武漢青年女性腰臀部形態(tài)及其合體下裝結構研究
發(fā)布時間：2018-11-18 10:01
【摘要】：隨著社會的發(fā)展,人們對服裝合體性、舒適性的要求越來越高,服裝是“以人為本”,人體的尺寸數(shù)據(jù)可以為服裝結構的研究提供準確的科學依據(jù),人體體型研究是服裝結構研究的基礎,本課題通過三維人體掃描獲取人體腰臀部詳細的數(shù)據(jù)庫,通過SPSS分析及橫截面的圖像疊加模擬腰臀部體型特征,通過體型分類研究其對合體下裝結構的影響。采用隨機抽樣法抽取武漢地區(qū)227名18-25歲青年女性作為樣本,采用三維人體掃描儀與手工測量相結合的方法獲取人體腰臀部相關數(shù)據(jù),并選取與腰臀部形態(tài)最為相關的23項指標參數(shù),采用SPSS軟件對指標參數(shù)進行科學的統(tǒng)計分析,首先,對采集的數(shù)據(jù)進行預處理,剔除異常值5個,最終保留222個樣本數(shù)據(jù),建立人體腰臀部數(shù)據(jù)文件。其次,對數(shù)據(jù)進行科學的數(shù)理統(tǒng)計分析,運用SPSS軟件對指標數(shù)據(jù)進行相關性分析,獲得腰臀部數(shù)據(jù)之間的相關性,然后隨機選擇顯著相關的腰厚、腰寬兩個數(shù)據(jù)進行偏相關檢驗,發(fā)現(xiàn)顯著相關的兩者之間存在別的因素的影響,說明不能直接利用相關性分析進行分類,因此本課題對數(shù)據(jù)進行KMO檢驗,驗證結果KMO為0.799可以進行因子分析,通過正交旋轉法最終提取腰臀部相關的五大因子。再次以腹凸傾斜角(α)為腰臀部初次分類的指標,將腰臀部初分為A、B、C、D、E 5類,由于A、E兩類只占樣本總量的2%和4%,樣本量過少,無法在進行細分,因此本課題運用K-均值聚類法將B、C、D 3類聚類為15類,因在一定檔差范圍內(nèi),可合并為一類,最終,將腰臀部細分為6類。最后,在腰臀部體型分類的基礎上,結合斜裙及褲裝的造型特點,進一步研究影響斜裙外觀形態(tài)的相關性因素,最終獲得最佳的斜裙穿著效果;研究影響褲裝合體性的關鍵性因素,通過局部調(diào)節(jié)褲裝版型,最終實現(xiàn)合體女褲的版型優(yōu)化。
[Abstract]:With the development of society, people have higher and higher requirements for clothing fit and comfort. Clothing is "people-oriented", and the size data of human body can provide an accurate scientific basis for the study of clothing structure. The research of human body shape is the foundation of clothing structure research. This subject obtains the detailed database of human waist and buttocks by 3D human body scanning, and simulates the features of waist and hip shape by SPSS analysis and image superposition of cross section. The effect of somatotype classification on the underfitting structure was studied. 227 young women aged 18 to 25 years old in Wuhan were sampled by random sampling method. The data of waist and hip of human body were obtained by combining 3D human body scanner with manual measurement. At the same time, 23 index parameters which are most related to the shape of waist and hip are selected, and the index parameters are analyzed scientifically by SPSS software. Firstly, the collected data are preprocessed, 5 abnormal values are eliminated, and 222 sample data are retained. Create a data file for the waist and hip of the human body. Secondly, the data are analyzed scientifically by mathematical statistics, and the correlation between the data of waist and hip is obtained by using SPSS software, and then the significant correlation of waist thickness is randomly selected. Two data of waist width were tested by partial correlation test, and it was found that there were other factors between the two data, which indicated that the correlation analysis could not be directly used to classify the data. Therefore, KMO test was carried out on the data in this paper. The results showed that KMO of 0.799 could be used for factor analysis, and the five factors related to waist and hip were extracted by orthogonal rotation method. Again, with the angle of inclination (偽) of abdominal kyphoid as the index of the first classification of waist and buttock, the waist and buttocks are initially divided into two categories: Agna Bu Che DU E 5. Because the two categories of Agna E only account for 2% and 4% of the total sample, the sample size is too small to be subdivided. Therefore, in this paper, the K-means clustering method is used to classify BCU D3 into 15 classes, which can be merged into a class within a certain range of differences, and finally, the waist and hip are subdivided into 6 classes. Finally, on the basis of the classification of waist and hip shape, combined with the shape characteristics of oblique skirt and trousers, the paper further studies the related factors that affect the appearance of oblique skirt, and finally obtains the best wearing effect of oblique skirt. The key factors affecting the fit of trousers are studied, and the pattern optimization of trousers is realized by adjusting the pattern of trousers.
【學位授予單位】：武漢紡織大學
【學位級別】：碩士
【學位授予年份】：2017
【分類號】：TS941.17
本文編號：2339731
[Abstract]:With the development of society, people have higher and higher requirements for clothing fit and comfort. Clothing is "people-oriented", and the size data of human body can provide an accurate scientific basis for the study of clothing structure. The research of human body shape is the foundation of clothing structure research. This subject obtains the detailed database of human waist and buttocks by 3D human body scanning, and simulates the features of waist and hip shape by SPSS analysis and image superposition of cross section. The effect of somatotype classification on the underfitting structure was studied. 227 young women aged 18 to 25 years old in Wuhan were sampled by random sampling method. The data of waist and hip of human body were obtained by combining 3D human body scanner with manual measurement. At the same time, 23 index parameters which are most related to the shape of waist and hip are selected, and the index parameters are analyzed scientifically by SPSS software. Firstly, the collected data are preprocessed, 5 abnormal values are eliminated, and 222 sample data are retained. Create a data file for the waist and hip of the human body. Secondly, the data are analyzed scientifically by mathematical statistics, and the correlation between the data of waist and hip is obtained by using SPSS software, and then the significant correlation of waist thickness is randomly selected. Two data of waist width were tested by partial correlation test, and it was found that there were other factors between the two data, which indicated that the correlation analysis could not be directly used to classify the data. Therefore, KMO test was carried out on the data in this paper. The results showed that KMO of 0.799 could be used for factor analysis, and the five factors related to waist and hip were extracted by orthogonal rotation method. Again, with the angle of inclination (偽) of abdominal kyphoid as the index of the first classification of waist and buttock, the waist and buttocks are initially divided into two categories: Agna Bu Che DU E 5. Because the two categories of Agna E only account for 2% and 4% of the total sample, the sample size is too small to be subdivided. Therefore, in this paper, the K-means clustering method is used to classify BCU D3 into 15 classes, which can be merged into a class within a certain range of differences, and finally, the waist and hip are subdivided into 6 classes. Finally, on the basis of the classification of waist and hip shape, combined with the shape characteristics of oblique skirt and trousers, the paper further studies the related factors that affect the appearance of oblique skirt, and finally obtains the best wearing effect of oblique skirt. The key factors affecting the fit of trousers are studied, and the pattern optimization of trousers is realized by adjusting the pattern of trousers.
【學位授予單位】：武漢紡織大學
【學位級別】：碩士
【學位授予年份】：2017
【分類號】：TS941.17
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