PREDICTION OF DRAPE COEFFICIENT BY ARTIFICIAL NEURAL NETWORK

被引：8
|
作者：
Ghith, Adel [1 ,2 ]
Hamdi, Thouraya [1 ,3 ]
Fayala, Faten [1 ,3 ]
机构：
[1] Univ Monastir, Natl Engn Sch, Text Dept, Monastir 5019, Tunisia
[2] Univ Monastir, ATSI Res Unit Automat Signal & Image Anal, Monastir 5019, Tunisia
[3] Univ Monastir, Lab Energet & Therm Syst, LESTE, Monastir 5019, Tunisia
来源：
AUTEX RESEARCH JOURNAL | 2015年 / 15卷 / 04期
关键词：
Bending rigidity; drape coefficient; neural networks; back-propagation; MECHANICAL-PROPERTIES; FABRIC-DRAPE;
D O I：
10.1515/aut-2015-0045
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：
An artificial neural network (ANN) model was developed to predict the drape coefficient (DC). Hanging weight, Sample diameter and the bending rigidities in warp, weft and skew directions are selected as inputs of the ANN model. The ANN developed is a multilayer perceptron using a back-propagation algorithm with one hidden layer. The drape coefficient is measured by a Cusick drape meter. Bending rigidities in different directions were calculated according to the Cantilever method. The DC obtained results show a good correlation between the experimental and the estimated ANN values. The results prove a significant relationship between the ANN inputs and the drape coefficient. The algorithm developed can easily predict the drape coefficient of fabrics at different diameters.
引用
收藏
页码：266 / 274
页数：9
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