain differences spatially. The ultimate goal is to identify spatial hotspots or areas with potential risks based on these analytical results.

[0043] Based on the geometric shape and spatial distribution characteristics of the main cable contact surface, the main cable contact surface is divided into multiple calculation units along the axial direction. These calculation units are usually regions with the same geometric shape, such as rectangles, triangles, or squares. Each region represents a small part of the contact surface. The purpose of dividing the calculation units is to decompose the entire main cable contact surface area into small, easy-to-analyze regions so as to accurately calculate the strain changes in each region.

[0044] For each defined calculation unit, the cumulative strain difference data is matched with these calculation units based on the spatial feature analysis results. Each calculation unit corresponds to a cumulative strain difference, reflecting the strain changes within that region. For the cumulative strain difference data within each calculation unit, the spatial rate of change of the strain difference within that region is calculated based on the spatial feature analysis results. The spatial rate of change represents the rate of change of the strain difference within that unit, indicating the degree of strain change in each region. For example, if the strain difference changes drastically in a certain calculation unit, it indicates that the region may be a high-risk area for slippage. Each calculation unit has its corresponding cumulative spatial rate of change, which reflects the magnitude and trend of strain changes in that region at different time points.

[0045] Based on the magnitude and characteristics of the cumulative spatial rate of change, different regions are locally labeled. This labeling process helps identify areas with significant strain differences, which are often more likely to be slip hotspots. Threshold determination and cluster analysis are used during the labeling process to determine which regions have strain change rates exceeding predetermined thresholds, thus becoming potential slip regions. After identifying regions with significant strain changes through local labeling, local strain gradient distribution parameters are further calculated. These parameters represent the rate of strain change with space within a local region, reflecting the local trend of strain variation. These parameters are calculated based on the strain changes within the local region, using gradient operators (such as finite difference and derivative calculations) to quantitatively describe the degree of strain change.

[0046] Slip behavior is identified by analyzing strain gradient change patterns. Slip behavior typically manifests as a sharp change in the strain gradient or a significant abrupt change in strain difference in certain regions. By analyzing the change patterns of the strain gradient, it is possible to determine whether slip has begun and its extent. After identifying slip behavior, local slip parameters are calculated. These parameters describe the degree of slip within a local area and are inferred from abrupt or sharp changes in the strain gradient. For example, a rapid change in the strain gradient in a certain region indicates that slip has occurred in that region. The calculation of local slip parameters relies on the comparison of strain before and after slip, helping to quantify the severity of slip.

[0047] By integrating the local strain gradient distribution parameters and local slip parameters, a more comprehensive set of local strain parameters is obtained, which contains integrated information on the strain gradient and slip within the local region.

[0048] Furthermore, the method includes:

[0049] A three-dimensional coordinate system for the cable clamp is constructed, and a mesh mapping unit is established based on the three-dimensional coordinate system. The local strain gradient distribution parameters and the local slip parameters are mapped to the mesh mapping unit for alignment analysis to obtain a spatial coordinate mapping network. Based on the spatial coordinate mapping network, spatial correlation analysis is performed on the local strain gradient distribution parameters and the local slip parameters, and spatial overlapping areas are marked. Based on the spatial coordinate mapping network, time-series evolution analysis is performed on the local strain gradient distribution parameters and the local slip parameters, and a biaxial evolution curve is plotted. Based on the spatial overlapping areas and the biaxial evolution curve, risk coupling analysis is performed on the local strain gradient distribution parameters and the local slip parameters to generate coupled risk data. The coupled risk data is used as avoidance data to integrate the local strain gradient distribution parameters and the local slip parameters to generate the local strain parameter set.

[0050] A three-dimensional coordinate system is defined within the three-dimensional space containing the cable clamp to precisely locate the position of each computational unit. This coordinate system consists of three axes (X, Y, and Z) and can be adjusted according to the geometry and arrangement of the cable clamp. Mesh mapping units are then established based on this coordinate system. Establishing mesh mapping units involves dividing the three-dimensional space into several small regions, each representing a computational unit on the cable clamp surface or contact surface. The size and shape of each mesh unit (e.g., rectangle or triangle) are selected based on the geometric characteristics of the cable clamp to ensure that the spatial division conforms as closely as possible to the shape of the actual contact surface.

[0051] The obtained local strain gradient distribution parameters and local slip parameters are mapped onto the created mesh cells. Each mesh cell contains its corresponding strain gradient and slip parameters. The mapping process involves interpolation methods, such as linear interpolation and bilinear interpolation, to ensure that the data is accurately assigned to each mesh cell, especially when the data distribution is not perfectly aligned with the mesh structure. The purpose of alignment analysis is to ensure that the strain data is consistent with the spatial location of the mesh cells. By assigning corresponding strain gradient and slip data to each mesh cell, the spatial consistency of the strain state and slip degree of each computational cell can be ensured. The key to this alignment analysis step is to maintain accurate data mapping to ensure the accuracy of subsequent analysis. After mapping and alignment analysis, a spatial coordinate mapping network is obtained. This network associates the spatial location of each mesh cell with its corresponding strain and slip data, providing a structured data foundation for subsequent spatial analysis.

[0052] Spatial correlation analysis aims to examine the relationship between local strain gradient distribution parameters and local slip parameters, and to identify their overlapping regions in space. Spatial correlation analysis reveals which regions exhibit a strong correlation between strain gradients and slip parameters; these regions are typically high-risk areas for slippage. After spatial correlation analysis, overlapping regions are marked to identify and label areas with significant variations in strain gradients and slip parameters. These overlapping regions are often potential slip sources and may be critical locations for slippage or failure at the contact surface between the cable clamp and the main cable. During the labeling process, certain thresholds are set or algorithms are used to identify overlapping regions. These areas have a high risk of slippage and require further analysis or protective measures.

[0053] The purpose of time-series evolution analysis is to track and analyze the trends of these two parameters over time. Through this analysis, the evolution of strain gradient and slip can be identified, and it can be determined whether they change over time, thereby inferring the patterns of slip or deformation. Based on the time-series evolution data, a biaxial evolution curve is plotted. This curve displays the trends of both parameters over time in the same graph, simultaneously showing the evolution of strain gradient and slip, helping to intuitively analyze the relationship between them and assess the risk of slip or deformation at different time points.

[0054] By combining spatially overlapping regions with biaxial evolution curves, a risk coupling analysis is performed on local strain gradient distribution parameters and local slip parameters. Spatially overlapping regions represent areas where strain gradient and slip data overlap; these areas are typically high-risk zones for slip behavior. By combining the temporal trends of the biaxial evolution curves with these spatially overlapping regions, the slip risk in these areas can be assessed, and potential slip hotspots can be identified. Following the risk coupling analysis, coupled risk data is generated, expressed as a risk index or weight, reflecting the coupling effect between strain and slip. This data represents the interaction between strain gradient and slip changes, revealing the probability and severity of slip occurrence in different time periods and regions.

[0055] Using coupled risk data as mitigation data to guide subsequent risk avoidance and safety measures, coupled risk data can provide decision-makers with detailed information on which regions have high risk in strain gradient and slip parameters. Based on coupled risk data, local strain gradient distribution parameters and local slip parameters are integrated to merge data from different sources into a unified and comprehensive set of local strain parameters. This set of parameters contains detailed information on strain gradient and slip, as well as corresponding risk data, providing comprehensive basic data for subsequent slip analysis and anti-slip performance assessment.

[0056] Furthermore, the method for identifying the slip initiation position based on the local strain gradient distribution parameters includes:

[0057] Based on the local strain gradient distribution parameters, multiple gradient value data are obtained by scanning. These multiple gradient value data are then filtered to obtain multiple high gradient points. Cluster analysis is performed on these high gradient points to delineate multiple high gradient regions. Based on these high gradient regions, maximum values ​​are located to determine the core point. The coordinates of the high gradient core region are determined by labeling the core point in conjunction with its gradient magnitude. These coordinates are then used as the slip start position.

[0058] The scan is based on local strain gradient distribution parameters. The strain gradient represents the degree of strain change per unit length and can reflect stress concentration areas or potential slip initiation points on the contact surface. The goal of the scan is to identify regions with significant changes in the local strain gradient distribution parameters; these regions are often potential locations for slip. During the scan, a threshold is set, for example, 200 microstrains / meter. This is an empirical value used to filter points with large strain gradients. Only strain gradient points whose gradient values ​​exceed this threshold and exhibit a continuous spatial distribution are considered high gradient points. After filtering, several high gradient points are obtained. These high gradient points reflect regions with significant strain gradients. The presence of high gradient points indicates drastic stress changes in these regions, potentially leading to slip or other structural failure phenomena.

[0059] For the multiple high-gradient points obtained, cluster analysis is performed to divide them into multiple regions, each representing a potential slip hotspot. For example, clustering algorithms such as K-means clustering and DBSCAN are used. Based on the spatial distance and similarity of gradient changes between high-gradient points, points that are close to each other are grouped together, resulting in multiple high-gradient regions. Maximum point localization is then performed on these high-gradient regions. A maximum point is the point with the strongest strain gradient within a region, often representing the starting point of slip behavior. The process of maximum localization involves identifying the most critical points within each high-gradient region; these points are typically the starting points of slip or deformation. Based on the results of maximum localization, core points are determined. These core points represent the locations of the maximum strain gradient within each high-gradient region, and these locations are where slip is most likely to occur.

[0060] The gradient magnitude of a core point reflects the intensity of strain change at that point. Generally, a larger magnitude indicates a higher risk of slippage or structural failure in the vicinity. The annotation process assigns an identifier to each core point, associating its gradient value with its spatial location, providing easily identifiable data for subsequent analysis. By combining the gradient magnitudes of the core points, the coordinates of high-gradient core regions are determined, representing key locations of potential slippage areas and high-risk zones for slippage. These high-gradient core region coordinates are used as the slippage initiation points; these locations are often the initial sites of slippage and can also serve as key areas for slippage detection.

[0061] Furthermore, the method for determining the anti-slip safety factor range by combining the slip initiation position with the local slip amount parameter includes:

[0062] The influence search is performed centered on the slip initiation position to obtain the cable diameter influence area. Data is extracted based on the cable diameter influence area to determine multiple slip parameters. The average value of the multiple slip parameters is calculated to determine the real-time slip rate. The preload data of high-strength bolts is introduced, and the attenuation of the preload data is calculated to obtain the preload attenuation rate. Friction change analysis is performed based on the temperature data of the main cable contact surface to construct a temperature friction coefficient correction curve. Anti-slip safety analysis is performed on the preload attenuation rate according to the temperature friction coefficient correction curve to generate multiple safety correction coefficients. Multi-level safety coefficient intervals are set according to the growth trend of the multiple safety correction coefficients. The multi-level safety coefficient intervals are added to the anti-slip safety coefficient interval.

[0063] An influence search is conducted with the slip initiation point as the center. The purpose is to identify the area surrounding the slip initiation point that may be affected or influenced by slip propagation. Typically, slip phenomena spread from the initiation point to the surrounding areas. During the influence search, the cable path influence area is identified. This area is usually the main range of slip propagation and includes areas that may be affected by slip. The extent of the cable path influence area is determined based on factors such as the surrounding conditions of the slip initiation point, strain changes, and slip rate. This area encompasses the possible directions and ranges of slip propagation.

[0064] After determining the area affected by the cable path, data is extracted from all monitoring points within the area. The monitoring points are typically the locations where data is collected by sensors (such as strain gauges, fiber optic sensors, etc.). Multiple slip parameters are extracted from all monitoring points within the area. These parameters reflect the magnitude and severity of slip at different locations within the area.

[0065] The average value of multiple slip parameters is calculated. The average value calculation can eliminate local fluctuations and provide an overall overview of slip behavior. The calculation formula is the average value of slip at all monitoring points. The real-time slip rate is obtained by calculating the average value.

[0066] In slip analysis, the influence of structural connections (such as bolts) must also be considered. High-strength bolts are typically used to ensure the stability of structural connections; therefore, their preload plays a crucial role in slip behavior. Preload data reflects the initial force applied to the bolted connection, which affects the contact state between the cable clamp and the main cable, as well as slip behavior. Over time, the preload of high-strength bolts may gradually weaken due to environmental factors, load changes, or other reasons. Therefore, attenuation calculations are performed based on the preload data to estimate the attenuation trend. These calculations simulate the change in preload over time, taking into account the working conditions of the high-strength bolts, external environmental factors (such as temperature and humidity changes), and repeated load variations. Based on these calculations, the preload attenuation rate is obtained. The preload attenuation rate represents the rate at which the preload of the high-strength bolt decreases over time. This rate is used to analyze slip behavior because as the preload weakens, the stability of the high-strength bolted connection decreases, and the risk of slippage may increase.

[0067] In slip behavior analysis, temperature affects friction. As temperature changes, the coefficient of friction between the main cable contact surfaces also changes, thus influencing the occurrence and development of slip. Temperature data of the main cable contact surfaces is collected from temperature sensors or meteorological monitoring equipment, reflecting temperature changes at different times. By analyzing the relationship between temperature and the coefficient of friction, the impact of temperature changes on friction can be revealed. Generally, increased temperature leads to a decrease in the coefficient of friction, reducing friction between the contact surfaces and thus increasing the likelihood of slip. By establishing a correction relationship between temperature and the coefficient of friction, the impact of temperature changes on the coefficient of friction can be quantified, thereby predicting slip risk. The temperature-friction coefficient correction curve, derived through experiments or models, describes the quantitative relationship between temperature and the coefficient of friction, providing necessary correction data for subsequent slip analysis.

[0068] The preload decay rate is corrected using a temperature-friction coefficient correction curve. Temperature changes can lead to variations in the friction coefficient, therefore the analysis results of the preload decay rate need to be adjusted using the temperature-friction coefficient curve. Based on the corrected decay rate, an anti-slip safety analysis is performed. This analysis assesses whether the risk of slippage increases under the current preload decay condition. The aim is to accurately assess the safety status of the current structure by correcting the friction coefficient, ensuring that the slippage risk remains within a controllable range. Based on the temperature-corrected preload decay rate, multiple safety correction coefficients are generated. These coefficients represent the resistance level to slippage under different conditions and are calculated based on variations in temperature, friction, and bolt preload decay.

[0069] Based on the growth trend of multiple safety correction factors, a multi-level safety factor range is established. Different safety factor ranges represent different slip risk levels; for example, a low safety factor range indicates low slip risk, and a high safety factor range indicates high slip risk. Adding these multi-level safety factor ranges to the anti-slip safety factor range indicates the slip risk under different conditions (such as different temperatures and different friction forces) and guides how to take corresponding risk control measures at different safety levels.

[0070] Furthermore, the method for performing cable clamp slip analysis according to the aforementioned anti-slip safety factor range and generating a slip distribution map includes:

[0071] A three-dimensional spatial model of the cable clamp is constructed based on the three-dimensional coordinate system of the cable clamp. The multi-level safety factor interval is mapped to the three-dimensional spatial model of the cable clamp for visualization rendering to obtain a multi-color three-dimensional rendering area. Adjacent three-dimensional rendering areas are merged according to the same color, and continuous danger zones are extracted based on the merging results. Based on the continuous danger zones, the area coverage is calculated to obtain the danger coverage area. A double layer is drawn according to the three-dimensional spatial model of the cable clamp. The danger coverage area is synchronized to the lower layer of the double layer, and the strain gradient intensity data is synchronized to the upper layer of the double layer to generate the slip distribution map.

[0072] A three-dimensional spatial model of the cable clamp is constructed based on the established three-dimensional coordinate system. This model accurately displays the cable clamp's shape in space, including its size, shape, and contact surface position. Calculated multi-level safety factor intervals are mapped onto the cable clamp's three-dimensional spatial model. Each safety factor interval represents a different risk level, such as low, medium, and high risk. These safety factors can be represented by visual elements such as color, allowing the risk level of each area to be intuitively displayed on the model. Through rendering technology, the multi-level safety factor intervals are mapped onto the three-dimensional spatial model, generating multi-colored three-dimensional rendering areas. Color changes represent different safety factor levels. This rendering method allows different safety factor intervals to be presented in different colors within the three-dimensional spatial model, thus enabling rapid differentiation of the safety levels of each area.

[0073] Traversing the multi-color 3D rendering area, we find adjacent areas of the same color. These areas of the same color represent areas with similar slip risks. We merge adjacent areas of the same color, that is, we merge areas with the same color and similar spatial proximity into a large area. This process helps to simplify the image, remove unnecessary details, and highlight the main risk areas of slip. The result of merging is a more clearly defined continuous danger zone. This strip-shaped area represents a zone with a high and continuous slip risk.

[0074] Regional coverage calculations are performed on continuous hazardous zones, which involves calculating the coverage area of ​​the strip-shaped area. The coverage area can be obtained by calculating the total area of ​​these zones. This is used to quantify the degree of slip risk. The calculated hazardous coverage area represents the potential slip risk area within the entire region. This area value provides a quantitative indicator for assessing structural safety. A high hazardous coverage area means that there is a significant slip risk in the area, and further reinforcement or monitoring measures are required.

[0075] A dual-layer model was created based on the 3D spatial model of the cable clamp. This dual-layer concept involves displaying different data dimensions in layers. The lower layer shows the hazardous coverage area, representing potential slip zones, while the upper layer displays strain gradient intensity data, reflecting the intensity of strain changes within the area. In this way, two different data dimensions are visually presented within the same model, aiding in a comprehensive assessment of slip risk. Ultimately, the generated slip distribution map combines the hazardous coverage area and strain gradient intensity information, providing detailed slip distribution information for subsequent safety assessments. This slip distribution map visually displays potential slip zones and their corresponding strain intensities, providing crucial visualization data for engineers and decision-makers.

[0076] Furthermore, the slip distribution map is used for safety assessment to determine the slip performance safety level, and the anti-slip performance of the cable clamps is tested to construct a performance test report. The method includes:

[0077] Alignment and matching of the upper layer of the dual-layer system with the lower layer to extract spatial slip hazard features; dynamic impact assessment of the cable clamp based on the spatial slip hazard features, setting multiple safety level judgment criteria; safety assessment of the slip distribution map according to the multiple safety level judgment criteria to determine the slip performance safety level; linkage detection and control of the cable clamp's anti-slip performance based on the slip performance safety level to obtain a cable clamp safety level map; backtracking from the cable clamp safety level map to the slip distribution map for multi-source slip verification, and constructing the cable clamp's performance detection report.

[0078] The lower layer of the dual-layer diagram displays the hazardous coverage area, while the upper layer displays the strain gradient intensity data. Aligning these two layers ensures spatial alignment between the hazardous coverage area of ​​the lower layer and the strain gradient intensity data of the upper layer. Simply put, it ensures that the strain intensity information of the slip hazard area is consistent with the risk assessment data for that area. After alignment, spatial slip hazard characteristics are extracted from the aligned dual layers, including: slip hotspots (areas with particularly high strain gradient intensity within the hazardous coverage area, typically indicating a significant slip risk); and slip risk patterns (the spatial distribution characteristics of slip hazard areas, such as concentration or expansion).

[0079] Based on the characteristics of spatial slip hazard, a dynamic impact assessment is conducted on the cable clamps. The purpose of the dynamic impact assessment is to evaluate how the slip hazard area affects the stability of the entire structure, especially the stress state, deformation, and potential slip of the cable clamps. During the assessment, based on multiple factors such as the size of the slip area, changes in strain intensity, and the trends of these factors over time, the assessment infers whether slip will propagate and dynamically predicts the safety of the cable clamps. Based on the dynamic impact assessment, multiple safety level determination criteria are established. These criteria are used to classify different safety levels according to the slip hazard characteristics and the results of the dynamic impact assessment. For example, if the slip hazard area and strain intensity are particularly high and propagate rapidly, the safety level of that area is rated as high risk, requiring immediate action. The establishment of safety level determination criteria helps to conduct accurate slip risk assessments under different conditions and assists engineers in adopting reasonable response strategies.

[0080] Multiple safety level assessment criteria are applied to the previously generated slip distribution map for a safety evaluation. The slip distribution map, through the aforementioned analysis, identifies potential slip areas and the risk intensity of each area. Based on the assessment results of the safety level assessment criteria and the slip distribution map, the slip performance safety level of each area is determined. For example, a high-risk level indicates a high probability of slippage, requiring immediate action; a medium-risk level indicates that slippage risk exists but is still within a controllable range; and a low-risk level indicates a low risk of slippage, allowing for continued monitoring. This assessment accurately determines the slip performance of different areas and provides a basis for subsequent risk management and control.

[0081] Based on the slip performance safety level, a linkage detection and control system is implemented for the anti-slip performance of cable clamps. This linkage detection and control refers to taking corresponding detection and control measures according to different safety levels. For example, for high-risk areas, more frequent monitoring and emergency reinforcement are required; for medium-risk areas, regular inspections and long-term monitoring plans can be developed; and for low-risk areas, the existing detection frequency can be maintained. Through linkage detection and control, the anti-slip performance of cable clamps can be dynamically adjusted to ensure that it remains within a safe range under different conditions. Based on the results of linkage detection and control, a cable clamp safety level map is generated, showing the safety level of the cable clamps in each area, helping to identify which areas are in a high-risk state and which are in a low-risk state.

[0082] Based on the generated cable clamp safety level map, a multi-source verification of slip is performed by tracing back to the previous slip distribution map. Multi-source verification means reassessing slip risk from different data sources, models, and perspectives to ensure the accuracy of slip behavior prediction and control measures. Finally, based on the slip distribution map, cable clamp safety level map, and multi-source verification results, a performance test report of the cable clamp is generated. This report includes a comprehensive assessment of slip risk, safety levels of each area, safety measures to be taken, and long-term monitoring recommendations to help decision-makers take appropriate actions to ensure the long-term stability and safety of the structure.

[0083] In summary, the cable clamp anti-slip performance testing method based on multi-point stress-strain monitoring provided in this application has the following technical effects:

[0084] A hydraulic tensioning module is used to apply graded loads to the target cable, enabling precise control of the load application process. Strain monitoring captures the cable's strain response under different load conditions, providing a dynamic strain dataset that offers more realistic and comprehensive cable strain information. This data helps analyze the contact between the cable clamp and the main cable, as well as the strain variation patterns, thus providing a reliable data foundation for subsequent performance evaluation. Strain difference calculation reveals minute differences on the contact surface between the cable clamp and the main cable, allowing for the acquisition of cumulative strain difference data. This process identifies potential strain accumulation areas on the contact surface, providing early warning information for slippage analysis. This method effectively complements traditional strain monitoring methods, revealing subtle changes in the cable clamp during load bearing. Change identification calculations based on the cumulative strain difference data yield a local strain parameter set, enabling a more precise analysis of the microscopic slippage behavior at the cable clamp and main cable contact surface. Local strain gradient distribution parameters and local slippage parameters can reflect the strain and slippage in detail within the local area. By analyzing the slip distribution of cable clamps, the location and trend of slippage can be revealed, enhancing the ability to identify slippage behavior. Compared to traditional testing methods, this process can provide earlier predictions and more refined risk analysis. By identifying the slippage initiation location and combining it with local slippage parameters to determine the slippage safety factor range, the area where slippage may begin and its corresponding safety level can be accurately identified. This provides a scientific basis for the anti-slip design and maintenance of the structure, ensuring that the structure can effectively resist slippage risks in the actual working environment and enhancing the safety and reliability of the system. By generating a slippage distribution map through cable clamp slippage analysis, the slippage risk of each area of ​​the cable clamp can be clearly shown, facilitating a safety assessment of the structure's slippage performance. Through the safety assessment, the slippage performance safety level can be reasonably classified. Through the above series of analyses, the final performance test report provides complete data support for design, maintenance, and monitoring. The scientific and systematic nature of the report provides strong support for engineering decision-makers, enabling timely risk control and optimization at different stages.

[0085] Example 2 is based on the same inventive concept as the cable clamp anti-slip performance testing method based on multi-point stress-strain monitoring in the previous examples, such as... Figure 2 As shown in the figure, this application provides a cable clamp anti-slip performance testing system based on multi-point stress-strain monitoring, the system comprising:

[0086] The strain monitoring module 10 is used to apply graded loads to the target cable body through the hydraulic tensioning module to monitor strain and obtain a dynamic strain dataset. The change identification and calculation module 20 is used to calculate the strain difference between the cable clamp and the main cable contact surface based on the dynamic strain dataset, obtain the cumulative strain difference data, and perform change identification calculation based on the cumulative strain difference data to obtain a local strain parameter set, which includes local strain gradient distribution parameters and local slip parameters. The coefficient interval determination module 30 is used to identify the slip initiation position based on the local strain gradient distribution parameters and determine the anti-slip safety factor interval based on the local slip parameters. The performance testing module 40 is used to perform cable clamp slip analysis according to the anti-slip safety factor interval, generate a slip distribution map for safety assessment, determine the slip performance safety level, perform cable clamp anti-slip performance testing, and construct a performance testing report.

[0087] Furthermore, the strain monitoring module 10 is used to perform the following operation steps:

[0088] Distributed fiber optic sensors are pre-embedded inside the target cable, and multiple strain gauge arrays are deployed on the outer surface of the cable clamp. A stepped load is applied to the target cable using a hydraulic tensioning module to determine multi-level load data. Stress and strain data are acquired and monitored based on the fiber optic sensors and the multi-level load data to obtain strain distribution data for the entire cable segment. Stress and strain data are also acquired and monitored using the multiple strain gauge arrays and the multi-level load data to obtain strain gauge array data. The strain distribution data for the entire cable segment and the strain gauge array data are integrated to obtain an initial strain dataset. Temperature data from the target cable is retrieved and used to compensate and correct the initial strain dataset to obtain the dynamic strain dataset.

[0089] Furthermore, the change recognition calculation module 20 is used to perform the following operation steps:

[0090] The dynamic strain dataset is disassembled according to the contact surface between the cable clamp and the main cable to determine the strain value sequence on the cable clamp side and the strain value sequence on the main cable side. The data acquisition timestamps of the dynamic strain dataset are retrieved, and the strain value sequences on the cable clamp side and the main cable side are sequentially traversed according to the data acquisition timestamps to perform difference calculations to generate a strain difference sequence. A sliding time window is set along the cable length direction, and the strain difference sequence is accumulated along the time axis according to the sliding time window to obtain an accumulated amount time sequence. The strain difference sequence is integrated according to the accumulated amount time sequence to generate the accumulated strain difference data.

[0091] Furthermore, the change recognition calculation module 20 is used to perform the following operation steps:

[0092] Spatial feature analysis is performed based on the accumulated strain difference data to determine the spatial distribution characteristics. Multiple calculation units are divided according to the axial direction of the main cable contact surface. The accumulated strain difference data is calculated according to the spatial distribution characteristics within these multiple calculation units to obtain multiple spatial change rates of the accumulated values. These multiple spatial change rates correspond to the multiple calculation units. Local identification is performed based on the multiple spatial change rates of the accumulated values ​​to determine local strain gradient distribution parameters. Slip behavior is identified based on the strain gradient change pattern, and local slip parameters are calculated. The local strain gradient distribution parameters and the local slip parameters are integrated to generate the local strain parameter set.

[0093] Furthermore, the change recognition calculation module 20 is used to perform the following operation steps:

[0094] A three-dimensional coordinate system for the cable clamp is constructed, and a mesh mapping unit is established based on the three-dimensional coordinate system. The local strain gradient distribution parameters and the local slip parameters are mapped to the mesh mapping unit for alignment analysis to obtain a spatial coordinate mapping network. Based on the spatial coordinate mapping network, spatial correlation analysis is performed on the local strain gradient distribution parameters and the local slip parameters, and spatial overlapping areas are marked. Based on the spatial coordinate mapping network, time-series evolution analysis is performed on the local strain gradient distribution parameters and the local slip parameters, and a biaxial evolution curve is plotted. Based on the spatial overlapping areas and the biaxial evolution curve, risk coupling analysis is performed on the local strain gradient distribution parameters and the local slip parameters to generate coupled risk data. The coupled risk data is used as avoidance data to integrate the local strain gradient distribution parameters and the local slip parameters to generate the local strain parameter set.

[0095] Furthermore, the coefficient interval determination module 30 is used to perform the following operation steps:

[0096] Based on the local strain gradient distribution parameters, multiple gradient value data are obtained by scanning. These multiple gradient value data are then filtered to obtain multiple high gradient points. Cluster analysis is performed on these high gradient points to delineate multiple high gradient regions. Based on these high gradient regions, maximum values ​​are located to determine the core point. The coordinates of the high gradient core region are determined by labeling the core point in conjunction with its gradient magnitude. These coordinates are then used as the slip start position.

[0097] Furthermore, the coefficient interval determination module 30 is used to perform the following operation steps:

[0098] The influence search is performed centered on the slip initiation position to obtain the cable diameter influence area. Data is extracted based on the cable diameter influence area to determine multiple slip parameters. The average value of the multiple slip parameters is calculated to determine the real-time slip rate. The preload data of high-strength bolts is introduced, and the attenuation of the preload data is calculated to obtain the preload attenuation rate. Friction change analysis is performed based on the temperature data of the main cable contact surface to construct a temperature friction coefficient correction curve. Anti-slip safety analysis is performed on the preload attenuation rate according to the temperature friction coefficient correction curve to generate multiple safety correction coefficients. Multi-level safety coefficient intervals are set according to the growth trend of the multiple safety correction coefficients. The multi-level safety coefficient intervals are added to the anti-slip safety coefficient interval.

[0099] Furthermore, the performance detection module 40 is used to perform the following operation steps:

[0100] A three-dimensional spatial model of the cable clamp is constructed based on the three-dimensional coordinate system of the cable clamp. The multi-level safety factor interval is mapped to the three-dimensional spatial model of the cable clamp for visualization rendering to obtain a multi-color three-dimensional rendering area. Adjacent three-dimensional rendering areas are merged according to the same color, and continuous danger zones are extracted based on the merging results. Based on the continuous danger zones, the area coverage is calculated to obtain the danger coverage area. A double layer is drawn according to the three-dimensional spatial model of the cable clamp. The danger coverage area is synchronized to the lower layer of the double layer, and the strain gradient intensity data is synchronized to the upper layer of the double layer to generate the slip distribution map.

[0101] Furthermore, the performance detection module 40 is used to perform the following operation steps:

[0102] Alignment and matching of the upper layer of the dual-layer system with the lower layer to extract spatial slip hazard features; dynamic impact assessment of the cable clamp based on the spatial slip hazard features, setting multiple safety level judgment criteria; safety assessment of the slip distribution map according to the multiple safety level judgment criteria to determine the slip performance safety level; linkage detection and control of the cable clamp's anti-slip performance based on the slip performance safety level to obtain a cable clamp safety level map; backtracking from the cable clamp safety level map to the slip distribution map for multi-source slip verification, and constructing the cable clamp's performance detection report.

[0103] Through the foregoing detailed description of the cable clamp anti-slip performance testing method based on multi-point stress and strain monitoring, those skilled in the art can clearly understand the cable clamp anti-slip performance testing system based on multi-point stress and strain monitoring in this embodiment. Since it corresponds to the method disclosed in the embodiment, the description is relatively simple, and relevant parts can be referred to the method section.

[0104] The above description of the disclosed embodiments enables those skilled in the art to make or use this application. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of this application. Therefore, this application is not to be limited to the embodiments shown herein, but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A method for detecting the anti-slip performance of cable clamps based on multi-point stress-strain monitoring, characterized in that, The method includes: The target cable is subjected to graded loads by a hydraulic tensioning module to monitor strain and obtain a dynamic strain dataset. Based on the dynamic strain dataset, the strain difference between the cable clamp and the main cable contact surface is calculated to obtain the cumulative strain difference data. Based on the cumulative strain difference data, change identification calculation is performed to obtain a local strain parameter set, which includes local strain gradient distribution parameters and local slip parameters. The slip initiation position is identified based on the local strain gradient distribution parameters, and the anti-slip safety factor range is determined by combining the local slip amount parameters. According to the aforementioned anti-slip safety factor range, cable clamp slippage analysis is performed, a slippage distribution map is generated for safety assessment, the slippage performance safety level is determined, cable clamp anti-slip performance is tested, and a performance test report is constructed. The method for obtaining a local strain parameter set by performing change identification calculations based on the accumulated strain difference data includes: Spatial feature analysis is performed based on the accumulated strain difference data to determine the spatial distribution characteristics. The main cable contact surface is divided into multiple calculation units according to the axial direction. The cumulative strain difference data is calculated according to the spatial distribution characteristics of the multiple calculation units to obtain multiple cumulative spatial change rates. The multiple cumulative spatial change rates are related to the multiple calculation units. Local strain gradient distribution parameters are determined by identifying the spatial change rates of the multiple cumulative quantities. Identify slip behavior based on strain gradient change patterns and calculate local slip parameters; The local strain gradient distribution parameters and the local slip parameters are integrated to generate the local strain parameter set; The method includes: Construct a three-dimensional coordinate system for the cable clamp, and establish a mesh mapping unit based on the three-dimensional coordinate system of the cable clamp; The local strain gradient distribution parameters and the local slip parameters are mapped to the mesh mapping cells for alignment analysis to obtain a spatial coordinate mapping mesh. Based on the spatial coordinate mapping network, spatial correlation analysis is performed on the local strain gradient distribution parameters and the local slip parameters to mark the spatial overlapping areas; Based on the spatial coordinate mapping network, the time-series evolution analysis of the local strain gradient distribution parameters and the local slip parameters is performed, and biaxial evolution curves are plotted. Based on the spatially overlapping region and the biaxial evolution curve, a risk coupling analysis is performed on the local strain gradient distribution parameter and the local slip parameter to generate coupling risk data. Using the coupling risk data as avoidance data, the local strain gradient distribution parameters and the local slip parameters are integrated to generate the local strain parameter set.

2. The method for detecting the anti-slip performance of cable clamps based on multi-point stress-strain monitoring as described in claim 1, characterized in that, The dynamic strain dataset is obtained by applying graded loads to the target cable using a hydraulic tensioning module and monitoring the strain. The method includes: Distributed fiber optic sensors are pre-embedded inside the target cable body, and multiple strain gauge arrays are arranged on the outer surface of the cable clamp. A stepped load is applied to the target cable through the tensioning device of the hydraulic tensioning module to determine multi-level load data; Based on the fiber optic sensor and the multi-level load data, stress and strain acquisition and monitoring are performed to obtain strain distribution data of the entire cable segment. Stress and strain data are acquired and monitored by combining the multiple strain gauge arrays with the multi-level load data to obtain strain gauge array data. The strain distribution data of the entire cable segment is integrated with the strain gauge array data to obtain an initial strain dataset; The temperature data of the target cable is retrieved and used to compensate and correct the initial strain dataset to obtain the dynamic strain dataset.

3. The method for detecting the anti-slip performance of cable clamps based on multi-point stress-strain monitoring as described in claim 1, characterized in that, Based on the dynamic strain dataset, the strain difference between the cable clamp and the main cable contact surface is calculated to obtain the cumulative strain difference data. The method includes: The dynamic strain dataset is decomposed according to the contact surface between the cable clamp and the main cable to determine the strain value sequence on the cable clamp side and the strain value sequence on the main cable side. Retrieve the data acquisition timestamp of the dynamic strain dataset, and perform difference calculations on the strain value sequence of the cable clamp side and the strain value sequence of the main cable side according to the data acquisition timestamp to generate a strain difference sequence. A sliding time window is set along the cable length direction, and the strain difference value sequence is accumulated along the time axis according to the sliding time window to obtain the accumulated amount time sequence; The strain difference sequence is integrated according to the cumulative time series to generate the cumulative strain difference data.

4. The method for detecting the anti-slip performance of cable clamps based on multi-point stress-strain monitoring as described in claim 1, characterized in that, The method for identifying the slip initiation position based on the local strain gradient distribution parameters includes: Based on the local strain gradient distribution parameters, a scan is performed to obtain multiple gradient value data. The multiple gradient value data are then traversed and filtered to obtain multiple high gradient points. Cluster analysis is performed on the multiple high gradient points to delineate multiple high gradient regions. Based on the multiple high gradient regions, maximum value localization is performed to determine the core points. The coordinates of the high-gradient core region are determined by marking the core point and its gradient magnitude, and the coordinates of the high-gradient core region are used as the starting position of the slip.

5. The method for detecting the anti-slip performance of cable clamps based on multi-point stress-strain monitoring as described in claim 1, characterized in that, Determining the anti-slip safety factor range by combining the slip initiation position with the local slip parameter includes the following methods: The influence search is performed with the slip initiation position as the center to obtain the cable path influence area. Data is extracted based on the cable path influence area to determine multiple slip amount parameters. The real-time slip rate is determined by calculating the average value of the multiple slip parameters. The preload force data of high-strength bolts is introduced, and the attenuation is calculated based on the preload force data to obtain the preload attenuation rate; Friction variation analysis was performed based on temperature data of the main cable contact surface, and a temperature friction coefficient correction curve was constructed. Based on the temperature friction coefficient correction curve, an anti-slip safety analysis is performed on the preload attenuation rate to generate multiple safety correction coefficients; Multi-level safety factor ranges are set according to the growth trend of the aforementioned multiple safety correction factors; The multi-level safety factor range is added to the anti-slip safety factor range.

6. The method for detecting the anti-slip performance of cable clamps based on multi-point stress-strain monitoring as described in claim 5, characterized in that, Perform cable clamp slip analysis according to the aforementioned anti-slip safety factor range, and generate a slip distribution map. The method includes: A three-dimensional spatial model of the cable clamp is constructed based on the three-dimensional coordinate system of the cable clamp. The multi-level safety factor interval is mapped to the three-dimensional spatial model of the cable clamp for visualization rendering to obtain a multi-color three-dimensional rendering area. Traverse the multi-color 3D rendering area to merge adjacent areas of the same color, and extract continuous danger zones based on the merging results; Based on the continuous danger zone, regional coverage calculation is performed to obtain the danger coverage area; Based on the three-dimensional spatial model of the cable clamp, a double layer is drawn, the dangerous coverage area is synchronized to the lower layer of the double layer, and the strain gradient intensity data is synchronized to the upper layer of the double layer to generate the slip distribution map.

7. The method for detecting the anti-slip performance of cable clamps based on multi-point stress-strain monitoring as described in claim 6, characterized in that, The slip distribution map is used for safety assessment to determine the slip performance safety level. The anti-slip performance of the cable clamps is then tested, and a performance test report is generated. The methods include: Align and match the upper layer of the two-layer structure according to the lower layer to extract spatial slip hazard features; Based on the aforementioned spatial slippage hazard characteristics, a dynamic impact assessment of the cable clamp is conducted, and multiple safety level judgment criteria are established. The slip distribution map is assessed for safety according to the multiple safety level determination criteria to determine the slip performance safety level. Based on the slip performance safety level, the anti-slip performance of the cable clamp is monitored and controlled in a coordinated manner to obtain a cable clamp safety level map. The slip distribution map is then traced back to the cable clamp safety level map to perform multi-source verification of slip and to construct the performance test report of the cable clamp.

8. A cable clamp anti-slip performance testing system based on multi-point stress-strain monitoring, characterized in that, The system is used to implement the cable clamp anti-slip performance testing method based on multi-point stress-strain monitoring as described in any one of claims 1-7, the system comprising: The strain monitoring module is used to apply graded loads to the target cable through the hydraulic tensioning module to monitor strain and obtain dynamic strain datasets. The change recognition and calculation module is used to calculate the strain difference between the contact surface between the cable clamp and the main cable based on the dynamic strain dataset, obtain the cumulative strain difference data, and perform change recognition calculation based on the cumulative strain difference data to obtain a local strain parameter set, which includes local strain gradient distribution parameters and local slip parameters. The coefficient interval determination module is used to identify the slip initiation position based on the local strain gradient distribution parameters and determine the anti-slip safety factor interval in combination with the local slip amount parameters. The performance testing module is used to perform cable clamp slip analysis according to the anti-slip safety factor range, generate a slip distribution map for safety assessment, determine the slip performance safety level, perform cable clamp anti-slip performance testing, and construct a performance testing report.

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