Predicting the unevenness of polyester/viscose blended open-end rotor spun yarns using artificial neural network and statistical models

被引:21
|
作者
Demiryurek, Oguz [1 ]
Koc, Erdem [2 ]
机构
[1] Cukurova Univ, Dept Text Engn, TR-01330 Balcali, Turkey
[2] Ondokuz Mayis Univ, Dept Mech Engn, TR-55139 Kurupelit, Turkey
关键词
OE-rotor spinning; Polyester/viscose blend; Unevenness; Simplex lattice design; Artificial neural network; ELONGATION;
D O I
10.1007/s12221-009-0237-z
中图分类号
TB3 [工程材料学]; TS1 [纺织工业、染整工业];
学科分类号
0805 ; 080502 ; 0821 ;
摘要
In this study, an artificial neural network (ANN) and a statistical model are developed to predict the unevenness of polyester/viscose blended open-end rotor spun yarns. Seven different blend ratios of polyester/viscose slivers are produced and these slivers are manufactured with four different rotor speed and four different yarn counts in rotor spinning machine. A back propagation multi layer perceptron (MLP) network and a mixture process crossed regression model (simplex lattice design) with two mixture components (polyester and viscose blend ratios) and two process variables (yarn count and rotor speed) are developed to predict the unevenness of polyester/viscose blended open-end rotor spun yarns. Both ANN and simplex lattice design have given satisfactory predictions, however, the predictions of statistical models gave more reliable results than ANN.
引用
收藏
页码:237 / 245
页数:9
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