Study On The Relations Between The Properties Of Fabrics And The Shape Of A-line Skirt

As we all know, fabric and its properties are crucial factors to the skirts design. For the gar-ments of the same style, the properties of the fabrics are determinants of the final shape. The fabric’s shaping ability means its appropriateness for the3D garments in motionless state and the ability to form the grace shape of the clothing when moving. This paper mainly studys the rela-tions between the properties of fabrics and the shape of A-line skirt. Study on the inherent laws between its Properties of Fabrics and their Shaping abilities will contribute to our master of the garments’shaping, objectively guide the production, control quality and have guiding significance for designer dresses design work.With the continuous growing of the computer technology, more and more scholars both at domestic and at abroad will use gray system, fuzzy mathematics, neural networks and data mining to study clothing drape and create new systems of the objective evaluation. And data mining which is recognized by more and more people, is experted at extracting extraordinary and implied information with potential value from the noisy database. It integrates theory and technology in many fields such as machine learning, databases, artificial intelligence and statistics. One of the most widely used applications of data mining is decision tree. It has high precision with output easy to understand. It has broad application in the medical and economical field but seldom in the field of textiles. Considering there are a large amount of noisy testing data of properties of fabrics, this paper proposes that the decision tree be applied into the field of textile to predict the performance and its impact on the ability of forming skirts.This paper chooses A-line skirt as the objective,controls variables in the least and accurately establishes two prediction models of fabric performance, which are closely related to our life With inputting different databases, two predictive models are respectively created. Trough analyzing and comparing the two models, the accuracy of the predictive results and differences between two models will be given out.The main contents and results are as follows:(1) design of test mannequin and obtain projected areaThe common mannequin just has dressing function which cannot help get the projected area underside. In order to obtain the projected area underside, so experimental mannequin has been designed. The camera and lighting is adjustable to obtain a better perspective. The projection image will be first transformed into black and white binary image through image processing of Matlab programming with Ostu threshold algorithm, and then all the pixels within the outline of the binary image can be calculated.(2)Analyze the factors affecting the shaping ability of the fabric based on the decision treeTest all the related properties that may affect the ability of forming skirts including tensile properties of bending stiffness, shear stiffness, surface friction resistance at warp and weft direction and bending rigidity at warp,weft and45°oblique direction, drape etc. After database normalizing, it creates mechanical properties of low load-A-line skirt shaping predictive models, and drape flexural stiffness-A-line skirt shaping predictive models. Important factors of mechanical properties at low load that affects the shaping index of A-line skirt (including angle, wave number, and projected area) are Warp/weft tensile power recovery, Warp tensile ratio, warp linearity, the warp/weft shear stiffness, the warp average coefficient of friction, weft/warp density, weight; the important factors of the other model have turned out to be oblique bending stiffness index, and weft/warp bending stiffness index, static drape coefficient, warp density and weight.(3) To establish two predictive models analyzing the shaping abilities of fabricsOne model, based on the mechanical properties at low load as input data and A-line skirt shape index (angle, wave number, and projected area) as the output data, predicts the shaping ability of fabric by calculating dividing point of decision tree model. Validated by the other two samples, the model has a precise prediction with small error, which is proved that has value in practice use.The other model is based on the drape performance and bending stiffness. Through two verification samples, the predicted angle indexes, wave numbers, and the projected area have been proved in some errors. The result shows its accuracy and stability are not better than the first predictive model.