Neural model of the spinning process dedicated to predicting properties of cotton-polyester blended yarns on the basis of the characteristics of feeding streams

被引：0

作者：

Jackowska-Strumillo, Lidia ^{[1
]}

Cyniak, Danuta ^{[2
]}

Czekalski, Jerzy ^{[2
]}

Jackowski, Tadeusz ^{[2
]}

机构：

[1] Computer Engineering Department, Technical University of Lódź, Al. Politechniki 11, 90-942 Lódź, Poland

[2] Department of Spinning Technology and Yarn Structure, Technical University of Lódź, ul. Zeromskiego 116, 90-543 Lódź, Poland

来源：

Fibres and Textiles in Eastern Europe | 2008年 / 16卷 / 01期

关键词：

Linear regression - Neural networks - Spinning (fibers) - Structural optimization - Wool - Yarn;

D O I：

暂无

中图分类号：

学科分类号：

摘要：

The subject of our research were yarns manufactured from cotton-polyester blended slivers, as well as pure cotton and polyester slivers wilh the use of a BD 200S rotor spinning frame. Partial models of the spinning process were developed for selected, essential yarn quality parameters, such as tenacity, irregularity of yarn's mass, hairiness, number of yarn faults (number of thin and thick places and number of neps). In order to model the variability of these parameters, the following methods were used: linear and linearised regression, non-linear multiple regression as well as ADALINE and two-layer perceptron (MLP) artificial neural networks. The best results of approximation we obtained using the MLP network. Selection of the optimum network structure was carried out for each of the parameters. A hybrid model was used to model the variability of the CV coefficient.

引用

页码：28 / 36