武汉青年女性腰臀部形态及其合体下装结构研究

发布时间：2018-11-18 10:01

【摘要】：随着社会的发展,人们对服装合体性、舒适性的要求越来越高,服装是“以人为本”,人体的尺寸数据可以为服装结构的研究提供准确的科学依据,人体体型研究是服装结构研究的基础,本课题通过三维人体扫描获取人体腰臀部详细的数据库,通过SPSS分析及横截面的图像叠加模拟腰臀部体型特征,通过体型分类研究其对合体下装结构的影响。采用随机抽样法抽取武汉地区227名18-25岁青年女性作为样本,采用三维人体扫描仪与手工测量相结合的方法获取人体腰臀部相关数据,并选取与腰臀部形态最为相关的23项指标参数,采用SPSS软件对指标参数进行科学的统计分析,首先,对采集的数据进行预处理,剔除异常值5个,最终保留222个样本数据,建立人体腰臀部数据文件。其次,对数据进行科学的数理统计分析,运用SPSS软件对指标数据进行相关性分析,获得腰臀部数据之间的相关性,然后随机选择显著相关的腰厚、腰宽两个数据进行偏相关检验,发现显著相关的两者之间存在别的因素的影响,说明不能直接利用相关性分析进行分类,因此本课题对数据进行KMO检验,验证结果KMO为0.799可以进行因子分析,通过正交旋转法最终提取腰臀部相关的五大因子。再次以腹凸倾斜角(α)为腰臀部初次分类的指标,将腰臀部初分为A、B、C、D、E 5类,由于A、E两类只占样本总量的2%和4%,样本量过少,无法在进行细分,因此本课题运用K-均值聚类法将B、C、D 3类聚类为15类,因在一定档差范围内,可合并为一类,最终,将腰臀部细分为6类。最后,在腰臀部体型分类的基础上,结合斜裙及裤装的造型特点,进一步研究影响斜裙外观形态的相关性因素,最终获得最佳的斜裙穿着效果;研究影响裤装合体性的关键性因素,通过局部调节裤装版型,最终实现合体女裤的版型优化。
[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 (伪) 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.
【学位授予单位】：武汉纺织大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：TS941.17

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