A method and device for testing the wear resistance of socks for sports performance

Abstract

The present invention discloses a method and device for testing the wear resistance of socks during exercise, and relates to the technical field of sock wear resistance detection. The method and device for testing the wear resistance of socks during exercise include the following steps: S1, collecting user parameters and gait parameters of different exercise types, constructing a gait model, calculating a pressure distribution evaluation value, and performing data preprocessing; S2, installing socks made of new materials, using the rhythm control of different exercise modes to reproduce the force path and friction environment of the socks under real exercise conditions, and synchronously recording the friction force, sliding trajectory, and local shearing conditions to form a wear trajectory; S3, acquiring an image of the sock sole, performing visual recognition and wear area extraction, and outputting a quantitative wear index; S4, evaluating the wear resistance of socks made of new materials, performing adaptability matching analysis, taking optimization measures, and outputting an evaluation report. This method solves the problem that sock wear is difficult to test because different exercise types have completely different gait cycles and movement postures.

Description

Technical Field

[0001] The present invention relates to the technical field of socks wear resistance detection, in particular to a method and device for testing the sports wear resistance of socks. Background Art

[0002] Socks, as frequently worn items close to the skin, have a wear resistance that directly impacts comfort, longevity, and athletic performance. Currently, standard test methods for assessing fabric abrasion resistance are widely available. These methods primarily assess fabric durability by simulating repeated friction between the fabric and a standard abrasive surface. While these methods have some value in the general evaluation of apparel materials, they are significantly inadequate for functional textiles like socks, which are subject to dynamic fit, multi-directional loads, and complex stress fields.

[0003] These methods are unable to reproduce the human gait rhythm, regional force changes, and shear slip processes under different types of movement, resulting in a disconnect between test results and actual usage scenarios. Furthermore, traditional testing methods struggle to capture the matching relationship between wear areas and stress areas, making it impossible to determine whether the sock structure is properly designed, and can easily miss potential functional area failure risks. Furthermore, current test indicators are generally single, lacking integrated analysis of dynamic parameters such as cadence, contact area, and pressure intensity, making it difficult to achieve systematic modeling and evaluation of the relationship between material properties, structural characteristics, and wear behavior.

[0004] Therefore, in view of the above problems, a method and device for testing the wear resistance of socks for sports performance are urgently needed. Summary of the Invention

[0005] Technical problems solved

[0006] In response to the shortcomings of the existing technology, the present invention provides a method and device for testing the wear resistance of socks during sports, which solves the problem that sock wear is difficult to test because different sports types have completely different gait cycles and movement postures.

[0007] Technical solution. To achieve the above objectives, the present invention is implemented through the following technical solution: a method and device for testing the wear resistance of socks in terms of sports performance, comprising the following steps: S1, collecting user parameters and gait parameters of different sports types, and constructing a gait model, calculating the pressure distribution evaluation value based on the user parameters and gait parameters, and performing data preprocessing; S2, installing socks made of new materials, using the rhythm control of different sports patterns to reproduce the force path and friction environment of the socks under real sports conditions, and synchronously recording the friction force, sliding trajectory and local shearing conditions through multiple sensors to form a wear trajectory; S3, obtaining an image of the sock sole, performing visual recognition and wear area extraction, and outputting a quantitative wear index; S4, integrating test data and wear results to evaluate the wear resistance of socks made of new materials, performing adaptability matching analysis, and taking optimization measures based on the adaptability evaluation value, and outputting an evaluation report.

[0008] Furthermore, the wearer's user parameters are collected, including: height, weight, gender, foot shape and plantar area size. Standard gait parameters are extracted according to different movement types, including: step frequency data, single step duration, landing lead position and force time ratio. The user parameters and gait parameters are normalized; the gait parameters are converted into control signals by using a controller, and the foot model realizes landing and pushing actions through the front and rear driving actuators, and the ankle angle adjustment machine adjusts the landing angle. The inertial measurement unit sensor measurement module and the displacement encoder are respectively arranged on the bottom of the foot model and the ankle joint to realize a highly simulated gait dynamic simulation cycle.

[0009] Furthermore, the pressure distribution evaluation value is calculated based on the user parameters and gait parameters, and the specific process of data preprocessing is as follows: obtaining the wearer's weight, monitoring the periodic oscillation through the inertial measurement unit sensor of the foot model to obtain the cadence data, obtaining the regional relative phase according to the landing leading position of the standard gait parameters, obtaining the force area of the i-th region of the sole by measuring the contact area through the flexible pressure sensing pad, and normalizing the force area; multiplying the wearer's weight by the gravity-to-pressure constant to obtain the total pressure value, multiplying the cadence data, twice the pi and the current time to obtain the angle value in the current gait cycle, adding the relative phase of the i-th sole area to the angle value to obtain the total phase angle value, calculating the cosine function of the total phase angle value, multiplying the cosine function calculation result by the landing impact weight factor plus the constant one, and then multiplying the addition result by the ratio of the force area of the i-th region and the total pressure value to obtain the pressure distribution evaluation value; the pressure value, angle value and displacement data are low-pass filtered to eliminate high-frequency noise, standardized and normalized, and synchronized with the time axis.

[0010] Furthermore, new material socks are installed, and the force path and friction environment of the socks under real movement conditions are reproduced by using the rhythm control of different movement patterns. The friction force, sliding trajectory and local shearing conditions are recorded synchronously by multiple sensors to form the wear trajectory. The specific process is as follows: the new material socks to be tested are installed on the surface of the foot model according to the standard process, and the tensile tester is used for tensioning. The initial length, width and position of the key force area are recorded, and the initial state images of the socks from multiple angles are taken, including the front view, the sole view and the arch close-up, and stored in the sample database; the gait trajectory is called according to the set movement mode, and the foot model is driven by the control system. Periodic bionic motion is performed under the foot model to achieve dynamic simulation of different scenarios, and the multi-directional load combination of friction, compression and tension is further established between the bottom of the foot model and the test table. During the test, the flexible pressure sensing pad is used to collect the force data of each area of the sock sole in real time, and the inertial measurement unit sensor module and the friction coefficient sensor are used to synchronously obtain the shear impact characteristics and foot trajectory changes. The bottom friction tensiometer is used to monitor the friction force changes, and the laser displacement meter is used to reconstruct the slip trajectory. The force data collected during the test are cached through a unified timestamp alignment mechanism, and undergo filtering, normalization and outlier elimination steps.

[0011] Furthermore, the specific process of obtaining the sock sole image and performing visual recognition and wear area extraction is as follows: after the motion simulation test is completed, the socks on the foot model are removed and flattened in a standard manner. The flattened areas are numbered with reference to the distribution of the sole area, and the sock sole image is obtained using a high-resolution platform. The shooting methods include standard vertical projection images and oblique side lighting images to enhance the clarity of recognition of broken threads, holes, and discoloration; after the image is acquired, the sock sole image is automatically subjected to wear image recognition analysis, image grayscale and background removal are performed, and the potential wear edges are located using an edge detection algorithm. In the cleaned image, the key attributes of the wear area, including the total length of the broken thread, the hole diameter, and the local color spot area index, are identified through regional connectivity analysis and morphological feature extraction methods, and a structured sock sole wear map is output based on the initial state image taken.

[0012] Furthermore, the specific process of outputting the quantitative wear index is as follows: the wear area ratio is output through the ratio of the damaged area area to the total sock sole area, and the broken line density is obtained through the number of broken lines per unit area; for each area i divided by the sock sole, the wear area of the i-th area is obtained by wear image recognition and the wear area is normalized, the average pressure distribution evaluation value is used to average the time integral to obtain the average pressure of the i-th area, and the maximum average pressure of all areas is screened out, the average pressure of the i-th area is divided by the maximum average pressure of all areas in the test to obtain the relative pressure intensity ratio of the area, the pressure distribution evaluation value of each area is compared with the average pressure threshold, and the high pressure duration of the area is obtained by using sensor data, and the high pressure exposure ratio of the area is obtained by the ratio of the high pressure duration to the total test time, the relative pressure intensity ratio is weighted by the pressure response weight factor in the form of an exponential to obtain a pressure intensity index term, the time exposure weight factor is weighted by the high pressure exposure ratio in the form of an exponential to obtain a high pressure time index term, and the pressure intensity The index term is multiplied by the high-pressure time index term and multiplied by the wear area and regional structure weight factor of the area to obtain the fatigue matching contribution value of the area. The fatigue matching contribution values of all areas are summed and divided by the sum of the products of all wear areas and regional structure weight factors to obtain the fatigue concentration assessment value; the fatigue concentration assessment value is compared with the fatigue concentration threshold in real time. When the fatigue concentration assessment value is greater than or equal to the fatigue concentration threshold, the sock wear is judged to be reasonably concentrated and automatically archived to the qualified sample library. It is recommended for use in the specified sport type and selected as a performance example, which appears on the summary page of the final report; when the fatigue concentration assessment value is less than the fatigue concentration threshold, the sock wear drift is judged, and the area with significant wear but insufficient pressure loading is automatically located, the structure and force mismatch area are identified, and a local structure reconstruction suggestion is generated. The stress type is inferred based on the wear characteristics, and a prompt is sent to replace high-wear-resistant and cushioning materials. The sock sample is automatically marked as a structural optimization to be verified. After adjustment, the test verification process is reloaded and the current test data is retained as a preliminary reference version.

[0013] Furthermore, the specific process of integrating test data and wear results to evaluate the wear resistance of new material socks is as follows: integrating user parameters, gait parameters and multi-dimensional data of wear results obtained from the test to construct characteristic variables, including the wear rate under unit pressure and the gait peak and wear alignment index; calculating the pressure distribution evaluation value of each area, and performing time integration operation to obtain the cumulative total force during the test cycle, and adding up the cumulative total force of all areas; obtaining the wear area of each area through wear image recognition and summing them to obtain the total wear of the entire sock, and dividing the cumulative total force of all areas by the total wear to obtain the unit wear evaluation value; comparing the unit wear evaluation value with the unit wear threshold in real time. When the unit wear evaluation value is less than the unit wear threshold, it is determined that the socks have insufficient material wear resistance and it is recommended to replace them with high-strength fabrics. It is recommended to adopt zoned differentiated reinforcement and linkage structural modeling to analyze whether the material strength matches the stress area to avoid high-pressure accumulation in weak material areas; when the unit wear evaluation value is greater than or equal to the unit wear threshold, it is determined that the material performance is stable and it is included in the qualified wear resistance sample set and recommended for use in high-load or long-term exercise scenarios.

[0014] Furthermore, the specific process of conducting adaptability matching analysis is as follows: compare the test wear results of the sock samples under different motion modes and output the adaptability matching results; obtain the unit wear assessment value and fatigue concentration assessment value of the sock sample, calculate the standard deviation and mean of the wear area of all regions of the sock sole based on wear image recognition, subtract the unit wear assessment value from the constant one and multiply it by the wear resistance assessment weight factor to obtain the wear resistance assessment item, multiply the fatigue concentration assessment value by the structural rationality weight factor to obtain the structural rationality assessment item, subtract the ratio of the standard deviation of the wear area to the mean from the constant one and multiply it by the wear distribution weight factor to obtain the wear uniformity assessment item, and sum the wear resistance assessment item, structural rationality assessment item and wear uniformity assessment item to obtain the adaptability assessment value.

[0015] Furthermore, optimization measures are taken according to the adaptability evaluation value. The specific process of outputting the evaluation report is as follows: real-time comparison of the adaptability evaluation value and the adaptability threshold. When the adaptability evaluation value is greater than or equal to the adaptability threshold, it is judged as "well-adapted"; published in the product visualization report as an example of high adaptability performance; continued large-scale intensity testing or multi-scenario expansion testing is allowed; a complete test report is generated for publicity and internal evaluation; when the adaptability evaluation value is less than the adaptability threshold, it is judged as "adaptability to be optimized"; based on the components of the adaptability evaluation value, the source of the performance bottleneck is automatically identified. , and puts forward targeted optimization suggestions from three aspects: material selection, structural layout and test configuration; after the optimization plan is adjusted by design, it triggers a new round of simulated gait loading process, re-evaluates wear and performance scoring, and realizes closed-loop feedback control of product iteration and upgrade; automatically integrates key parameters and evaluation results of the whole process, and outputs a structured, visual standardized test report, including test parameters, sock images, wear images, and scoring suggestions, including the output of the most suitable population type and the most suitable sports scene for socks made of this new material, and supports the prediction of the expected life of socks under different sports rhythms and populations.

[0016] Furthermore, it includes a data acquisition and preprocessing module, a dynamic loading and wear simulation module, a wear detection and intelligent evaluation module, and a loss modeling and motion scene adaptation analysis module: the data acquisition and preprocessing module is used to collect user parameters and gait parameters of different motion types, and construct a gait model, calculate the pressure distribution evaluation value according to the user parameters and gait parameters, and perform data preprocessing; the dynamic loading and wear simulation module is used to install new material socks, use the rhythm control of different motion patterns to reproduce the force path and friction environment of the socks under real motion conditions, and synchronously record the friction force, slip trajectory and local shear conditions through multiple sensors to form a wear trajectory; the wear detection and intelligent evaluation module is used to obtain the sock sole image, perform visual recognition and wear area extraction, and output quantitative wear indicators; the loss modeling and motion scene adaptation analysis module is used to integrate simulation parameters and wear results to evaluate the wear resistance of new material socks, perform adaptability matching analysis, take optimization measures according to the adaptability evaluation value, and output an evaluation report.

[0017] Beneficial effects

[0018] The present invention has the following beneficial effects:

[0019] (1) This invention combines user parameters with movement types to construct a parameter-driven simulation gait control model, and uses a foot model for dynamic loading to achieve a highly realistic gait dynamic cycle. This model breaks through the limitations of traditional homogeneous load test models that cannot distinguish individual differences and movement characteristics, and can more realistically reproduce the friction and shear path that socks experience in actual movement scenarios.

[0020] (2) This invention establishes pressure distribution assessment values for different areas of the sock sole and, combined with features such as broken lines, holes, and color spots in the wear image, calculates the wear area and force matching of each area, thereby obtaining a fatigue concentration assessment value. This is used to measure the consistency and structural rationality of the sock's wear area and force concentration area. This mechanism can quantify whether wear is concentrated in high-pressure areas and achieve a refined diagnosis of whether the structural rationality and regional functional configuration match. It is a pioneering fatigue-wear coupling analysis method.

[0021] (3) The present invention proposes a compatibility evaluation value that comprehensively reflects the material's load-bearing capacity, structural partitioning rationality, and wear distribution balance, effectively determining the compatibility of new material socks for specific sports scenarios and population types. This scoring mechanism breaks through the traditional single "total wear" or "number of cycles" evaluation model and has significant data interpretation power and engineering guidance significance.

[0022] (4) Based on fatigue concentration values, unit wear values, and adaptability assessment values, the present invention's system can automatically identify wear drift areas and risks of insufficient material wear resistance, generate local structural optimization suggestions and material replacement prompts, and trigger a new round of loading tests, thus achieving a closed-loop feedback process of product testing-analysis-adjustment-retesting. This mechanism greatly improves the adaptability and development accuracy of new material socks in multiple scenarios, and promotes the intelligent evaluation and adaptive optimization of socks into a new stage.

[0023] Of course, any product implementing the present invention does not necessarily need to achieve all of the advantages described above at the same time. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] Figure 1 This is a flow chart of a method for testing the wear resistance of athletic socks;

[0025] Figure 2 Module connection diagram of a socks sports wear resistance test device

[0026] Figure 3 A bar graph showing the fit evaluation values of a method and device for testing the wear resistance of athletic socks; DETAILED DESCRIPTION

[0027] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0028] See also Figure 1-Figure 3, an embodiment of the present invention provides a technical solution: a method and device for testing the wear resistance of socks in terms of sports performance, comprising the following steps: S1, collecting user parameters and gait parameters of different sports types, and constructing a gait model, calculating a pressure distribution evaluation value based on the user parameters and gait parameters, and performing data preprocessing; S2, installing socks made of new materials, using the rhythm control of different sports patterns to reproduce the force path and friction environment of the socks under real sports conditions, and synchronously recording friction, sliding trajectory and local shear conditions through multiple sensors to form a wear trajectory; S3, acquiring an image of the sock sole, performing visual recognition and wear area extraction, and outputting a quantitative wear index; S4, integrating the test data and wear results to evaluate the wear resistance of the socks made of new materials, performing adaptability matching analysis, taking optimization measures based on the adaptability evaluation value, and outputting an evaluation report.

[0029] Specifically, the process of collecting user parameters and gait parameters of different motion types and constructing a gait model is as follows: collecting the wearer's user parameters, including height, weight, gender, foot shape and plantar area size; extracting standard gait parameters according to different motion types, including cadence data, single-step duration, landing lead position and force time ratio; normalizing the user parameters and gait parameters. This process enables the test system to accurately model individual differences and motion characteristics, enhancing the adaptability and restoration of motion scene simulation; using a controller to convert gait parameters into control signals, the foot model realizes landing and pushing movements through front and rear drive actuators, and the ankle angle adjustment machine adjusts the landing angle, effectively restoring foot motion states such as inversion, eversion and flatfoot, and improving the authenticity of gait simulation; inertial measurement unit sensor measurement modules and displacement encoders are respectively arranged at the bottom and ankle joint of the foot model, which can realize high-precision synchronous acquisition of foot trajectory and posture changes, ensuring that the simulated movements are controllable and traceable, thereby realizing a highly simulated gait dynamic simulation cycle, providing a physical basis for subsequent dynamic load loading and wear behavior tracking.

[0030] In this implementation, by collecting individual user parameters and movement type gait characteristics, a highly personalized gait control model is constructed, enabling the system to accurately adapt to the foot structure and movement behavior of different people, significantly improving the simulation accuracy and applicability of the test scenario; using drive actuators and angle adjustment devices to realistically restore dynamic postures such as inversion, eversion and flatfoot, the physical fit of the bionic simulation is improved; at the same time, the inertial measurement unit and displacement encoder achieve high-precision synchronous acquisition of foot trajectory and posture changes, ensuring the controllability and traceability of the test process, and providing stable and reliable raw data support for dynamic loading control and wear cause analysis, thereby enhancing the system's ability to truly evaluate the wear resistance of socks under complex motion conditions.

[0031] Specifically, the pressure distribution evaluation value is calculated based on the user parameters and gait parameters, and the specific process of data preprocessing is as follows: obtain the wearer's weight, monitor the periodic oscillation through the inertial measurement unit sensor of the foot model to obtain the cadence data, obtain the regional relative phase according to the landing leading position of the standard gait parameters, obtain the force area of the i-th region of the sole by measuring the contact area through the flexible pressure sensing pad, and normalize the force area; multiply the wearer's weight by the gravity-to-pressure constant to obtain the total pressure value, multiply the cadence data, twice the pi and the current time to obtain the angle value in the current gait cycle, add the relative phase of the i-th sole area to the angle value to obtain the total phase angle value, calculate the cosine function of the total phase angle value, multiply the result of the cosine function calculation by the landing impact weight factor plus the constant one, and then multiply the summation result by the ratio of the force area of the i-th region and the total pressure value to obtain the pressure distribution evaluation value; the pressure value, angle value and displacement data are low-pass filtered to eliminate high-frequency noise, and are standardized and normalized, and time axis synchronization is performed.

[0032] The specific calculation formula for the pressure distribution evaluation value is:

[0033]

[0034] Where, is the pressure distribution evaluation value of the i-th area of the sole at the current time t, which is used to calculate the unit area pressure of the i-th area of the sole at time t to reflect the dynamic changes of the sole force during a gait cycle; is the gravity-to-pressure constant, which is a fixed value of 9.8 / 1000; The wearer's weight will affect the total force strength of the sole; For cadence data, the inertial measurement unit sensor is used to monitor periodic oscillations and automatically identify them, which can be used to distinguish the rhythm characteristics of jogging, sprinting, jumping, etc. is the relative phase of the region, which is used to describe when different regions are subjected to force in a gait cycle, for example: the forefoot leads and the heel lags, and is usually set to , ; is the force-bearing area of the ith region of the sole; The landing impact weight factor is obtained by collecting vertical acceleration through the inertial measurement unit module, estimating the peak acceleration, and then normalizing it to the relative impact intensity, ranging from 0 to 0.5.

[0035] In this implementation, by integrating multi-dimensional parameters such as user weight, cadence, landing rhythm and plantar structure, a regional pressure distribution assessment model with time dynamics is constructed, which can accurately simulate the actual load changes in various areas of the plantar during different gait cycles; the cadence is extracted using an inertial measurement unit, and a phase-controlled cosine function model is established in combination with the regional relative phase and the measured area of the flexible pressure sensing pad, thereby achieving detailed modeling of pressure fluctuations in different regions; at the same time, data preprocessing mechanisms such as low-pass filtering, standardization and time axis synchronization are introduced to effectively improve data quality and system response stability.

[0036] Specifically, new material socks are installed, and the rhythm control of different motion patterns is used to reproduce the force path and friction environment of the socks under real motion conditions. The friction force, sliding trajectory and local shear conditions are recorded synchronously by multiple sensors to form the specific process of wear trajectory: the new material socks to be tested are installed on the surface of the foot model according to the standard process, and a tensile tester is used for tensioning. The initial length, width and position of the key force area are recorded, and the initial state images of the socks from multiple angles are taken, including the front view, the sole image and the close-up of the arch, which are uniformly stored in the sample database. This process helps to build a standardized before-and-after state comparison system, and improve the subsequent wear identification accuracy and sample traceability; the gait trajectory is called according to the set motion mode, so that the foot model performs periodic bionic motion under the drive of the control system to realize dynamic simulation of different scenes. This gait loading method can truly restore the force rhythm and sliding behavior of the sole under multiple types of motion, and enhance the wear load path. environmental credibility; between the bottom of the foot mold and the test table, the multi-directional load combination of friction, compression and tension is further established, which significantly improves the mechanical multidimensionality of the simulated environment and makes the wear test results more practical, adaptable and reliable; during the test, the flexible pressure sensing pad is used to collect the force data of each area of the sock sole in real time, and the inertial measurement unit sensor module and the friction coefficient sensor are used to synchronously obtain the shear impact characteristics and foot trajectory changes. The bottom friction tensiometer is used to monitor the friction force changes, and the laser displacement meter is used to reconstruct the slip trajectory, so as to realize the full process, multi-channel and high-frequency data synchronization of the wear load behavior, and provide data support for the establishment of the mapping model between the wear mechanism and the load trajectory; the force data collected during the test are cached through a unified timestamp alignment mechanism, and are filtered, normalized and outlier eliminated to ensure the data quality is stable and the structure is complete, which is convenient for subsequent analysis, modeling and decision-making.

[0037] In this implementation plan, wear identification accuracy and sample traceability are improved through standardized installation and initial state recording; based on multi-type motion rhythm control, the real plantar force and sliding path are reproduced, and the test environment restoration is enhanced; the friction-compression-tension joint effect is constructed to improve the multi-dimensional adaptability of the test load; the fusion of multiple sensors realizes the synchronous acquisition of force, friction and trajectory, providing high-quality data support for wear mechanism modeling; unified timestamps and data preprocessing processes ensure that the data structure is stable and reliable, supporting subsequent analysis and optimization.

[0038] Specifically, the specific process of obtaining the sock sole image, performing visual recognition and extracting the wear area is as follows: after the motion simulation test is completed, the socks on the foot model are removed and flattened in a standard way. The flattened areas are numbered with reference to the distribution of the sole area, and the sock sole image is obtained using a high-resolution platform. The shooting methods include standard vertical projection images and oblique side lighting images to enhance the clarity of thread breaks, holes, and color changes. This image acquisition method can improve the image's ability to resolve subtle wear features and enhance the accuracy and stability of subsequent algorithm recognition. After the image is acquired, the sock sole image is automatically subjected to wear image recognition analysis and image grayscale analysis. The system uses edge detection algorithm to locate potential wear edges through degree analysis and background removal, which can effectively eliminate background interference information and extract the true boundary shape of the wear area. In the cleaned image, regional connectivity analysis and morphological feature extraction methods are used to identify the key attributes of the wear area, including the total length of broken lines, hole diameter, and local color spot area indicators, to achieve multi-dimensional quantitative characterization of the wear degree and enhance the evaluation dimension. A structured sock sole wear map is output based on the initial state image taken. This map can be used as an intuitive basis for subsequent fatigue assessment and material structure optimization, improving the interpretability of the results and the efficiency of data reuse.

[0039] In this implementation, high-resolution image acquisition and standard flattening operations are used to improve the recognition capability of subtle wear features of sock soles, such as broken threads, holes, and discoloration, thereby enhancing image clarity and the accuracy and stability of algorithm recognition. Combined with grayscale conversion, background removal, and edge detection algorithms, the true boundaries of the wear area can be accurately extracted, reducing background interference. Through regional connectivity analysis and morphological feature extraction, a multi-dimensional quantitative expression of the degree of wear is achieved, effectively supporting the detailed evaluation of the wear behavior of the sock soles. The final output of the structured wear map strengthens the system's decision-making ability in wear mechanism analysis and material structure optimization.

[0040] Specifically, the specific process of outputting the quantitative wear index is as follows: the wear area ratio is output through the ratio of the damaged area area to the total sock sole area, and the broken line density is obtained through the number of broken lines per unit area; for each area i divided by the sock sole, the wear area of the i-th area is obtained by wear image recognition and the wear area is normalized, the average pressure distribution evaluation value is used to average the time integral to obtain the average pressure of the i-th area, and the maximum average pressure of all areas is screened out, the average pressure of the i-th area is divided by the maximum average pressure of all areas in the test to obtain the relative pressure intensity ratio of the area, the pressure distribution evaluation value of each area is compared with the average pressure threshold, and the high pressure duration of the area is obtained by using sensor data, and the high pressure exposure ratio of the area is obtained by the ratio of the high pressure duration to the total test time, the relative pressure intensity ratio is weighted by the pressure response weight factor in the form of an exponential to obtain a pressure intensity index term, the time exposure weight factor is weighted by the high pressure exposure ratio in the form of an exponential to obtain a high pressure time index term, and the pressure intensity index The number term is multiplied by the high-pressure time index term and multiplied by the wear area and regional structure weight factor of the area to obtain the fatigue matching contribution value of the area. The fatigue matching contribution values of all areas are summed and divided by the sum of the products of all wear areas and regional structure weight factors to obtain the fatigue concentration assessment value; the fatigue concentration assessment value is compared with the fatigue concentration threshold in real time. When the fatigue concentration assessment value is greater than or equal to the fatigue concentration threshold, the sock wear is judged to be reasonably concentrated and automatically archived to the qualified sample library. It is recommended for use in the specified sport type and selected as a performance example, which appears on the summary page of the final report; when the fatigue concentration assessment value is less than the fatigue concentration threshold, the sock wear drift is judged, and the area with significant wear but insufficient pressure loading is automatically located, the structure and force mismatch area are identified, and a local structure reconstruction suggestion is generated. The stress type is inferred based on the wear characteristics, and a prompt is sent to replace high-wear-resistant and cushioning materials. The sock sample is automatically marked as a structural optimization to be verified. After adjustment, the test verification process is reloaded and the current test data is retained as a preliminary reference version.

[0041] The specific calculation formula for fatigue concentration assessment value is:

[0042]

[0043] Where, Fatigue concentration assessment value, a quantitative indicator to measure whether the actual wear distribution of the socks matches its stress pattern; is the wear area of the i-th region of the sole obtained by wear image recognition, which quantitatively reflects the wear intensity of the socks in this area; is the average pressure of the i-th region, indicating the force level of this region of the sock sole; is the maximum average pressure in all regions, which is used to construct the relative pressure ratio; is the high pressure duration of the i-th region in the high pressure state, reflecting the cumulative time that the region is in the high pressure state; is the total test time, which is used to standardize the reference value of high-voltage time so that different test durations can be compared; is the regional structure weight factor, which is obtained by extracting the landing frequency of each region in a complete cycle from the gait parameters and normalizing the proportion of the cumulative pressure of the region to the total load, ranging from 0.05 to 0.6; is the pressure response weight factor, which is obtained by nonlinear fitting based on multiple sets of average pressure and wear area data sets and ranges from 0.8 to 1.5; is the time exposure weighting factor, which is obtained by comparing the high-pressure duration and wear area in multiple regions through bivariate regression fitting and ranges from 0.5 to 1.2.

[0044] In this implementation plan, through image recognition and multi-region partitioning analysis, the multi-dimensional indicators such as the area of sock sole wear, line break density, pressure intensity ratio and high-pressure exposure ratio are accurately quantified, and then a fatigue concentration assessment value is constructed to effectively reflect the consistency between the wear area and the force pattern; this process not only improves the coupling modeling capability between wear behavior and mechanical response, but also can automatically judge the rationality of wear and structural adaptability; based on the evaluation results, abnormal wear areas can be accurately located, and suggestions for high-wear-resistant material replacement and structural reconstruction can be proposed, and a feedback loop can be formed to drive a new round of verification testing, thereby realizing the accurate screening, performance grading and iterative design optimization of sock products.

[0045] Specifically, the specific process of integrating test data and wear results to evaluate the wear resistance of new material socks is as follows: integrating user parameters, gait parameters and multi-dimensional data of wear results tested, constructing characteristic variables, including the wear rate under unit pressure and the gait peak and wear alignment index; calculating the pressure distribution evaluation value of each area, and performing time integration operation to obtain the cumulative total force during the test cycle, and adding up the cumulative total force of all areas; obtaining the wear area of each area through wear image recognition and summing up to obtain the total wear of the socks as a whole, and dividing the cumulative total force of all areas by the total wear to obtain the unit wear evaluation value; comparing the unit wear evaluation value with the unit wear threshold in real time. When the unit wear evaluation value is less than the unit wear threshold, it is determined that the socks have insufficient material wear resistance and it is recommended to replace them with high-strength fabrics. It is recommended to use zoned differentiated reinforcement and linkage structural modeling to analyze whether the material strength matches the stress area to avoid high-pressure accumulation in weak material areas; when the unit wear evaluation value is greater than or equal to the unit wear threshold, it is determined that the material performance is stable and it is included in the qualified wear resistance sample set and recommended for use in high-load or long-term exercise scenarios.

[0046] The specific calculation formula for unit wear assessment value is:

[0047]

[0048] Where, The unit wear assessment value measures the cumulative load that the socks as a whole bear under unit wear; The total number of standard areas divided into the sole of the foot, such as forefoot, arch, heel, etc., for regional statistics; is the i-th area of the plantar at the current time Pressure distribution evaluation value at ; For region i in the test cycle The total cumulative force within is used to express the total load intensity, where Indicates the upper limit of the integration time interval to ensure the time consistency of the force data in each area; is the wear area of the i-th region of the sole obtained by wear image recognition.

[0049] In this implementation, by integrating user parameters, gait data and wear results, a unit wear assessment value is constructed to accurately quantify the wear resistance of the sock material under motion loads; based on threshold comparison, insufficient material strength can be automatically identified, and high-strength fabric replacement and zoning reinforcement suggestions can be made to avoid mismatch in high-pressure areas; when the material performance is stable, it is included in the qualified sample library for high-load motion recommendations, thereby achieving closed-loop control of wear resistance screening and material optimization.

[0050] Specifically, the specific process of adaptability matching analysis is as follows: compare the test wear results of sock samples under different motion modes, and output the adaptability matching results, which helps to reveal the performance stability and adaptability of socks in multiple scenarios; obtain the unit wear assessment value and fatigue concentration assessment value of the sock sample, and calculate the standard deviation and mean of the wear area of all areas of the sock sole based on wear image recognition, which can effectively reflect the uniformity and local concentration of wear distribution, subtract the unit wear assessment value from the constant one and then multiply it by the wear resistance assessment weight factor to obtain the wear resistance assessment item, multiply the fatigue concentration assessment value by the structural rationality weight factor to obtain the structural rationality assessment item, subtract the ratio of the standard deviation and mean of the wear area from the constant one and then multiply it by the wear distribution weight factor to obtain the wear uniformity assessment item, and sum the wear resistance assessment item, structural rationality assessment item and wear uniformity assessment item to obtain the adaptability assessment value.

[0051] The specific calculation formula for the adaptability evaluation value is:

[0052]

[0053] Where, This is the fit evaluation value, which comprehensively measures wear resistance, fatigue concentration, and wear distribution uniformity to facilitate the judgment of whether the socks are suitable for a certain type of sports scene. The higher the value, the more suitable the socks are for that type of sports scene. is the unit wear assessment value, which measures the average cumulative force corresponding to unit wear. The smaller it is, the more wear-resistant the material is; Fatigue concentration evaluation value, which measures whether the stress concentration leads to wear concentration. The higher the value, the better the match, indicating that the structure is consistent with the stress path. is the standard deviation of the wear area in all regions, which measures the dispersion of wear between different regions. A larger value indicates more uneven wear. is the mean of the wear area in all regions; Indicates the distribution consistency of wear. The closer the value is to 1, the more uniform the distribution is. is the wear resistance evaluation weight factor, which is obtained by linear regression fitting of the unit wear evaluation values of multiple groups of sock samples and ranges from 0.3 to 0.5; is the structural rationality weight factor, which is obtained by linear regression fitting through the fatigue concentration evaluation values of several socks with different structural designs, and ranges from 0.3 to 0.5; is the wear distribution weight factor, which is obtained by linear regression fitting the standard deviation and mean of the wear area of multiple groups of socks and ranges from 0.2 to 0.4.

[0054] The wear resistance evaluation weighting factor was set to 0.4, the structural rationality weighting factor was set to 0.35, and the wear distribution weighting factor was set to 0.25. These three weighting factors were kept constant. The fit evaluation value of the socks was calculated under the conditions of varying unit wear evaluation values, fatigue concentration evaluation values, and regional wear area for the new material socks. Table 1 shows the fit evaluation value data.

[0055] Table 1 Adaptability evaluation value data table

[0056]

[0057] like Figure 3 As shown in Table 1 and Figure 3 It can be seen that when the three weight factors remain unchanged and the unit wear assessment value, fatigue concentration assessment value and regional wear area of the new material socks continue to change, different sock samples have different adaptability assessment values.

[0058] In this implementation plan, by comparing the wear performance under different sports modes, the performance adaptability of socks in multiple scenarios is fully revealed; at the same time, the three core indicators of unit wear, fatigue concentration and wear distribution are integrated to construct an adaptability evaluation value, which can accurately reflect the comprehensive characteristics such as material durability, structural matching and wear uniformity; this method not only improves the explanatory power and scientific nature of the evaluation results, but also provides data support and quantitative basis for sock design optimization and application scenario matching.

[0059] Specifically, optimization measures are taken according to the adaptability evaluation value, and the specific process of outputting the evaluation report is as follows: real-time comparison of the adaptability evaluation value and the adaptability threshold. When the adaptability evaluation value is greater than or equal to the adaptability threshold, it is judged as "well-adapted"; published in the product visualization report as an example of high adaptability performance to enhance the credibility and market orientation of product recommendations; allow to continue to carry out large-scale intensity testing or multi-scenario expansion testing to further verify its broad-spectrum adaptability; generate a complete test report for publicity and internal evaluation; when the adaptability evaluation value is less than the adaptability threshold, it is judged as "adaptability to be optimized"; based on the components of the adaptability evaluation value, automatically identify Identify the source of performance bottlenecks, ensure the efficiency and accuracy of problem location, and put forward targeted optimization suggestions from three aspects: material selection, structural layout and test configuration; after the optimization plan is adjusted by design, trigger a new round of simulated gait loading process, re-evaluate wear and performance scoring, and realize closed-loop feedback control of product iteration and upgrade; automatically integrate key parameters and evaluation results of the whole process, and output structured, visual standardized test reports, including test parameters, sock images, wear images, and scoring suggestions, including the output of the most suitable population type and the most suitable sports scene for socks made of new materials, and support the prediction of the expected life of socks under different sports rhythms and populations.

[0060] In this implementation plan, through real-time comparison of the adaptability evaluation value and the threshold, the system can automatically determine the performance level of the sock sample, and recommend it to enter the large-scale testing and market promotion process in the case of "well-fitted type", thereby improving the conversion efficiency of excellent samples; and for "fitness to be optimized" samples, the system can accurately identify performance bottlenecks, put forward targeted material, structure and test scheme optimization suggestions, and achieve rapid iteration through a closed-loop control mechanism; at the same time, the test report output is structured and visualized, covering core information such as applicable population, sports scenarios and life prediction, significantly enhancing the application guidance and R&D decision-making value of the report.

[0061] Reference Figure 2As shown, the second aspect of the present invention provides a socks sports wear resistance testing device, which is applied to the above-mentioned socks sports wear resistance testing method, including a data acquisition and preprocessing module, a dynamic loading and wear simulation module, a wear detection and intelligent evaluation module, and a loss modeling and motion scene adaptation analysis module: wherein the data acquisition and preprocessing module is used to collect user parameters and gait parameters of different motion types, and construct a gait model, calculate the pressure distribution evaluation value according to the user parameters and gait parameters, and perform data preprocessing; the dynamic loading and wear simulation module is used to install new material socks, use the rhythm control of different motion patterns to reproduce the force path and friction environment of the socks under real motion conditions, and synchronously record the friction force, slip trajectory and local shear conditions through multiple sensors to form a wear trajectory; the wear detection and intelligent evaluation module is used to obtain the sock sole image, perform visual recognition and wear area extraction, and output quantitative wear indicators; the loss modeling and motion scene adaptation analysis module is used to integrate simulation parameters and wear results to evaluate the wear resistance of new material socks, perform adaptability matching analysis, and take optimization measures according to the adaptability evaluation value, and output an evaluation report.

[0062] In this implementation plan, four functional modules are constructed to achieve a full-process, multi-dimensional intelligent assessment of the athletic wear resistance of socks. The data acquisition and preprocessing module ensures the personalization and accuracy of gait models and force data, improving the pertinence of test simulations. The dynamic loading and wear simulation module highly restores actual sports scenes, ensuring that the wear path is realistic and reliable. The wear detection and intelligent assessment module achieves high-precision recognition and index quantification of wear images, enhancing the depth of analysis. The loss modeling and adaptation analysis module integrates multi-source data, outputs scientific adaptability assessment results, and links optimization suggestions and feedback control to form an integrated closed-loop mechanism for product testing, evaluation, and improvement, significantly improving the efficiency of sock R&D and the intelligent level of applicability judgment.

[0063] It should be noted that, in this document, relational terms such as first and second, etc., are used only to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any actual relationship or order between these entities or operations. Moreover, the terms "comprises," "comprising," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that includes a list of elements includes not only those elements but also other elements not explicitly listed, or elements inherent to such process, method, article, or apparatus.

[0064] The preferred embodiments of the present invention disclosed above are intended only to help illustrate the present invention. These preferred embodiments do not exhaustively describe all details, nor do they limit the present invention to the specific embodiments described. Obviously, many modifications and variations are possible based on the content of this specification. These embodiments are selected and described in detail in this specification to better explain the principles and practical applications of the present invention, thereby enabling those skilled in the art to better understand and utilize the present invention. The present invention is limited only by the claims and their full scope and equivalents.

Claims

1. A method for testing the wear resistance of athletic socks, characterized in that: The following steps are involved: S1, collects user parameters and gait parameters of different motion types, builds a gait model, calculates pressure distribution evaluation values based on user parameters and gait parameters, and performs data preprocessing; S2: Installing new material socks, using rhythm control of different motion patterns to reproduce the force path and friction environment of the socks under real motion conditions, and using multiple sensors to synchronously record friction, slip trajectory and local shear conditions to form wear tracks; S3, obtains the sock sole image, performs visual recognition and wear area extraction, and outputs quantitative wear indicators; S4, integrates test data and wear results to evaluate the wear resistance of new material socks, conducts adaptability matching analysis, takes optimization measures based on the adaptability evaluation value, and outputs an evaluation report.

2. A method for testing the wear resistance of socks for sports performance according to claim 1, characterized in that: The specific process of collecting user parameters and gait parameters of different motion types and constructing a gait model is as follows: The wearer's user parameters are collected, including height, weight, gender, foot shape and plantar area size. Standard gait parameters are extracted according to different movement types, including step frequency data, single-step duration, landing lead position and force time ratio. The user parameters and gait parameters are normalized. The controller is used to convert the gait parameters into control signals. The foot model realizes landing and pushing actions through the front and rear drive actuators. The ankle angle adjustment machine adjusts the landing angle. The inertial measurement unit sensor measurement module and displacement encoder are respectively arranged at the bottom of the foot model and the ankle joint to achieve a highly simulated gait dynamic simulation cycle.

3. A method for testing the wear resistance of socks for sports performance according to claim 1, characterized in that: The specific process of calculating the pressure distribution evaluation value based on the user parameters and gait parameters and performing data preprocessing is as follows: Obtain the wearer's weight, monitor periodic oscillations through the inertial measurement unit sensor of the foot model to obtain cadence data, obtain the regional relative phase based on the landing lead position of the standard gait parameters, obtain the force area of the i-th region of the sole of the foot by measuring the contact area through the flexible pressure sensing pad, and normalize the force area; multiply the wearer's weight by the gravity-to-pressure constant to obtain the total pressure value; multiply the cadence data, twice the pi, and the current time to obtain the angle value in the current gait cycle; add the relative phase of the i-th sole area to the angle value to obtain the total phase angle value; calculate the cosine function of the total phase angle value, multiply the cosine function calculation result by the landing impact weight factor plus the constant one, and then multiply the summation result by the ratio of the force area of the i-th region and the total pressure value to obtain the pressure distribution assessment value; The pressure value, angle value and displacement data are low-pass filtered to eliminate high-frequency noise, standardized and normalized, and synchronized with the time axis.

4. A method for testing the wear resistance of socks for sports performance according to claim 1, characterized in that: The specific process of installing the new material socks and using the rhythm control of different movement patterns to reproduce the force path and friction environment of the socks under real movement conditions, and synchronously recording the friction force, slip trajectory and local shearing conditions through multiple sensors to form the wear trajectory is as follows: The socks made of the new material to be tested are mounted on the surface of the foot mold according to the standard process. They are tensioned using a tensile tester. The initial length, width, and locations of key stress-bearing areas are recorded. Images of the socks' initial state from multiple angles, including front views, sole images, and close-ups of arches, are captured and stored in a sample database. The gait trajectory is called according to the set motion mode, so that the foot model performs periodic bionic motion under the drive of the control system, realizing dynamic simulation of different scenarios. The multi-directional load action of friction, compression and tension is further established between the bottom of the foot model and the test table. During the test, a flexible pressure sensing pad is used to collect force data from various areas of the sock sole in real time. The inertial measurement unit sensor module and the friction coefficient sensor are used to synchronously obtain the shear impact characteristics and foot trajectory changes. The bottom friction tensiometer is used to monitor friction changes, and the laser displacement meter is used to reconstruct the slip trajectory. The force data collected during the test is cached through a unified timestamp alignment mechanism and undergoes filtering, normalization, and outlier removal steps.

5. A method for testing the wear resistance of socks for sports performance according to claim 1, characterized in that: The specific process of obtaining the sock sole image, performing visual recognition and extracting the worn area is as follows: After the motion simulation test is completed, the socks are removed from the foot model and flattened in a standard manner. The flattened areas are numbered according to the distribution of the plantar area. A high-resolution platform is used to obtain images of the sock soles. The shooting methods include standard vertical projection images and oblique side lighting images to enhance the clarity of thread breaks, holes, and color changes. After image acquisition, the wear image recognition and analysis of the sock sole image is automatically performed, the image is grayed and the background is removed, and the edge detection algorithm is used to locate the potential wear edges. In the cleaned image, the key attributes of the wear area are identified through regional connectivity analysis and morphological feature extraction methods, including the total length of broken lines, hole diameter, and local color spot area indicators. A structured sock sole wear map is output based on the initial state image taken.

6. A method for testing the wear resistance of socks for sports performance according to claim 1, characterized in that: The specific process of outputting the quantitative wear index is as follows: The wear area ratio is output by the ratio of the damaged area to the total sock sole area, and the broken line density is obtained by the number of broken lines per unit area. For each area i divided by the sock sole, the wear area of the i-th area is obtained by wear image recognition and the wear area is normalized. The average pressure distribution evaluation value is used to average the time integral to obtain the average pressure of the i-th area, and the maximum average pressure of all areas is screened out. The average pressure of the i-th area is divided by the maximum average pressure of all areas in the test to obtain the relative pressure intensity ratio of the area. The pressure distribution evaluation value of each area is compared with the average pressure threshold using sensor data to obtain the relative pressure intensity ratio of the area. High-pressure duration: The high-pressure exposure ratio of the area is obtained by the ratio of the high-pressure duration to the total test time. The pressure response weight factor is weighted by the relative pressure intensity ratio in the form of an exponential to obtain the pressure intensity index term. The time exposure weight factor is weighted by the high-pressure exposure ratio in the form of an exponential to obtain the high-pressure time index term. The pressure intensity index term and the high-pressure time index term are multiplied together and then multiplied by the wear area and regional structure weight factor of the area to obtain the fatigue matching contribution value of the area. The fatigue matching contribution values of all areas are summed and divided by the sum of the products of all wear areas and regional structure weight factors to obtain the fatigue concentration assessment value. Compare the fatigue concentration assessment value with the fatigue concentration threshold in real time. When the fatigue concentration assessment value is greater than or equal to the fatigue concentration threshold, the socks are judged to have reasonable wear concentration and automatically filed in the qualified sample library. They are recommended for use in specified sports types, selected as performance examples, and appear on the final report summary page. When the fatigue concentration assessment value is less than the fatigue concentration threshold, the sock wear drift is determined, and the areas with significant wear but insufficient pressure loading are automatically located. The structural and force mismatch areas are identified, and local structural reconstruction suggestions are generated. The stress type is inferred based on the wear characteristics, and a prompt is sent to replace high-wear-resistant and cushioning materials. The sock sample is automatically marked as structural optimization to be verified. After adjustment, the test verification process is reloaded, and the current test data is retained as a preliminary reference version.

7. A method for testing the wear resistance of socks for sports performance according to claim 1, characterized in that: The specific process of integrating test data and wear results to evaluate the wear resistance of new material socks is as follows: By integrating multi-dimensional data of user parameters, gait parameters, and wear results from the test, characteristic variables are constructed, including the wear rate under unit pressure and the gait peak and wear alignment index; Calculate the pressure distribution assessment value for each area, perform time integration to obtain the cumulative total force during the test cycle, and sum the cumulative total forces of all areas. Obtain the wear area of each area through wear image recognition and sum them to obtain the total wear of the entire sock. Divide the cumulative total force of all areas by the total wear to obtain the unit wear assessment value. The unit wear assessment value is compared with the unit wear threshold in real time. If the unit wear assessment value is less than the unit wear threshold, the socks are judged to have insufficient material wear resistance and are recommended to be replaced with high-strength fabrics. Zoned differentiated reinforcement is also recommended, and linked structural modeling is used to analyze whether the material strength matches the stress area to avoid high-pressure accumulation in weak material areas. When the unit wear assessment value is greater than or equal to the unit wear threshold, the material is judged to be stable, classified into the qualified wear resistance sample set, and recommended for use in high-load or long-term motion scenarios.

8. A method for testing the wear resistance of socks for sports performance according to claim 1, characterized in that: The specific process of performing the adaptability matching analysis is as follows: Compare the test wear results of the sock samples under different motion modes and output the adaptability matching results; obtain the unit wear assessment value and fatigue concentration assessment value of the sock sample, calculate the standard deviation and mean of the wear area of all areas of the sock sole based on wear image recognition, subtract the unit wear assessment value from the constant one and multiply it by the wear resistance assessment weight factor to obtain the wear resistance assessment item, multiply the fatigue concentration assessment value by the structural rationality weight factor to obtain the structural rationality assessment item, subtract the ratio of the standard deviation of the wear area to the mean from the constant one and multiply it by the wear distribution weight factor to obtain the wear uniformity assessment item, and sum the wear resistance assessment item, structural rationality assessment item and wear uniformity assessment item to obtain the adaptability assessment value.

9. A method for testing the wear resistance of socks for sports performance according to claim 1, characterized in that: The specific process of taking optimization measures based on the adaptability evaluation value and outputting the evaluation report is as follows: Compare the adaptability assessment value with the adaptability threshold in real time. When the adaptability assessment value is greater than or equal to the adaptability threshold, it is determined to be "well-adapted" and published in the product visualization report as an example of high adaptability performance. Continuation of large-scale intensity testing or multi-scenario expansion testing is allowed. Generate complete test reports for publicity and internal evaluation; When the adaptability assessment value is less than the adaptability threshold, it is judged as "adaptability to be optimized"; based on the components of the adaptability assessment value, the system automatically identifies the source of performance bottlenecks and provides targeted optimization suggestions in terms of material selection, structural layout, and test configuration; After the optimization plan is adjusted, a new round of simulated gait loading process is triggered, and wear assessment and performance scoring are re-performed, thus achieving closed-loop feedback control for product iteration and upgrading. Automatically integrate key parameters and evaluation results of the entire process, and output a structured, visual, standardized test report containing test parameters, sock images, wear images, and scoring recommendations. This report also outputs the most suitable population type and sports scenario for socks made of this new material, and supports the prediction of the expected life of socks under different sports rhythms and populations.

10. A socks sports wear resistance testing device, characterized in that: It includes data acquisition and preprocessing module, dynamic loading and wear simulation module, wear detection and intelligent evaluation module, and loss modeling and motion scene adaptation analysis module: The data acquisition and preprocessing module is used to collect user parameters and gait parameters of different motion types, build a gait model, calculate the pressure distribution evaluation value based on the user parameters and gait parameters, and perform data preprocessing; The dynamic loading and wear simulation module is used to install socks made of new materials. It uses the rhythm control of different movement patterns to reproduce the force path and friction environment of the socks under real movement conditions. It uses multiple sensors to synchronously record friction, slip trajectory and local shear conditions to form a wear trajectory. The wear detection and intelligent assessment module is used to obtain images of the sock soles, perform visual recognition and wear area extraction, and output quantitative wear indicators; The loss modeling and motion scene adaptation analysis module is used to integrate simulation parameters and wear results to evaluate the wear resistance of new material socks, perform adaptability matching analysis, take optimization measures based on the adaptability evaluation value, and output an evaluation report.

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