A clothing design simulation evaluation method and system based on clothing ergonomics

Abstract

The application discloses a garment design simulation evaluation method and system based on ergonomics, and belongs to the technical field of digital garment design.S1, human body size data and three-dimensional scanning data of a target user are acquired, a personalized human body three-dimensional model of the user is constructed, and a body curve data set containing multi-part dimensional features and curvature features is generated;S2, pattern structure parameters and fabric mechanical property parameters of a target garment are acquired, and a three-dimensional digital model of the garment is constructed;S3, based on the principle of human body kinematics, the range of motion of key joints under a typical motion action is set, and the human body model is driven to perform motion simulation;S4, motion comfort evaluation indexes and thermal-wet comfort evaluation indexes are respectively constructed;S5, a garment comprehensive adaptation degree evaluation model is constructed, comfort scores of each part and comprehensive adaptation degree results are output, and pattern optimization suggestions are generated.The application adopts multi-dimensional precise simulation evaluation based on ergonomics, forms an optimized closed loop, and improves garment design efficiency.

Description

Technical Field

[0001] This invention relates to the field of digital clothing design technology, and in particular to a method and system for simulating and evaluating clothing design based on clothing ergonomics. Background Technology

[0002] As the apparel industry accelerates its digital and intelligent transformation, the traditional apparel design model, which relies on physical sample garments for trial and verification, has drawbacks such as long development cycles, high material costs, and strong subjectivity in comfort evaluation. It is no longer suitable for the market demand for rapid iteration and personalized customization of fast fashion products.

[0003] Current 3D clothing simulation technologies primarily focus on static drape and basic fit, relying heavily on simplified human body models based on key circumference parameters such as bust and waist circumference. This lack of detailed breakdown and feature extraction of body contours prevents accurate morphological support for surface pressure calculations. In dynamic wearing scenarios, existing solutions lack sufficient accuracy in simulating garment stretching deformation and relative slippage. Interface pressure calculations do not adequately incorporate dynamic corrections based on garment slippage during movement, leading to significant discrepancies between dynamic comfort assessments and actual wearing experiences. Furthermore, existing clothing comfort assessment systems often consider only pressure or thermo-moisture performance, failing to systematically integrate pressure comfort, motion comfort, and thermo-moisture comfort into a scientifically comprehensive evaluation model. Most simulation systems only output basic assessment results, lacking effective integration between assessment analysis and pattern optimization, thus failing to provide precise optimization directions for design iterations and hindering the overall efficiency and quality of digital clothing design. Summary of the Invention

[0004] The purpose of this invention is to provide a method and system for simulating and evaluating clothing design based on clothing ergonomics, thereby solving the aforementioned technical problems.

[0005] To achieve the above objectives, a simulation evaluation method for clothing design based on clothing ergonomics includes the following steps: S1. Obtain the target user's human body size data and 3D scan data, construct a personalized 3D human body model for the user, and extract the body contour curve based on the human body orthogonal projection to generate a body curve dataset containing multi-part dimensional features and curvature features. S2. Obtain the pattern structure parameters and fabric mechanical performance parameters of the target garment, and construct a three-dimensional digital model of the garment; S3. Based on the principles of human kinematics, the range of motion of key joints under typical movements is set, and the human body model is driven to perform motion simulation. The amount of stretching deformation and slippage of clothing during the movement is calculated simultaneously. Based on the elastic modulus of the fabric and the contact area between clothing and human body, the pressure distribution data of the human body-clothing interface is dynamically calculated. S4. Construct evaluation indices for motion comfort and thermal-humidity comfort respectively; S5. Integrate evaluation indicators of pressure comfort, motion comfort, and thermal and moisture comfort to construct a comprehensive clothing fit evaluation model, output comfort scores for each part and comprehensive fit results, and generate pattern optimization suggestions.

[0006] Preferably, the process of generating the body curve dataset in S1 is as follows: Orthogonally project the three-dimensional human body model along the sagittal and coronal planes respectively to obtain two sets of two-dimensional contour curves. For each set of two-dimensional contour curves, a two-dimensional coordinate system is established with the midpoint of the human foot as the origin and the height direction as the vertical axis. Height nodes are set at equal intervals along the vertical axis, and the human horizontal dimension value corresponding to each height node is extracted to form a set of discrete contour points. The peak and valley points in the contour curve are identified, and the valley points are used as segment boundaries to divide the contour curve into feature segments corresponding to different human body parts. The curvature change rate, maximum girth value and girth gradient of each feature segment are extracted to form a body curve dataset.

[0007] Preferably, the fabric mechanical performance parameters in S2 include at least the warp / weft tensile modulus, bending stiffness, air permeability, moisture resistance, and surface friction coefficient of the fabric; the pattern structure parameters include at least the ease allowance of each part of the garment, the position of the dividing line, the dart parameters, and the seam allowance design.

[0008] Preferably, the calculation process for the human body-clothing interface pressure in S3 is as follows: Based on the Laplace surface pressure formula, and combining the deformation curvature of clothing on the human body surface with fabric tension, the interfacial pressure per unit area is calculated using the following formula: ; In the formula, This refers to the interfacial pressure, expressed in Pa. The fabric tension per unit width is expressed in N / m. , These are the two principal radii of curvature of the surface at the human contact point, in meters; Among them, fabric tension The tension is dynamically corrected by calculating the local stretching deformation of the garment and the elastic modulus of the fabric, and by combining the amount of slippage of the garment during movement.

[0009] Preferably, the motion comfort evaluation index in S4 is based on the difference in the maximum joint range of motion between the clothed and bare states, and the motion restriction rate is calculated using the following formula: ; In the formula, Joint movement restriction rate; This represents the maximum range of motion of the joint in its bare state, expressed in degrees (°). The maximum range of motion of the joint in the dressed state, in degrees; The motion restriction rates of four key joints—shoulder, elbow, hip, and knee—are selected, and a motion comfort evaluation index is obtained by weighted summation. The calculation formula is as follows: ; In the formula, Rate the comfort of movement; For the first The weight coefficients of each key joint, and ; For the first Movement restriction rate of key joints.

[0010] Preferably, the thermal and moisture comfort evaluation index in S4 is based on the fabric's breathability and moisture resistance parameters, and is corrected by combining the influence of interfacial pressure distribution on the microclimate air layer. The corrected formula for calculating the total thermal resistance of the garment is as follows: ; In the formula, The corrected total thermal resistance of the garment is expressed in meters (m). 2 K / W; The thermal resistance of the fabric itself, measured in meters (m). 2 K / W; Thermal resistance of the stationary air layer, in meters (m). 2 K / W; This is the pressure influence coefficient, with a value ranging from 0.2 to 0.5. The standard comfort pressure threshold is expressed in Pa. The correction logic for moisture resistance is the same as that for thermal resistance. The formula for calculating the corrected total moisture resistance is as follows: ; In the formula, The corrected total wet resistance of the garment is expressed in meters (m). 2 Pa / W; The moisture resistance of the fabric itself, measured in meters (m). 2 Pa / W; The moisture resistance of the still air layer, in meters. 2 Pa / W; Finally, the thermal and humid comfort score is calculated by combining the human body's metabolic heat production rate and sweating rate.

[0011] Preferably, the comprehensive fitness evaluation model in S5 uses the analytic hierarchy process (AHP) to determine the weights of each indicator, specifically as follows: Pressure comfort, motion comfort, and thermal-humidity comfort are used as primary indicators. Pressure comfort is calculated based on the uniformity of the interface pressure distribution and the degree to which the pressure value deviates from the comfort range. A judgment matrix is ​​constructed using expert scoring. After passing the consistency test, the weight coefficients of each primary indicator are calculated, and the weighted sum is used to obtain the overall suitability score. The calculation formula is as follows: ; In the formula, The overall fit score; , , The ratings are for pressure comfort, motion comfort, and thermal and humidity comfort, respectively. , , These are the weighting coefficients for the corresponding primary indicators, and ; The overall fit score is directly proportional to the comfort and fit of the clothing.

[0012] A system for simulation evaluation of clothing design based on clothing ergonomics includes: The human body data processing module is used to acquire user human body data, construct a three-dimensional human body model, and generate a body curve dataset. The garment modeling module is used to import pattern parameters and fabric parameters to build a 3D digital model of the garment. The motion simulation and pressure calculation module is used to drive the human body model to perform typical motion simulations and calculate the amount of clothing deformation and the pressure distribution at the human body-clothing interface. The comfort assessment module is used to calculate the comfort indices for motion, thermal and humidity, and pressure, and output the comprehensive fit evaluation results. The output module is optimized to identify uncomfortable areas based on the evaluation results, generate pattern and fabric optimization suggestions, and output a visual simulation report.

[0013] Preferably, the human body data processing module includes a 3D modeling unit, a contour projection extraction unit, and a feature segmentation and dataset generation unit; The 3D modeling unit is used to denoise, normalize the format, and filter invalid data from the input human body size data and 3D scan data to build a personalized 3D human body model for the user. The contour projection extraction unit is used to perform orthogonal projection along the sagittal and coronal planes of the three-dimensional human body model, establish a two-dimensional coordinate system, and extract the discrete point set of the contour. The feature segmentation and dataset generation unit is used to identify the peak and valley points of the contour curve, complete the feature segmentation of human body parts, extract the curvature and circumference features of each segment, generate a body curve dataset, and encapsulate and output it in a preset format.

[0014] Preferably, the process of generating layout optimization suggestions in the output module is as follows: The comfort scores for each part of the body are compared with preset comfort thresholds, and the uncomfortable parts with scores below the thresholds are marked. For parts with substandard pressure comfort, the amount of clothing relaxation and the position of the dividing lines in the corresponding area are adjusted. For parts with substandard movement comfort, the elastic modulus and dart parameters of the fabric at the joints are optimized. For parts with substandard thermal and moisture comfort, the breathability and moisture resistance parameters of the fabric in the corresponding area are replaced. Finally, the pattern and fabric optimization suggestions for each part are integrated.

[0015] Therefore, the present invention employs the above-mentioned clothing design simulation evaluation method and system based on clothing ergonomics, which has the following beneficial effects: 1. More accurate human body morphology representation: By extracting the body contour curves through orthogonal projection and segmenting them by part, a body curve dataset containing dimensional and curvature features is constructed, which accurately restores the human body surface morphology and provides a reliable morphological basis for subsequent simulation calculations.

[0016] 2. Dynamic pressure assessment is more realistic: Combining human kinematics to drive motion simulation, the amount of clothing stretching deformation and slippage is calculated simultaneously, and the interface pressure is calculated after dynamically correcting the fabric tension based on the slippage, which is more in line with the stress state of clothing in real sports scenarios.

[0017] 3. More comprehensive and objective comfort evaluation: A comfort evaluation system covering three dimensions—pressure, movement, and heat and humidity—is constructed. A comprehensive fit evaluation model is formed through scientific weight allocation, avoiding the one-sidedness of evaluation based on a single indicator, and the evaluation results are more in line with the actual wearing experience.

[0018] 4. Significantly improved design iteration efficiency: Simulation evaluation and pattern optimization form a complete closed loop, which can directly output targeted pattern optimization suggestions based on the evaluation results, reduce manual trial and error costs, shorten product development cycle, and improve the efficiency of digital clothing design and the comfort of finished products.

[0019] The technical solution of the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. Attached Figure Description

[0020] Figure 1 This is a flowchart illustrating the closed-loop logic of the system modules of the present invention. Figure 2 This is a flowchart of the garment design and pattern making method of the present invention; Figure 3 This is a schematic diagram of the two-dimensional production pattern for the drop-shoulder sleeve of the present invention; Figure 4 This is a flowchart illustrating the clothing design evaluation process of the present invention. Detailed Implementation

[0021] To make the objectives, technical solutions, and advantages disclosed in the embodiments of the present invention clearer, the embodiments of the present invention will be further described in detail below with reference to the accompanying drawings and examples. It should be understood that the specific embodiments described herein are only used to explain the embodiments of the present invention and are not intended to limit the embodiments of the present invention. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without creative effort are within the scope of protection of this application. Examples of the embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout.

[0022] It should be noted that the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion, such as a process, method, system, product, or server that includes a series of steps or units, not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such process, method, product, or device.

[0023] The embodiments of the present invention will now be described in detail with reference to the accompanying drawings.

[0024] like Figures 1-4 As shown, this embodiment uses a loose-fitting, drop-shoulder pure cotton T-shirt for male consumers aged 18-35 as the evaluation object. It employs a clothing design simulation evaluation method based on clothing ergonomics proposed in this invention to complete the pattern design and comfort verification. The specific implementation process is as follows: S1. Construction of 3D Human Body Model and Generation of Body Curve Dataset: Targeting the consumer group (men aged 18-35), the EinScanPro 3D scanner was used to collect anthropometric data and 3D scan data of 500 volunteers. The average body parameters of the standard Chinese male body type 175 / 92A were statistically obtained: height 175cm, weight 70kg, BMI=22.9, chest circumference 92cm, waist circumference 78cm, and shoulder width 42cm. At the same time, dynamic ergonomic parameters were collected: shoulder flexion 175°, abduction 170°, and axillary skin elongation rate 24%.

[0025] The system calls the basic human body model of standard body type 175 / 92A, and generates a standard three-dimensional human body model for mass production through bilinear interpolation algorithm. The model size accuracy error is controlled within 0.2cm.

[0026] Based on the completed 3D human body model, orthogonal projections are performed along the sagittal and coronal planes respectively to obtain two sets of 2D body contour curves. For each set of 2D contour curves, a 2D coordinate system is established with the midpoint of the human foot as the origin and the height direction as the vertical axis. Height nodes are set at equal intervals of 0.5cm along the vertical axis, and the human body horizontal dimension value corresponding to each height node is extracted to form a set of discrete contour points.

[0027] The peak and valley points in the contour curve are identified, and the valley points are used as segment boundaries to divide the contour curve into feature segments corresponding to different human body parts such as neck and shoulder, chest, waist, upper arm, and elbow. The curvature change rate, maximum circumference value and circumference gradient of each feature segment are extracted, and finally a body curve dataset containing multi-part dimensional features and curvature features is formed, which provides morphological basis for subsequent clothing modeling and pressure calculation.

[0028] S2. Construction of 3D Digital Model of Clothing: Obtain the pattern structure parameters and fabric mechanical performance parameters of the target clothing, and construct a parametric 3D digital model of clothing.

[0029] This embodiment uses a loose-fitting, drop-shoulder T-shirt pattern template, loading initial pattern parameters that meet the company's production standards: shoulder slope angle 15°, armhole arc length 32.2cm, sleeve cap height 10cm, garment length 68cm, bust 102cm, and initial cuff circumference 37cm. After the designer adjusts the cuff circumference from 37cm to 40cm according to the season's fashion trends, the system automatically updates the 3D virtual sample garment through a topological association algorithm, with a model refresh delay of 0.08 seconds, enabling rapid iterative adjustment of pattern parameters.

[0030] The fabric used is a 21-count pure cotton plain weave fabric commonly used in the company's production. Its core mechanical and physical performance parameters include: drape factor 0.65, warp tensile modulus of elasticity 800 N / m. 2 The warp stretch rate is 4% and the weft stretch rate is 3%. The bending stiffness, air permeability, moisture resistance and surface friction coefficient of this fabric are all measured according to national testing standards such as GB / T11048 and GB / T5453, which fully cover the input requirements of the mechanical performance parameters of the fabric.

[0031] S3. Motion Simulation and Human-Clothing Interface Pressure Calculation: Based on the principles of human kinematics, the range of motion of key joints under typical daily movements is set. In this embodiment, raising the arm 180° is selected as a typical dynamic movement, driving a standard three-dimensional human body model for motion simulation. During the simulation, the tensile deformation and slippage of the clothing during the movement are calculated simultaneously. Based on the elastic modulus of the fabric and the clothing-human contact area, the pressure distribution data of the human-clothing interface is dynamically calculated using the Laplace surface pressure formula. The interface pressure calculation formula is as follows: ; In the formula, This refers to the interfacial pressure, expressed in Pa. Fabric tension is the fabric tension per unit width, expressed in N / m. The tension is dynamically corrected by calculating the local tensile deformation of the garment and the elastic modulus of the fabric, and by combining the amount of slippage of the garment during movement. , These are the two principal radii of curvature of the surface at the point of contact with the human body, in meters.

[0032] The static fit simulation results show that the overall fit rate between the clothing and the human body is 93%, and the maximum gap between the human body and the clothing is 1.2cm, which meets the static wearing fit requirements.

[0033] Simulation results of a dynamic 180° arm raise showed that the average contact pressure in the armpit area was 0.62 kPa, exceeding the comfort pressure threshold; the elbow movement margin was only 0.4 cm, which was insufficient and required pattern optimization.

[0034] S4. Construction of Sub-item Comfort Evaluation Indicators: Separate evaluation indicators for motion comfort and thermal-moisture comfort are constructed to quantitatively assess the performance of the clothing. For motion comfort evaluation, the motion restriction rate is calculated based on the difference in maximum joint range of motion between clothed and unclothed states. The formula for calculating the motion restriction rate is: ; In the formula, Joint movement restriction rate; This represents the maximum range of motion of the joint in its bare state, expressed in degrees (°). The maximum range of motion of the joint in the dressed state, in degrees; This embodiment selects two key upper limb joints, the shoulder and elbow, and combines them with the motion restriction rates of two lower limb reference joints, the hip and knee. A weighted summation is used to obtain a motion comfort evaluation index, calculated using the following formula: ; In the formula, Rate the comfort of movement; For the first The weight coefficients of each key joint, and In this embodiment, the shoulder joint weight =0.4, elbow joint weight =0.3, hip joint weight Knee joint weight Both are 0.15; For the first Based on the motion restriction rate of key joints, the initial model's motion comfort score was low, with the elbow motion restriction rate exceeding the comfort range.

[0035] For the evaluation of thermal and moisture comfort, the total thermal resistance and total moisture resistance of the garment are obtained by correcting the calculation based on the fabric's breathability and moisture resistance parameters, combined with the influence of interfacial pressure distribution on the microclimate air layer.

[0036] The revised formula for calculating the total thermal resistance of clothing is as follows: ; In the formula, The corrected total thermal resistance of the garment is expressed in meters (m). 2 K / W; The thermal resistance of the fabric itself, measured in meters (m). 2 K / W; Thermal resistance of the stationary air layer, in meters (m). 2 K / W; This is the pressure influence coefficient, with a value ranging from 0.2 to 0.5. The standard comfort pressure threshold is expressed in Pa. The correction logic for moisture resistance is the same as that for thermal resistance. The formula for calculating the corrected total moisture resistance is as follows: ; In the formula, The corrected total wet resistance of the garment is expressed in meters (m). 2 Pa / W; The moisture resistance of the fabric itself, measured in meters (m). 2 Pa / W; The moisture resistance of the still air layer, in meters. 2 Pa / W; Finally, the thermal and humidity comfort score was calculated by combining the metabolic heat production rate and sweating rate of the human body in a seated state. The initial version had a slightly lower thermal and humidity comfort score because the local microclimate air layer was thinner in the armpit area due to higher pressure.

[0037] S5. Comprehensive Fit Assessment and Pattern Optimization: Integrating three evaluation indicators—pressure comfort, movement comfort, and thermal and moisture comfort—a comprehensive fit assessment model for clothing is constructed using the analytic hierarchy process (AHP). The model outputs comfort scores for each part of the garment and the overall fit result, and generates pattern optimization suggestions.

[0038] Pressure comfort, motion comfort, and thermal-humidity comfort are used as primary indicators. Pressure comfort is calculated based on the uniformity of the interface pressure distribution and the degree to which the pressure value deviates from the comfort range. A judgment matrix is ​​constructed using an expert scoring method. After passing a consistency test, the weight coefficients of each primary indicator are calculated, and the weighted sum is used to obtain the comprehensive fit score. The calculation formula is as follows: ; In the formula, The overall fit score; , , The ratings are for pressure comfort, motion comfort, and thermal and humidity comfort, respectively. , , These are the weighting coefficients for the corresponding primary indicators, and In this embodiment, the weights of the three items are 0.4, 0.35, and 0.25, respectively. The overall fit score is directly proportional to the comfort and fit of the clothing; a higher score indicates better overall performance.

[0039] The process of generating pattern optimization suggestions is as follows: compare the comfort scores of each part with preset comfort thresholds, and mark the uncomfortable parts with scores below the thresholds; for parts with substandard pressure comfort, adjust the ease of clothing and the position of the seam lines in the corresponding areas; for parts with substandard movement comfort, optimize the elastic modulus and dart parameters of the fabric at the joints; for parts with substandard thermal and moisture comfort, replace the breathability and moisture resistance parameters of the fabric in the corresponding areas; and finally, integrate them to form pattern and fabric optimization suggestions for each part.

[0040] In this embodiment, the system outputs the following optimization suggestions for the initial pattern: increase the armhole arc length by 2cm, adjust the shoulder slope angle to 16°, and increase the elbow ease by 1cm. Based on these suggestions, the pattern structure parameters are adjusted: the armhole arc length is increased to 34.2cm, the shoulder slope angle is changed to 16°, and the elbow ease is increased by 1cm. The system uses a gradient descent algorithm for automatic iterative optimization, aiming to minimize the variance of contact pressure and homogenize the movement allowance. After three iterations, simulation verification is performed again: the average contact pressure in the underarm area is reduced to 0.42kPa, within the comfortable pressure range; the elbow movement allowance is increased to 0.8cm, meeting dynamic movement requirements; and the overall fit score is improved by 18.7%, demonstrating significant pattern optimization.

[0041] After optimization, the system converts the three-dimensional virtual sample garment into a two-dimensional paper pattern through a pre-trained neural network, and corrects the size according to the warp stretch rate of 4% of pure cotton fabric. The correction formula is: corrected size = initial three-dimensional size / (1 + warp stretch rate × correction coefficient). In this embodiment, the correction coefficient is 1.0.

[0042] Based on calculations, the garment length is corrected as follows: ; Sleeve length adjusted to: ; The system automatically adds size markings and seam allowance parameters that conform to the garment industry standards: side seam allowance 1.5cm, sleeve seam allowance 1cm, neckline seam allowance 0.8cm, and finally outputs a standard two-dimensional paper pattern file that can be directly used for production.

[0043] The clothing design simulation evaluation system based on clothing ergonomics that implements the above evaluation methods includes a human data processing module, a clothing modeling module, a motion simulation and pressure calculation module, a comfort evaluation module, and an optimization output module. The human body data processing module is used to acquire user human body data, construct a 3D human body model, and generate a body curve dataset; the clothing modeling module is used to import pattern structure parameters and fabric mechanical performance parameters to construct a parametric 3D digital model of clothing; the motion simulation and pressure calculation module is used to drive the human body model to perform typical motion simulations, calculate clothing stretching deformation and pressure distribution at the human-clothing interface; the comfort assessment module is used to calculate motion comfort, thermal and moisture comfort, and pressure comfort indices respectively, and output a comprehensive fit evaluation result; the optimization output module is used to identify uncomfortable areas based on the evaluation results, generate pattern and fabric optimization suggestions, and output a visual simulation report including pressure heatmap and deformation cloud map.

[0044] The human body data processing module further includes a 3D modeling unit, a contour projection extraction unit, and a feature segmentation and dataset generation unit: the 3D modeling unit is used to denoise, normalize the format, and filter invalid data from the input human body size data and 3D scan data to construct a personalized 3D human body model for the user; the contour projection extraction unit is used to perform orthogonal projection along the sagittal and coronal planes of the 3D human body model, establish a 2D coordinate system, and extract the discrete point set of the contour; the feature segmentation and dataset generation unit is used to identify the peak and valley points of the contour curve, complete the feature segmentation of human body parts, extract the curvature and circumference features of each segment, generate a body curve dataset, and encapsulate and output it in a preset format.

[0045] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit them. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can still be made to the technical solutions of the present invention, and these modifications or equivalent substitutions cannot cause the modified technical solutions to deviate from the spirit and scope of the technical solutions of the present invention.

Claims

1. A simulation evaluation method for clothing design based on clothing ergonomics, characterized in that, Includes the following steps: S1. Obtain the target user's human body size data and 3D scan data, construct a personalized 3D human body model for the user, and extract the body contour curve based on human orthogonal projection to generate a body curve dataset containing multi-part dimensional features and curvature features. S2. Obtain the pattern structure parameters and fabric mechanical performance parameters of the target garment, and construct a three-dimensional digital model of the garment; S3. Based on the principles of human kinematics, the range of motion of key joints under typical movements is set, and the human body model is driven to perform motion simulation. The amount of stretching deformation and slippage of clothing during the movement is calculated simultaneously. Based on the elastic modulus of the fabric and the contact area between clothing and human body, the pressure distribution data of the human body-clothing interface is dynamically calculated. S4. Construct evaluation indices for motion comfort and thermal-humidity comfort respectively; S5. Integrate evaluation indicators of pressure comfort, motion comfort, and thermal and moisture comfort to construct a comprehensive clothing fit evaluation model, output comfort scores for each part and comprehensive fit results, and generate pattern optimization suggestions.

2. The clothing design simulation evaluation method based on clothing ergonomics according to claim 1, characterized in that, The specific process of generating the body curve dataset in S1 is as follows: Orthogonally project the three-dimensional human body model along the sagittal and coronal planes respectively to obtain two sets of two-dimensional contour curves. For each set of two-dimensional contour curves, a two-dimensional coordinate system is established with the midpoint of the human foot as the origin and the height direction as the vertical axis. Height nodes are set at equal intervals along the vertical axis, and the human horizontal dimension value corresponding to each height node is extracted to form a set of discrete contour points. The peak and valley points in the contour curve are identified, and the valley points are used as segment boundaries to divide the contour curve into feature segments corresponding to different human body parts. The curvature change rate, maximum girth value and girth gradient of each feature segment are extracted to form a body curve dataset.

3. The clothing design simulation evaluation method based on clothing ergonomics according to claim 1, characterized in that: The fabric mechanical properties parameters in S2 include at least the warp / weft tensile modulus, bending stiffness, air permeability, moisture resistance, and surface friction coefficient of the fabric; the pattern structure parameters include at least the ease allowance of each part of the garment, the position of the seam line, the dart parameters, and the seam allowance design.

4. The clothing design simulation evaluation method based on clothing ergonomics according to claim 1, characterized in that, The calculation process for the human body-clothing interface pressure in S3 is as follows: Based on the Laplace surface pressure formula, and combining the deformation curvature of clothing on the human body surface with fabric tension, the interfacial pressure per unit area is calculated using the following formula: ； In the formula, This refers to the interfacial pressure, expressed in Pa. The fabric tension per unit width is expressed in N / m. , These are the two principal radii of curvature of the surface at the human contact point, in meters; Among them, fabric tension The tension is dynamically corrected by calculating the local stretching deformation of the garment and the elastic modulus of the fabric, and by combining the slippage of the garment during movement.

5. The clothing design simulation evaluation method based on clothing ergonomics according to claim 1, characterized in that: The motion comfort evaluation index in S4 is based on the difference in the maximum joint range of motion between clothed and bare states, which is used to calculate the motion restriction rate. The formula for calculating the motion restriction rate is as follows: ； In the formula, Joint movement restriction rate; This represents the maximum range of motion of the joint in its bare state, expressed in degrees (°). The maximum range of motion of the joint in the dressed state, in degrees; The motion restriction rates of four key joints—shoulder, elbow, hip, and knee—are selected, and a motion comfort evaluation index is obtained by weighted summation. The calculation formula is as follows: ； In the formula, Rate the comfort of movement; For the first The weight coefficients of each key joint, and ; For the first Movement restriction rate of key joints.

6. The clothing design simulation evaluation method based on clothing ergonomics according to claim 1, characterized in that: The thermal and moisture comfort evaluation index in S4 is based on fabric breathability and moisture resistance parameters, and is modified by combining the influence of interfacial pressure distribution on the microclimate air layer. The modified formula for calculating the total thermal resistance of clothing is as follows: ； In the formula, The corrected total thermal resistance of the garment is expressed in meters (m). 2 K / W; The thermal resistance of the fabric itself, measured in meters (m). 2 K / W; Thermal resistance of the stationary air layer, in meters (m). 2 K / W; This is the pressure influence coefficient, with a value ranging from 0.2 to 0.

5. The standard comfort pressure threshold is expressed in Pa. The moisture resistance is corrected using the same logic as the thermal resistance. The corrected total moisture resistance calculation formula is as follows: ； In the formula, The corrected total wet resistance of the garment is expressed in meters (m). 2 Pa / W; The moisture resistance of the fabric itself, measured in meters (m). 2 Pa / W; The moisture resistance of the still air layer, in meters. 2 Pa / W; Finally, the thermal and humid comfort score is calculated by combining the human body's metabolic heat production rate and sweating rate.

7. The clothing design simulation evaluation method based on clothing ergonomics according to claim 1, characterized in that, The S5 comprehensive fitness evaluation model uses the analytic hierarchy process (AHP) to determine the weights of each indicator, specifically: Pressure comfort, motion comfort, and thermal-humidity comfort are used as primary indicators. Pressure comfort is calculated based on the uniformity of the interface pressure distribution and the degree to which the pressure value deviates from the comfort range. A judgment matrix is ​​constructed using expert scoring. After passing the consistency test, the weight coefficients of each primary indicator are calculated, and the weighted sum is used to obtain the overall suitability score. The calculation formula is as follows: ； In the formula, The overall fit score; , , The ratings are for pressure comfort, motion comfort, and thermal and humidity comfort, respectively. , , These are the weighting coefficients for the corresponding primary indicators, and ; The overall fit score is directly proportional to the comfort and fit of the clothing.

8. A system for simulation evaluation of clothing design based on clothing ergonomics according to any one of claims 1-7, characterized in that, include: The human body data processing module is used to acquire user human body data, construct a three-dimensional human body model, and generate a body curve dataset. The garment modeling module is used to import pattern parameters and fabric parameters to build a 3D digital model of the garment. The motion simulation and pressure calculation module is used to drive the human body model to perform typical motion simulations and calculate the amount of clothing deformation and the pressure distribution at the human body-clothing interface. The comfort assessment module is used to calculate the comfort indices for motion, thermal and humidity, and pressure, and output the comprehensive fit evaluation results. The output module is optimized to identify uncomfortable areas based on the evaluation results, generate pattern and fabric optimization suggestions, and output a visual simulation report.

9. The system for a clothing design simulation evaluation method based on clothing ergonomics according to claim 8, characterized in that: The human body data processing module includes a 3D modeling unit, a contour projection extraction unit, and a feature segmentation and dataset generation unit; The 3D modeling unit is used to denoise, normalize the format, and filter invalid data from the input human body size data and 3D scan data to build a personalized 3D human body model for the user. The contour projection extraction unit is used to perform orthogonal projection along the sagittal and coronal planes of the three-dimensional human body model, establish a two-dimensional coordinate system, and extract the discrete point set of the contour. The feature segmentation and dataset generation unit is used to identify the peak and valley points of the contour curve, complete the feature segmentation of human body parts, extract the curvature and circumference features of each segment, generate a body curve dataset, and encapsulate and output it in a preset format.

10. The system for a clothing design simulation evaluation method based on clothing ergonomics according to claim 8, characterized in that, The specific process for generating layout optimization suggestions in the output module is as follows: The comfort scores for each part of the body are compared with preset comfort thresholds, and the uncomfortable parts with scores below the thresholds are marked. For parts with substandard pressure comfort, the amount of clothing relaxation and the position of the dividing lines in the corresponding area are adjusted. For parts with substandard movement comfort, the elastic modulus and dart parameters of the fabric at the joints are optimized. For parts with substandard thermal and moisture comfort, the breathability and moisture resistance parameters of the fabric in the corresponding area are replaced. Finally, the pattern and fabric optimization suggestions for each part are integrated.

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