Method and system for evaluating performance of inhaul cable test piece under low-speed impact condition

Abstract

The invention relates to the technical field of performance evaluation, in particular to an inhaul cable test piece performance evaluation method and system under the low-speed impact condition, and provides the following scheme that stress data are obtained through a drop hammer impact test, and the maximum load and anchoring performance are calculated through a data analysis model; integrating and optimizing the evaluation data through the quantitative relation model; according to the method, the overall mechanical property of the inhaul cable under the low-speed impact condition can be comprehensively analyzed, the accuracy and applicability of an evaluation result are ensured from multiple aspects such as dynamic response, anchoring stability and energy absorption efficiency through a multi-layer data analysis model, and the safety requirements in different engineering applications are met.

Description

Technical Field

[0001] The present invention relates to the technical field of performance evaluation, and in particular to a method and system for evaluating the performance of a cable specimen under low-speed impact conditions. Background Art

[0002] As the scale of modern bridges, buildings and engineering structures becomes larger and larger, cable systems such as stay cables are increasingly used in these structures. However, in actual application environments, cable structures are often subject to various external shocks, such as accidental collisions with vehicles and earthquakes caused by natural disasters. Especially under low-speed impact conditions, the bearing capacity, stability and fatigue resistance of the cable system are particularly important. These impacts may cause fatigue damage, reduced bearing capacity or even fracture of the cables, posing a threat to the safety and durability of the overall structure. Therefore, effective evaluation of the performance of cable specimens under low-speed impact conditions has become a key and urgent issue in structural design and safety assurance.

[0003] At present, traditional cable performance evaluation methods are mainly based on static tensile tests and fatigue tests, and the focus is mostly on the tensile, fracture and deformation behaviors of cables under static and cyclic loads. However, these methods are difficult to effectively reflect the complex mechanical behavior of cables under transient load conditions such as low-speed impact. Cable specimens under low-speed impact conditions not only have to withstand large instantaneous impact forces, but also involve complex dynamic responses, energy absorption and stability assessment of anchoring structures. Traditional methods cannot fully reflect the dynamic response characteristics under impact loads. Therefore, how to comprehensively evaluate the performance of cables and their anchoring structures under low-speed impact environments has become a technical problem in research.

[0004] For example, the Chinese patent application with the authorization announcement number CN108225906B discloses a method for monitoring, identifying and evaluating fatigue life of cables based on computer vision. It takes images of corroded high-strength steel wires and extracts image features from them. It then builds a corrosion degree evaluation model, and then builds a fatigue life characteristic index evaluation model. It matches the degradation state of steel wire corrosion fatigue performance under artificial accelerated corrosion tests, and finally completes the corrosion state identification and fatigue life evaluation of in-service cables. The invention has high recognition accuracy, fast speed and low cost. The invention can also meet the real-time data processing requirements of online monitoring and early warning of cable corrosion fatigue, that is, it does not update the data set, and directly recognizes the images collected by consumer-grade ordinary cameras. The invention improves the automation, intelligence, accuracy and robustness of cable corrosion monitoring, identification and fatigue life evaluation, and provides a solution for the automatic monitoring and identification of corrosion fatigue of bridge structure cables.

[0005] The above patents have the problems raised by this background technology: it is difficult to effectively reflect the transient dynamic response characteristics under low-speed impact conditions, and lack a comprehensive analysis of key performance such as the stability of the anchoring structure and energy absorption efficiency, resulting in insufficient accuracy and applicability of the evaluation results. To solve the above problems, this application designs a performance evaluation method and system for cable specimens under low-speed impact conditions. Summary of the invention

[0006] The technical problem to be solved by the present invention is to address the deficiencies of the prior art and provide a method and system for evaluating the performance of cable specimens under low-speed impact conditions. The force data is obtained by combining a drop hammer impact test, and the maximum load and anchoring performance are calculated through a data analysis model. The evaluation data is integrated and optimized through a quantitative relationship model, so that the method can comprehensively analyze the overall mechanical properties of the cable under low-speed impact conditions. Specifically, the method uses a multi-layer data analysis model to start from multiple aspects such as dynamic response, anchoring stability, and energy absorption efficiency to ensure the accuracy and applicability of the evaluation results and meet the safety requirements of different engineering applications.

[0007] To achieve the above object, the present invention provides the following technical solutions:

[0008] A method for evaluating performance of a cable specimen under low-speed impact conditions, the method comprising:

[0009] The cable specimens are tested by a drop hammer impact test to obtain the stress data of the cable specimens under different impact conditions;

[0010] Analyzing the force data to calculate the maximum load of the cable specimen;

[0011] Constructing a data analysis model, analyzing the stability and bearing capacity of the anchoring structure of the cable specimen through the data analysis model, and calculating the anchoring performance of the cable specimen;

[0012] A quantitative relationship model is established according to the maximum load and the anchoring performance, and the design parameters of the cable and its anchoring structure are optimized according to the quantitative relationship model.

[0013] The drop weight impact test is performed on the cable specimen by using a drop weight impact test device, and the drop weight impact test device comprises:

[0014] The drop weight assembly is arranged directly above the cable specimen and is used to release from a preset height to generate an impact force, simulating the low-speed impact that may occur in the actual environment;

[0015] The semi-cylindrical hammer head is installed at the end of the drop hammer, which can evenly transfer the impact force of the drop hammer to the surface of the cable specimen, thereby ensuring the stability and uniformity of the impact effect;

[0016] The cable specimen fixing system includes steel plates, fixing devices and support columns arranged at both ends of the cable specimen to ensure that the cable specimen remains stable during the impact process without lateral displacement;

[0017] The force sensor is installed near the impact area to measure the instantaneous impact force on the cable specimen during the impact process and transmit the instantaneous impact force to the data acquisition system;

[0018] The displacement sensor is installed at the key position of the cable specimen to record the displacement change of the cable during the impact process in real time to obtain the deformation situation;

[0019] The data acquisition system, connected to the force sensor and displacement sensor, is used to collect and store the force and displacement data collected during the test for subsequent data analysis and evaluation.

[0020] The analyzing the force data comprises:

[0021] Connecting the force data to generate a force curve based on a time series, and extracting key dynamic response points according to the force curve;

[0022] Dividing the stress curve into a buffer section, a load-bearing section, a decay section and a recovery section according to the key dynamic response points;

[0023] Performing adaptive polynomial segmented fitting on the force curves corresponding to the buffer section, the load-bearing section, the attenuation section and the recovery section, respectively, to generate a fitting curve that satisfies the force characteristics of each stage;

[0024] According to the fitting curve, a hierarchical grey correlation analysis model is constructed, and the grey correlation parameters of each stage are calculated by the hierarchical grey correlation analysis model. The initial buffering capacity, peak bearing capacity, energy absorption efficiency and residual strength recovery force of the cable specimen are calculated according to the grey correlation parameters.

[0025] The hierarchical grey relational analysis model comprises:

[0026] Map the fitting curves of each stage into the grey relational space, compare the fitting curves of each stage with the ideal curve, and calculate the difference sequence;

[0027] Calculate dynamic weights according to the stages corresponding to the difference sequence, assign the dynamic weights to the difference sequence, and obtain grey relational parameters, wherein the grey relational parameters include nonlinear adjustment factors, and the nonlinear adjustment factors include nonlinear response and geometric characteristics of the cable specimen;

[0028] According to the grey correlation parameters of each stage, a correlation difference matrix between stages is constructed, and according to the grey correlation parameters and the correlation difference matrix, the initial buffering capacity, peak bearing capacity, energy absorption efficiency and residual strength recovery force of the cable specimen are calculated.

[0029] The calculation of the maximum load of the cable specimen includes:

[0030] The parameters of initial buffering capacity, peak load-bearing capacity, energy absorption efficiency and residual strength recovery were standardized;

[0031] The normalized parameters are combined by weighted averaging to calculate the dynamic response index;

[0032] According to the frequency response of the cable specimen under different impact conditions, the residual strength restoring force is subjected to Fourier transformation to calculate the nonlinear recovery coefficient;

[0033] According to the dynamic response index and the nonlinear recovery coefficient, the maximum load of the cable specimen is calculated. The calculation formula of the maximum load is:

[0034] ;

[0035] in, represents the maximum load of the cable specimen, represents the dynamic correction coefficient, represents the reference load of the cable specimen, represents the dynamic response coefficient, represents the nonlinear restitution coefficient, represents the peak bearing capacity of the cable specimen, represents the energy absorption efficiency of the cable specimen, Represents the material property coefficient of the cable specimen.

[0036] The data analysis model comprises:

[0037] The parameter extraction layer is used to perform multi-dimensional parameter decomposition on the force data of the cable specimen and convert the original force data from the time domain to the wavelet domain and the principal component domain;

[0038] The parameter clustering layer divides the force data under different impact conditions into characteristic clusters based on the original force data in the wavelet domain and the principal component domain through a clustering algorithm, and calculates the clustering results based on the characteristic clusters;

[0039] The modal decomposition layer is used to apply the modal decomposition technology to the clustering results, extract the characteristic modes of the anchoring structure, and analyze the frequency spectrum response of the characteristic modes to obtain the natural frequency, damping ratio and modal shape of the cable specimen in different modes.

[0040] The calculation formula of the anchoring performance is:

[0041] ;

[0042] in, represents the anchoring performance of the cable specimen, n represents a single characteristic mode of the anchoring structure, N represents the total number of characteristic modes of the anchoring structure, represents the stiffness coefficient of the nth eigenmode, represents the mode shape function of the nth eigenmode, represents the damping ratio of the nth eigenmode, represents the natural frequency of the nth characteristic mode, t represents the response time after the impact, represents the cosine function, represents the damping coefficient of the nth eigenmode, It represents the time rate of change of the nth eigenmode shape and is used to reflect the instantaneous velocity effect.

[0043] The quantitative relationship model includes:

[0044] The parameter coupling layer is used to couple the maximum load and anchoring performance of the cable specimen and calculate the comprehensive performance score;

[0045] A target optimization layer, which optimizes the design parameters of the cable specimen and its anchoring structure through an optimization algorithm according to the comprehensive performance score, wherein the optimization includes maximizing the impact strength of the structure, minimizing material consumption and weight, and extending fatigue life;

[0046] The feedback adjustment layer verifies and adjusts the optimized design parameters through a closed-loop feedback mechanism, and adjusts the objective function of the optimization algorithm based on the verification results.

[0047] A cable specimen performance evaluation system under low-speed impact conditions, the system comprising a data acquisition module, a performance analysis module and a design optimization module;

[0048] The data acquisition module simulates the low-speed impact conditions in the actual environment through the drop hammer impact test to collect the force and displacement data of the cable specimen;

[0049] The performance analysis module is provided with a force data analysis strategy, which is used to perform multi-dimensional performance analysis on the output of the data acquisition module and calculate the maximum load and anchoring performance of the cable specimen;

[0050] The design optimization module applies the results of the performance analysis to the design optimization of the cable specimen and the anchoring structure based on the quantitative relationship model, and adjusts the design parameters through the optimization algorithm to maximize the impact strength, reduce the weight and improve the fatigue life.

[0051] The performance analysis module comprises:

[0052] A data preprocessing unit, used to preprocess the force and displacement data output by the data acquisition module, and perform denoising, filtering and standardization operations;

[0053] The maximum load analysis unit identifies and extracts the peak load-bearing capacity of the cable specimen under impact through time series analysis and segmented fitting of the force data, and obtains the ultimate load-bearing capacity of the cable specimen by combining the frequency response and energy absorption characteristics;

[0054] Anchor performance evaluation unit, which evaluates the stability and bearing capacity of the anchor structure under impact loads through modal analysis and dynamic response analysis methods;

[0055] The force data analysis strategy includes dynamic response extraction logic and modal feature analysis logic;

[0056] The dynamic response extraction logic is configured in the maximum load analysis unit and is used to extract dynamic response features from the time series;

[0057] The modal characteristic analysis logic is configured in the anchoring performance evaluation unit and is used to decompose the modal characteristics of the anchoring structure, including natural frequency, damping ratio and modal shape.

[0058] Compared with the prior art, the present invention has the following beneficial effects:

[0059] 1. The present invention can comprehensively analyze the stress characteristics of the cable specimen under impact load. Through dynamic response analysis, energy absorption efficiency evaluation and anchoring performance stability calculation, the accuracy and reliability of the evaluation results are improved;

[0060] 2. The present invention optimizes the design parameters through a quantitative relationship model and a target optimization algorithm, so that the cable and its anchoring structure achieve an optimal balance in terms of impact strength, weight reduction and fatigue life, thereby better meeting the safety and economy requirements in engineering applications. BRIEF DESCRIPTION OF THE DRAWINGS

[0061] Other features, objects and advantages of the present invention will become more apparent from the detailed description of non-limiting embodiments made with reference to the following drawings:

[0062] Figure 1 This is a schematic flow chart of a method for evaluating cable specimen performance under low-speed impact conditions according to Example 1 of the present invention;

[0063] Figure 2 This is a flow chart of force data analysis in Example 1 of the present invention;

[0064] Figure 3 This is a flow chart of grey correlation analysis in Example 1 of the present invention;

[0065] Figure 4 This is a structural diagram of a data analysis model according to Embodiment 1 of the present invention;

[0066] Figure 5 This is a module diagram of the cable specimen performance evaluation system under low-speed impact conditions in Example 2 of the present invention. DETAILED DESCRIPTION

[0067] The technical solutions in the embodiments of the present invention will be described clearly and completely below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all the embodiments.

[0068] Example 1

[0069] See also Figure 1 The present invention provides an embodiment: a method for evaluating the performance of a cable specimen under low-speed impact conditions, wherein the method comprises the following specific steps:

[0070] S1: Test the cable specimen through a drop hammer impact test to obtain the force data of the cable specimen under different impact conditions;

[0071] In this step, the magnitude and direction of the impact force are adjusted by setting different drop hammer heights and release positions, so as to comprehensively evaluate the performance of the specimen under various impact conditions. Force sensors and displacement sensors are installed at key locations of the specimen to monitor the instantaneous changes in the impact force and the deformation response of the specimen in real time. The data collected by these sensors are recorded and transmitted in real time through the data acquisition system, providing a basis for subsequent data analysis and performance evaluation. Through multiple tests and data acquisition under different impact conditions, the complete force characteristics and deformation of the cable specimen under low-speed impact conditions can be obtained;

[0072] S2: Analyze the force data and calculate the maximum load of the cable specimen;

[0073] S3: construct a data analysis model, analyze the stability and bearing capacity of the anchoring structure of the cable specimen through the data analysis model, and calculate the anchoring performance of the cable specimen;

[0074] In this step, the anchor performance evaluation method based on modal analysis and dynamic response is established by combining the geometric characteristics and material properties of the anchor structure. The data analysis model uses the modal characteristics (such as natural frequency, damping ratio and modal shape) extracted from the force data as input to comprehensively evaluate the dynamic response of the specimen under impact conditions. Through modal decomposition, the response characteristics of the anchor structure at different frequencies can be identified, and then its stiffness, stability and energy dissipation capacity under impact can be analyzed;

[0075] S4: According to the maximum load and anchoring performance, a quantitative relationship model is established, and the design parameters of the cable and its anchoring structure are optimized according to the quantitative relationship model;

[0076] In this step, a quantitative relationship model is established based on the maximum load and anchoring performance of the specimen to associate different performance parameters and structural characteristics. The quantitative relationship model couples multiple performance indicators such as maximum load, anchoring stiffness, fatigue life, etc. to generate a comprehensive performance score to fully reflect the performance of the cable specimen under impact conditions. The quantitative relationship model uses nonlinear fitting technology to balance various performance indicators with dynamically assigned weight coefficients, making the score more scientific and objective;

[0077] The drop weight impact test is performed on the cable specimen by using a drop weight impact test device, and the drop weight impact test device comprises:

[0078] The drop hammer assembly is placed directly above the cable specimen and is used to release from a preset height to generate impact force, simulating the low-speed impact that may occur in the actual environment, so that the specimen exhibits a stress state similar to that in the actual working condition under the force. The height and weight of the drop hammer assembly can be adjusted to change the impact energy, thereby testing the performance of the specimen under different impact conditions;

[0079] The semi-cylindrical hammer head is installed at the end of the drop hammer assembly to evenly transfer the impact force of the drop hammer to the surface of the specimen. Its semi-cylindrical design makes the impact force distribution more uniform, reduces the local stress concentration phenomenon, and thus simulates a more realistic impact distribution in the actual force environment;

[0080] The cable specimen is located in the center of the entire drop weight impact test device and is directly impacted by the drop weight assembly. The specimen represents the actual cable in use, and its performance will be evaluated under impact load. The two ends of the specimen are connected by steel plates and fixtures to ensure the stability of the specimen during the impact process, and there will be no test errors caused by lateral slippage;

[0081] The cable specimen fixing assembly includes steel plates, fixing devices and support columns arranged at both ends of the cable specimen to ensure that the cable specimen remains stable during the impact process without lateral displacement;

[0082] The force sensor is installed below or near the impact area to measure the instantaneous impact force on the specimen during the impact process. The instantaneous impact force refers to the force acting on an object in a very short period of time. This force is characterized by a very short duration but a very high intensity, and usually occurs during a rapid collision or impact. In a drop hammer impact test, the instantaneous force generated when the drop hammer hits the specimen is the instantaneous impact force. The force sensor transmits the captured data to the data acquisition system in real time to ensure that the peak value and change curve of the impact force can be accurately recorded. These data are the key to the subsequent analysis of the strength and energy absorption characteristics of the specimen;

[0083] The displacement sensor is installed at the key parts of the specimen. The key parts refer to the deformation parts of the specimen, such as the impact center area and its surroundings, or the high stress area near the fixtures at both ends of the cable. It is used to monitor and record the displacement of the specimen during the impact in real time. The displacement sensor can capture the deformation data of the specimen, especially the deformation under the impact force, which is crucial to evaluate the elastic and plastic deformation characteristics of the specimen.

[0084] Strain sensors are installed in some areas of the specimen to measure the strain of the specimen under the impact force. The strain sensors can provide detailed strain distribution data to help study the stress distribution characteristics of the cable material during the impact process;

[0085] Resistive displacement sensor, used to measure displacement changes in a wider range, combined with displacement sensor, can provide displacement data of the specimen to ensure the accuracy of the test;

[0086] A data acquisition system, connected to the force sensor and displacement sensor, for collecting and storing the force and displacement data collected during the test for subsequent data analysis and evaluation;

[0087] See also Figure 2 , the force data analysis flow chart of the embodiment of the present invention, the specific steps of S2 are as follows:

[0088] S2.1: connecting the force data to generate a force curve based on a time series, and extracting key dynamic response points according to the force curve;

[0089] The force data obtained by the drop hammer impact test device is first time-seriesized, that is, the data points are connected one by one according to the time axis to generate a complete force curve. This force curve shows the force changes of the specimen at different time points during the impact process, which can intuitively reflect the response process of the cable specimen under the impact force;

[0090] By processing the stress data through time series analysis technology, the key dynamic response points in the curve are extracted, including peak points, valley points, rising points and falling points. These points represent the important mechanical responses of the cable specimen during the impact process and can show the stress state and structural response of the specimen in different time periods;

[0091] S2.2: Divide the stress curve into a buffer section, a load-bearing section, a decay section and a recovery section according to the key dynamic response point;

[0092] According to the extracted key dynamic response points, the stress curve is divided into four main stages: buffer section, load-bearing section, attenuation section and recovery section. Each stage corresponds to the performance of the specimen under different stress conditions. The buffer section is the stage when the specimen just begins to be impacted, the load-bearing section is the stage when the specimen bears the maximum load, the attenuation section is the stage when the impact force begins to weaken, and the recovery section is the process of the specimen gradually returning to a balanced state. The curve is automatically divided based on the position of different dynamic response points and the changing trend of the curve. Through segmented analysis, the response characteristics of the specimen at each stage can be carefully observed, laying the foundation for subsequent fitting analysis and correlation calculation;

[0093] S2.3: performing adaptive polynomial segmented fitting on the force curves corresponding to the buffer section, the load-bearing section, the attenuation section and the recovery section, respectively, to generate a fitting curve that satisfies the force characteristics of each stage;

[0094] Specifically, according to the stress characteristics of each segment, the appropriate polynomial order is selected for fitting, so as to generate a fitting curve that meets the stress characteristics of each stage. For example, for the fast-changing buffer segment, a high-order polynomial is used for fitting, while a low-order polynomial is selected for the stable recovery segment to simplify the model;

[0095] Through adaptive polynomial fitting, the complex impact response curve can be decomposed into a simple mathematical expression, which is convenient for the calculation and analysis of the subsequent model. At the same time, the fitting curve retains the characteristics of the original force data, ensuring that the model can reflect the actual force characteristics of the specimen;

[0096] S2.4: constructing a hierarchical grey correlation analysis model according to the fitting curve, calculating grey correlation parameters of each stage through the hierarchical grey correlation analysis model, and calculating the initial buffering capacity, peak bearing capacity, energy absorption efficiency and residual strength recovery force of the cable specimen according to the grey correlation parameters;

[0097] By calculating the grey correlation parameters, the stress performance of the specimen at different stages can be quantitatively evaluated, providing a basis for cable design and optimization. This analysis model not only improves the utilization of data, but also effectively evaluates the bearing capacity of the specimen under complex impact conditions;

[0098] See also Figure 3 , Grey correlation analysis flow chart of the embodiment of the present invention, the core of the hierarchical grey correlation analysis model is to compare the different stress stages of the cable specimen with the ideal state through staged grey correlation analysis to quantify its performance at each stage. The model accurately reflects the response characteristics of the cable under low-speed impact conditions through dynamic weights, grey correlation and nonlinear adjustment factors. The hierarchical grey correlation analysis model includes:

[0099] The fitting curves of each stage are mapped into the grey relational space, and the fitting curves of each stage are compared with the ideal curves to calculate the difference sequence. The difference sequence is calculated point by point by calculating the difference between the fitting curve and the ideal curve to form a sequence, which is used to characterize the degree of deviation between the actual stress state of the specimen and the ideal state at this stage.

[0100] Different dynamic weights are assigned based on the value range of the difference sequence and the importance of each stage in the force process. The dynamic weight takes into account the relative importance of the stage in the overall mechanical properties, so that the key characteristics exhibited in different stages can have an appropriate impact on the final grey relational degree parameters. For example, the dynamic weight of the load-bearing section may be higher to highlight its impact on the maximum load performance of the specimen;

[0101] The design of dynamic weights aims to assign different weight coefficients according to the importance of different stages to ensure that the key stages have a greater impact in the final performance evaluation. For example, in an impact test, the load-bearing stage is often the key stage for evaluating the maximum load-bearing capacity of the structure, while the buffering and attenuation stages are mainly used to observe energy absorption efficiency and stability. Therefore, different stages have different importance, and fixed weights are difficult to fully reflect the impact of each stage on the overall performance;

[0102] Dynamic weights are automatically assigned based on the numerical characteristics of the difference sequence. Specifically, the model statistically analyzes the difference sequences of each stage to identify which stages are more important when bearing the maximum impact force, and assigns higher weights to these stages. At the same time, by analyzing the mechanical response characteristics of each stage, the weights are further modified to dynamically adapt to different impact conditions.

[0103] Dynamic weights are applied to the difference sequence to obtain the grey relational parameter, which quantitatively reflects the matching degree of each stage with the ideal model by comprehensively considering the difference sequence and weight distribution.

[0104] Under low-speed impact conditions, the stress behavior of the cable specimen has significant nonlinear characteristics, such as material yielding and plastic deformation. In order to adapt to these nonlinear responses, the model introduces a nonlinear adjustment factor to modify the gray correlation parameters so that the analysis results can better reflect the actual mechanical properties. The nonlinear adjustment factor is calculated based on the geometric characteristics and material properties of the specimen. For example, the nonlinear stress-strain relationship of the material can be reflected in the gray correlation parameters through the adjustment factor, making the parameters more sensitive to changes in force. The geometric characteristics are reflected in the influence of the shape of the structure on the distribution of force. The model is dynamically adjusted through the adjustment factor to adapt to specimens of different shapes;

[0105] According to the difference sequence and the preset correlation function, the grey correlation parameter is calculated. The closer the grey correlation parameter is to 1, the closer the actual force curve is to the ideal state;

[0106] The grey correlation parameters of each stage are arranged in order to form a correlation difference matrix, which is used to systematically evaluate the correlation differences between different stages. The correlation difference matrix is ​​a quantitative tool used to systematically display the differences in mechanical properties at different stages. By comparing the grey correlation parameters of each stage, the correlation distribution of different stages can be clearly seen, thereby more comprehensively evaluating the comprehensive performance of the specimen.

[0107] The grey correlation parameters of the buffer section, load-bearing section, attenuation section and recovery section are arranged in a matrix, and each matrix element represents the correlation of a certain stage. The rows and columns in the matrix correspond to different mechanical stages, and the values ​​of the matrix elements reflect the differences in correlation between the stages. For example, when the difference between the load-bearing section and the buffer section is large, the value of the element will be significantly lower, prompting designers to pay attention to the improvement of load-bearing performance;

[0108] Based on the correlation difference matrix, the initial buffering capacity, peak bearing capacity, energy absorption efficiency and residual strength recovery of the specimen are further calculated. By decomposing and analyzing the parameter values ​​in the matrix, the different mechanical performance indicators of the specimen during the impact process are quantified;

[0109] Specifically, it is assumed that in the actual impact test, the grey correlation parameter of the cable specimen in the buffer section is 0.8, the load section is 0.9, the attenuation section is 0.7, and the recovery section is 0.85. Through the analysis of the correlation difference matrix, the performance of the specimen in the load stage is close to the ideal state, indicating that it has good peak load-bearing capacity. At the same time, the lower grey correlation degree is shown in the attenuation section, indicating that there is room for improvement in the impact energy dissipation of the specimen.

[0110] Through this analysis model, the mechanical performance of the specimen at each stage can be quickly identified to determine whether its energy absorption characteristics need to be strengthened or its peak load-bearing capacity needs to be improved. This multi-stage, hierarchical analysis method significantly improves the accuracy and detail of performance evaluation and provides in-depth analysis that cannot be achieved by traditional single load test methods.

[0111] These processed parameters are combined by weighted average to form a dynamic response index, thereby evaluating the overall load-bearing capacity of the cable specimen under different impact conditions. Based on the frequency response characteristics, the residual strength restoring force parameters are Fourier transformed, the nonlinear recovery coefficient is calculated, and the maximum load of the cable specimen is calculated by combining the dynamic response index and the nonlinear recovery coefficient. The calculation of the maximum load of the cable specimen includes:

[0112] The parameters of initial buffering capacity, peak bearing capacity, energy absorption efficiency and residual strength recovery force are standardized. This process eliminates the influence of different indicator dimensions, allowing various indicators to be compared on the same scale. The standardized parameters reflect the relative strength of various performances during the entire impact process, making the final dynamic response index more accurate and unified;

[0113] Under low-speed impact conditions, the performance of the specimen is not determined by a single factor. For example, the peak load-bearing capacity can only reflect its load-bearing capacity in a short period of time, while ignoring important indicators such as buffering performance and energy absorption efficiency. Therefore, the standardized parameters are combined through weighted average to calculate the dynamic response index. The weight of each parameter is dynamically adjusted according to its impact on the overall performance. The higher the final calculated dynamic response index, the better the specimen performs during the impact process and the stronger its impact resistance.

[0114] Cable specimens may exhibit nonlinear recovery properties such as viscoelasticity or plastic deformation under low-speed impact conditions. These properties make the specimens not recover to their original state immediately after impact, but recover gradually. This recovery ability is crucial for judging the durability of the structure;

[0115] According to the frequency response of the cable specimen under different impact conditions, the residual strength restoring force is Fourier transformed, the time series of the restoring force is converted to the frequency domain, the frequency characteristics are extracted and the nonlinear recovery coefficient is calculated. This coefficient describes the restoring force characteristics of the specimen after being subjected to force. It is a parameter that can reflect the nonlinear recovery characteristics. The nonlinear recovery coefficient is used to describe the nonlinear characteristics of the restoring force of the specimen after impact. Since the cable may experience multiple repeated impacts under actual working conditions, its recovery characteristics directly affect the long-term stability and durability of the structure;

[0116] According to the dynamic response index and the nonlinear recovery coefficient, the maximum load of the cable specimen is calculated. The calculation formula of the maximum load is:

[0117] ;

[0118] in, represents the maximum load of the cable specimen, It represents the dynamic correction factor, which is used to adjust the influence of the reference load. Especially under dynamic impact conditions, the influence of the reference load on the maximum load needs to be adjusted to adapt to the actual impact environment. represents the reference load of the cable specimen, represents the dynamic response coefficient, represents the nonlinear restitution coefficient, The peak bearing capacity of the cable specimen is the maximum instantaneous force that the specimen can withstand under impact load. This is an important mechanical performance indicator of the specimen, which directly reflects the strength of the material. Through the drop hammer impact test, the force time series curve of the specimen is recorded. The peak bearing capacity is the maximum value in the curve, which reflects the bearing capacity of the specimen under extreme stress conditions. It indicates the energy absorption efficiency of the cable specimen, which indicates the ratio of the energy absorbed by the specimen during the impact process to the total input energy. It is an important indicator to measure the impact resistance of the material. By integrating the force curve, the energy dissipation during the impact process can be calculated. It represents the material property coefficient of the cable specimen, which is used to quantify the influence of material properties on the overall bearing capacity. It specifically reflects the hardness, ductility and energy absorption capacity of the material.

[0119] See also Figure 4 , the structure diagram of the data analysis model of the embodiment of the present invention, the design purpose of the data analysis model is to comprehensively extract the force characteristics of the cable specimen under low-speed impact conditions through hierarchical multi-dimensional data processing means. The entire model consists of three main layers: parameter extraction layer, parameter clustering layer and modal decomposition layer. Each layer undertakes different analysis tasks and gradually converts the force data of the specimen into characteristic parameters that can be used to evaluate the anchoring performance. The data analysis model includes:

[0120] The parameter extraction layer is used to perform multi-dimensional parameter decomposition on the stress data of the cable specimen and convert the original stress data from the time domain to the wavelet domain and the principal component domain. The wavelet domain is used to extract the transient characteristics and detailed changes in the data, while the principal component domain is used to extract the main trends and patterns in the data.

[0121] Through wavelet transform decomposition, the original force data can be decomposed into sub-bands of different frequencies and times, revealing the impact response of the specimen at different time points. At the same time, principal component analysis (PCA) is used to extract the principal components of the data, reduce the dimension, retain the most important data information, and reduce the computational complexity;

[0122] Through the combination of wavelet transform and principal component analysis, the parameter extraction layer can accurately extract the core factors that affect the stress characteristics of the specimen, ensuring the accuracy of subsequent cluster analysis and modal decomposition. At the same time, the dimensionality reduction of the data greatly improves the analysis efficiency;

[0123] The parameter clustering layer divides the force data under different impact conditions into characteristic clusters based on the original force data in the wavelet domain and the principal component domain through a clustering algorithm, calculates the clustering results based on the characteristic clusters, and identifies the groups of specimens that exhibit similar force characteristics under the same impact conditions;

[0124] Performing preliminary clustering on the data in the principal component domain according to the DBSCAN clustering algorithm to obtain core points, and determining the number of cluster center clusters according to the number of core points;

[0125] In this step, first obtain the data of the principal component domain. The data of the principal component domain forms multiple functional element data points. The core of DBSCAN is to cluster based on the density of data points, without predefining the number of clusters. By setting the minimum number of points (MinPts) and the radius parameter (Eps), the DBSCAN algorithm can find high-density areas as cluster centers, while sparse data points are marked as noise points. The purpose of this step is to extract high-density areas (i.e., core points) from the demand description. The number of core points directly determines the number of initial cluster center clusters of the subsequent K-means algorithm;

[0126] The core points after DBSCAN clustering are used as the initial center clusters of the K-means clustering algorithm, and the Euclidean distance from the wavelet domain data to each of the initial center clusters is calculated;

[0127] K-means algorithm is a distance-based partitioning clustering algorithm. The core idea is to optimize the clustering effect by minimizing the distance within the cluster. Each wavelet domain data will be assigned to the cluster center closest to it.

[0128] Perform clustering according to the Euclidean distance, calculate the average clustering error of the initial central cluster, and update the central cluster according to the average clustering error;

[0129] Define a convergence condition, determine whether the updated center cluster meets the convergence condition, if not, continue to update the center cluster, if it meets the convergence condition, output the clustering result;

[0130] The optimal division of functional elements is ensured by iteratively updating the cluster center and calculating the error. In the K-means algorithm, the convergence condition is a common judgment criterion, that is, the change in the position of the cluster center or the error of the distance within the cluster no longer decreases significantly. After setting the convergence condition, the algorithm terminates and outputs the final module group for system architecture design;

[0131] Specifically, by combining the two clustering algorithms, DBSCAN and K-means, cluster analysis is performed on the data, and more accurate clustering results are obtained by iteratively optimizing the central cluster. DBSCAN is a density clustering algorithm used to identify closely connected data points in space and divide them into clusters. DBSCAN can be used for preliminary clustering to obtain core points. Core points refer to the core area containing at least a specified number of data points within a given radius. Since each core point may represent a cluster, the number of core points can be used to preliminarily determine the number of central clusters of clustering. Through cluster analysis, cable specimens with similar stress characteristics can be identified and grouped. Such clustering results facilitate the subsequent analysis of characteristic modes and simplify the complexity of modal decomposition. Clustering also helps to identify the distribution law of stress characteristics under different impact conditions, which facilitates engineering designers to optimize the specimen structure in a targeted manner.

[0132] The modal decomposition layer is used to apply the modal decomposition technique to the clustering results. The purpose of modal decomposition is to determine the natural frequency and damping ratio of the structure under different impact conditions. The natural frequency represents the inherent vibration characteristics of the structure, while the damping ratio describes the attenuation rate of the vibration. Through modal decomposition, the vibration mode of the cable under impact can be determined, thereby evaluating the stability of the anchoring structure. For example, the spectrum peak obtained by FFT analysis in the frequency domain can be used to calculate the natural frequency; and the damping ratio can be obtained by exponential fitting of the vibration attenuation curve, extracting the characteristic mode of the anchoring structure, and analyzing the spectrum response of the characteristic mode to obtain the natural frequency, damping ratio and modal shape of the cable specimen under different modes;

[0133] Use modal analysis methods such as eigenvalue decomposition and spectrum analysis to specifically extract the modal frequency and damping ratio of each characteristic cluster. For example, use singular value decomposition (SVD) to determine the characteristic frequency of each mode, and combine spectrum analysis to obtain the spectrum response of each mode under different impact conditions. The damping ratio is calculated through curve fitting in the time domain or frequency domain to measure the vibration attenuation ability of the specimen under different modes;

[0134] The calculation formula of the anchoring performance is:

[0135] ;

[0136] in, represents the anchoring performance of the cable specimen, n represents a single characteristic mode of the anchoring structure, N represents the total number of characteristic modes of the anchoring structure, represents the stiffness coefficient of the nth eigenmode, represents the mode shape function of the nth eigenmode, represents the damping ratio of the nth eigenmode, represents the natural frequency of the nth characteristic mode, t represents the response time after the impact, represents the cosine function, represents the damping coefficient of the nth eigenmode, It represents the time rate of change of the nth characteristic mode shape, which is used to reflect the instantaneous velocity effect;

[0137] The purpose of the quantitative relationship model is to quantitatively score the comprehensive performance of the cable specimen based on its maximum load and anchoring performance, and optimize the design parameters through the optimization algorithm. The model consists of three main levels: parameter coupling layer, target optimization layer and feedback adjustment layer. Each level has different tasks and gradually conducts comprehensive analysis, optimization and adjustment of the performance of the specimen. The quantitative relationship model includes:

[0138] The parameter coupling layer is used to couple the two key performance indicators of the cable specimen, the maximum load and anchoring performance, to calculate the comprehensive performance score of the specimen. The maximum load reflects the bearing capacity of the specimen under impact load, while the anchoring performance characterizes the stability and fatigue resistance of the cable connection structure.

[0139] The maximum load and anchoring performance are quantitatively combined through a weighted algorithm to generate a comprehensive performance score. The weight coefficient is adjusted according to the specific application scenario and performance requirements to balance the load-bearing capacity and anchoring stability. For example, in applications with high impact resistance requirements, the weight of the maximum load can be increased, while in applications that focus on long-term stability, the weight of the anchoring performance can be increased;

[0140] A target optimization layer, which optimizes the design parameters of the cable specimen and its anchoring structure through an optimization algorithm according to the comprehensive performance score, wherein the optimization includes maximizing the impact strength of the structure, minimizing material consumption and weight, and extending fatigue life;

[0141] The optimization algorithm specifically includes:

[0142] defining an objective function that comprehensively considers the impact strength, material consumption and weight, and fatigue life of the cable and its anchoring structure;

[0143] The design parameter set is iteratively optimized through selection, crossover and mutation operations; the selection operation selects the design solution with higher fitness based on the comprehensive performance score, the crossover operation is used to generate new design solutions, and the mutation operation is used to make small adjustments to the design parameters to increase the diversity of solutions;

[0144] Physical and engineering constraints are imposed on the design parameter set of the cables and their anchorage structures. The constraints include:

[0145] Impact strength constraint ensures that the cable does not break under the maximum impact force;

[0146] Material and weight constraints, which limit the type, density, and overall weight of the selected materials;

[0147] Fatigue life constraints ensure that the cables maintain structural integrity within the designed number of fatigue cycles; the constraints are introduced into the objective function in the form of penalty functions to adjust the fitness score;

[0148] In each iteration, the algorithm generates a new set of design parameters based on the comprehensive performance score and verifies its performance through simulation or experiment. This process ensures that the optimization result achieves the best balance between multiple objectives;

[0149] Feedback adjustment layer, which verifies and adjusts the optimized design parameters through a closed-loop feedback mechanism, and adjusts the objective function of the optimization algorithm based on the verification results;

[0150] After each optimization, the optimization effect is verified through experiments or simulation results, and the deviation data is fed back to the optimization algorithm to adjust the parameter settings and weights of the objective function. The feedback mechanism enables the model to continuously self-correct, thereby gradually converging to the optimal design solution.

[0151] Example 2

[0152] See also Figure 5 , the present invention provides an embodiment: a cable specimen performance evaluation system under low-speed impact conditions, the system comprising a data acquisition module, a performance analysis module and a design optimization module;

[0153] The data acquisition module simulates the low-speed impact conditions in the actual environment through the drop hammer impact test to collect the force and displacement data of the cable specimen;

[0154] The performance analysis module is provided with a force data analysis strategy, which is used to perform multi-dimensional performance analysis on the output of the data acquisition module and calculate the maximum load and anchoring performance of the cable specimen;

[0155] The design optimization module applies the results of the performance analysis to the design optimization of the cable specimen and the anchoring structure based on the quantitative relationship model, and adjusts the design parameters through the optimization algorithm to maximize the impact strength, reduce the weight and improve the fatigue life.

[0156] The performance analysis module comprises:

[0157] A data preprocessing unit, used to preprocess the force and displacement data output by the data acquisition module, and perform denoising, filtering and standardization operations;

[0158] The maximum load analysis unit identifies and extracts the peak load-bearing capacity of the cable specimen under impact through time series analysis and segmented fitting of the force data, and obtains the ultimate load-bearing capacity of the cable specimen by combining the frequency response and energy absorption characteristics;

[0159] Anchor performance evaluation unit, which evaluates the stability and bearing capacity of the anchor structure under impact loads through modal analysis and dynamic response analysis methods;

[0160] The force data analysis strategy includes dynamic response extraction logic and modal feature analysis logic;

[0161] The dynamic response extraction logic is configured in the maximum load analysis unit and is used to extract dynamic response features from the time series;

[0162] The modal characteristic analysis logic is configured in the anchoring performance evaluation unit and is used to decompose the modal characteristics of the anchoring structure, including natural frequency, damping ratio and modal shape.

[0163] Although the embodiments of the present invention have been shown and described above, it is to be understood that the above embodiments are exemplary and are not to be construed as limitations of the present invention. A person skilled in the art may change, modify, replace and vary the above embodiments within the scope of the present invention.

Claims

1. A method for evaluating the performance of cable specimens under low-speed impact conditions, characterized in that: The method comprises: The cable specimens are tested by a drop hammer impact test to obtain the stress data of the cable specimens under different impact conditions; Analyzing the force data to calculate the maximum load of the cable specimen; Constructing a data analysis model, analyzing the stability and bearing capacity of the anchoring structure of the cable specimen through the data analysis model, and calculating the anchoring performance of the cable specimen; A quantitative relationship model is established according to the maximum load and the anchoring performance, and the design parameters of the cable and its anchoring structure are optimized according to the quantitative relationship model.

2. The method for evaluating cable specimen performance under low-speed impact conditions according to claim 1, characterized in that: The drop weight impact test is performed on the cable specimen by using a drop weight impact test device, and the drop weight impact test device comprises: The drop weight assembly is arranged directly above the cable specimen and is used to release from a preset height to generate an impact force, simulating the low-speed impact that occurs in the actual environment; The semi-cylindrical hammer head is installed at the end of the drop hammer, which can evenly transfer the impact force of the drop hammer to the surface of the cable specimen to ensure the stability and uniformity of the impact effect; The cable specimen fixing system includes steel plates, fixing devices and support columns arranged at both ends of the cable specimen to ensure that the cable specimen does not produce lateral displacement during the impact process; The force sensor is installed near the impact area to measure the instantaneous impact force on the cable specimen during the impact process and transmit the instantaneous impact force to the data acquisition system; The displacement sensor is installed at the key position of the cable specimen to record the displacement change of the cable during the impact process in real time to obtain the deformation situation; The data acquisition system is connected to the force sensor and displacement sensor to collect and store the force and displacement data collected during the test.

3. The method for evaluating cable specimen performance under low-speed impact conditions according to claim 1, characterized in that: The analyzing the force data comprises: Connecting the force data to generate a force curve based on a time series, and extracting key dynamic response points according to the force curve; Dividing the stress curve into a buffer section, a load-bearing section, a decay section and a recovery section according to the key dynamic response points; Performing adaptive polynomial segmented fitting on the force curves corresponding to the buffer section, the load-bearing section, the attenuation section and the recovery section, respectively, to generate a fitting curve that satisfies the force characteristics of each stage; According to the fitting curve, a hierarchical grey correlation analysis model is constructed, and the grey correlation parameters of each stage are calculated by the hierarchical grey correlation analysis model. The initial buffering capacity, peak bearing capacity, energy absorption efficiency and residual strength recovery force of the cable specimen are calculated according to the grey correlation parameters.

4. The method for evaluating cable specimen performance under low-speed impact conditions according to claim 3, characterized in that: The hierarchical grey relational analysis model comprises: Map the fitting curves of each stage into the grey relational space, compare the fitting curves of each stage with the ideal curve, and calculate the difference sequence; Calculate dynamic weights according to the stages corresponding to the difference sequence, assign the dynamic weights to the difference sequence, and obtain grey relational parameters, wherein the grey relational parameters include nonlinear adjustment factors, and the nonlinear adjustment factors include nonlinear response and geometric characteristics of the cable specimen; According to the grey correlation parameters of each stage, a correlation difference matrix between stages is constructed, and according to the grey correlation parameters and the correlation difference matrix, the initial buffering capacity, peak bearing capacity, energy absorption efficiency and residual strength recovery force of the cable specimen are calculated.

5. The method for evaluating cable specimen performance under low-speed impact conditions according to claim 4, characterized in that: The calculation of the maximum load of the cable specimen includes: The parameters of initial buffering capacity, peak load-bearing capacity, energy absorption efficiency and residual strength recovery were standardized; The normalized parameters are combined by weighted averaging to calculate the dynamic response index; According to the frequency response of the cable specimen under different impact conditions, the residual strength restoring force is subjected to Fourier transformation to calculate the nonlinear recovery coefficient; The maximum load of the cable specimen is calculated according to the dynamic response index and the nonlinear recovery coefficient.

6. The method for evaluating cable specimen performance under low-speed impact conditions according to claim 1, characterized in that: The data analysis model comprises: The parameter extraction layer is used to perform multi-dimensional parameter decomposition on the force data of the cable specimen and convert the original force data from the time domain to the wavelet domain and the principal component domain; The parameter clustering layer divides the force data under different impact conditions into characteristic clusters based on the original force data in the wavelet domain and the principal component domain through a clustering algorithm, and calculates the clustering results based on the characteristic clusters; The modal decomposition layer is used to apply the modal decomposition technology to the clustering results, extract the characteristic modes of the anchoring structure, analyze the spectral response of the characteristic modes, obtain the natural frequency, damping ratio and modal shape of the cable specimen in different modes, and calculate the anchoring performance based on the natural frequency, damping ratio and modal shape.

7. The method for evaluating cable specimen performance under low-speed impact conditions according to claim 1, characterized in that: The quantitative relationship model includes: The parameter coupling layer is used to couple the maximum load and anchoring performance of the cable specimen and calculate the comprehensive performance score; The target optimization layer optimizes the design parameters of the cable specimen and its anchoring structure through an optimization algorithm according to the comprehensive performance score; The feedback adjustment layer verifies and adjusts the optimized design parameters through a closed-loop feedback mechanism, and adjusts the objective function of the optimization algorithm based on the verification results.

8. The method for evaluating cable specimen performance under low-speed impact conditions according to claim 7, characterized in that: The optimization of the design parameters of the cable specimen and its anchoring structure includes: Maximize the impact strength of the structure; Minimize material consumption and weight; Extend fatigue life.

9. A cable specimen performance evaluation system under low-speed impact conditions, used to implement the cable specimen performance evaluation method under low-speed impact conditions as claimed in any one of claims 1 to 8, characterized in that: The system includes a data acquisition module, a performance analysis module and a design optimization module; The data acquisition module simulates the low-speed impact conditions in the actual environment through the drop hammer impact test to collect the force and displacement data of the cable specimen; The performance analysis module is provided with a force data analysis strategy, which is used to perform multi-dimensional performance analysis on the output of the data acquisition module and calculate the maximum load and anchoring performance of the cable specimen; The design optimization module applies the results of the performance analysis to the design optimization of the cable specimen and the anchoring structure based on the quantitative relationship model, and adjusts the design parameters through the optimization algorithm to maximize the impact strength, reduce the weight and improve the fatigue life.

10. The cable specimen performance evaluation system under low-speed impact conditions according to claim 9, characterized in that: The performance analysis module comprises: A data preprocessing unit, used to preprocess the force and displacement data output by the data acquisition module, and perform denoising, filtering and standardization operations; The maximum load analysis unit identifies and extracts the peak load-bearing capacity of the cable specimen under impact through time series analysis and segmented fitting of the force data, and obtains the ultimate load-bearing capacity of the cable specimen by combining the frequency response and energy absorption characteristics; Anchor performance evaluation unit, which evaluates the stability and bearing capacity of the anchor structure under impact loads through modal analysis and dynamic response analysis methods; The force data analysis strategy includes dynamic response extraction logic and modal feature analysis logic; The dynamic response extraction logic is configured in the maximum load analysis unit and is used to extract dynamic response features from the time series; The modal characteristic analysis logic is configured in the anchoring performance evaluation unit and is used to decompose the modal characteristics of the anchoring structure, including natural frequency, damping ratio and modal shape.

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