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Prediction Of Body-shaping Clothes’ Loading Pressure And Shaping Effect Based On GA-BP Neural Network

Posted on:2023-10-08Degree:MasterType:Thesis
Country:ChinaCandidate:F F WangFull Text:PDF
GTID:2531307076983629Subject:Costume design and engineering
Abstract/Summary:PDF Full Text Request
Currently,there is no clear standard on the selection of shapewear size and the range of comfortable clothing pressure for human body,which leads many users to blindly pursue the shaping effect and choose the wrong size of shapewear to affect their health.Therefore,this paper investigates the effects of clothing pressure comfort and shaping effect of shapewear to provide reference for enterprises to optimize the structure and fabric of shapewear for subjects with different body types;to establish a model that can predict the clothing pressure and shaping effect after wearing shapewear,and to recommend the appropriate size for users.In order to analyze the characteristics and differences of clothing pressure comfort and shaping effect after wearing shapewear for subjects with different body types,this paper selects a brand of waist and back clips and buttock lifting corsets as experimental materials,and recruits30 women as subjects(BMI between 17.9 and 31.0 kg/m~2),and on the basis of body measurements,the subjects are analyzed by K-means mean cluster analysis method according to BMI,Bust,waist and hip circumference were divided into three categories,named S,M and F bodies,and the rationality of the classification was analyzed and verified.Thirty subjects were allowed to wear three sizes of shapewear:fit,smaller and larger(individual subjects did not have small or large shapewear),so that a total of 78 experimental samples were obtained.The AMI3037-10-II airbag garment pressure test system from AMITECHNO,Japan,was used to test the back of the shoulders(3 points),lower chest(3 points),waist(4 points),and abdomen(4 points)of the subjects in six body positions:standing,standing deep breathing,standing forward,sitting,sitting deep breathing,and sitting forward,respectively,in a relatively quiet environment with comfortable temperature and humidity.),abdomen(4 points),buttocks(1 point)and thigh root(3 points)were tested for a total of 19 points of clothing pressure.The weight distribution of each garment pressure measurement point in each part was calculated by the entropy assignment method,and the garment pressure of each part was calculated by combining the test results of each garment pressure measurement point in each part.Through the analysis of the test results,it was found that:(1)the garment pressure values of the same parts of the three body types were close after wearing the fit shapewear,with a minimum difference of0.04 k Pa and a maximum difference of 2.40 k Pa;(2)the garment pressure values of the same parts were slightly smaller for the S body than for the M body and the F body;(3)the garment pressure at the back of the shoulders of the S body and the M body varied between 1.08 k Pa~1.90 k Pa,with the garment pressure at the back of the shoulders of the M body and the F body always greater than that of the F body.The garment pressure at the back of the shoulders of M and F bodies is always greater than that of S bodies,and basically shows the same trend with the change of posture;the garment pressure at the lower bust and waist and abdomen is greater,all greater than 3 k Pa,and the maximum can reach 5.87 k Pa;the garment pressure at the hips is less than 1 k Pa in standing posture and deep breathing in standing posture,and close to 2.5 k Pa in sitting forward posture;the garment pressure at the root of the thighs of the three body types is closer in size,and the values are all between 2 k Pa~3k Pa,with the test posture change pattern consistent,in the standing posture forward leaning when the smallest,sitting posture forward leaning when the largest.(4)The three body types wearing different sizes of shapewear produced clothing pressure change pattern is basically the same,are smaller size>fit>larger size,wearing different sizes of shapewear the same parts of the clothing pressure difference is basically greater than 0.50k Pa.While the objective garment pressure test was conducted on 78 experimental samples,the subjective evaluation of garment pressure sensation and garment pressure comfort was conducted in the form of subjective evaluation scale and questionnaire,and the consistency of the subjective evaluation results was found to be good through reliability analysis.Through the analysis of the subjective evaluation results,it was found that(1)the subjects wore three different sizes of shapewear,and the garment pressure comfort was above the average level,indicating that the comfort of the shapewear was good.(2)The pressure sensitivity and pressure-bearing capacity of different parts were different,among which the pressure sensitivity at the lower bust was weaker and the pressure-bearing capacity at the waist and abdomen was stronger.The[TC]~2 3D body scanner was used to scan the body shape of the subject’s net body state and wearing the shapewear state respectively,and the reverse engineering software Geomagic Wrap was used to process the 3D point cloud data of the human body output from[TC]~2 and extract to the data of each part of the human body.The shaping effect was expressed by the rate of change in the circumference,thickness and width of each test part of the human body before and after wearing the shapewear.Through analysis,it was found that(1)the shapewear had an obvious shaping effect,and the shaping effects were waist lifting,breast lifting,abdominal tightening,leg slimming and buttock lifting in descending order;(2)the shaping effects of the shapewear on the subjects with three types of body shapes were similar,and from the mean value,it was found that the S body had an obvious effect of breast lifting and breast enlargement,waist lifting and(3)The waist-to-hip ratio of the three body types decreased and was closer to 0.7 after wearing the shapewear,among which the waist-to-hip ratio of body type F changed the most,and the WHR value decreased by 10%,indicating that the shapewear had the most obvious effect on this body type;(4)After wearing different sizes of shapewear,the rates of change in bust line height,hip line height,bust circumference,hip circumference,thigh root circumference,abdominal thickness,hip thickness,thigh root thickness,abdominal width and thigh root width were relatively similar,while the rates of change in waist width and waist circumference were more different.The rates of change of waist width and waist circumference of S and M bodies are smaller size>fit size>larger size,with a large difference in values,while the rates of change of waist width and waist circumference of F bodies are fit size>small size>large size,with a small difference in values.In order to establish a BP neural network model that can predict the body garment pressure and shaping effect after wearing shapewear and assist consumers in choosing the appropriate shapewear size,this paper establishes a BP neural network model after determining the input index,prediction index,the number of nodes in the hidden layer and the combination of functions,and then uses genetic algorithm to optimize the BP neural network model to make up for the defect that the BP neural network is easy to fall into local minima and find the optimal initial weights and threshold values.When the best fit is reached after 796 training sessions,the coefficient of determination R of its training set is 0.990,the coefficient of determination R of its test set is 0.985,and the coefficient of determination R of the overall sample is 0.989,and the coefficient of determination R of each data set is close to 1,which is a significant improvement over the fitting effect of the BP neural network model,indicating that the genetic algorithm has an obvious effect on the optimization of the BP neural network model.Finally,the output parameters in the MATLAB workspace were called into the GUI interface using C#language to determine the principles of shapewear size recommendation and develop a women’s shapewear size recommendation system.
Keywords/Search Tags:Shapewear, Clothing pressure, Shaping effect, GA-BP neural network model, Recommendation system
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