Prediction of Mechanical Properties of Woven Fabrics by ANN

IF 0.7 4区 工程技术 Q3 MATERIALS SCIENCE, TEXTILES
Sherien N. Elkateb
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引用次数: 3

Abstract

Abstract This study aims to obtain an accurate prediction model of mechanical properties of woven fabric to achieve customer satisfaction. Samples of plain woven fabric were produced from different yarn counts and blend ratios of cotton and polyester of weft yarn at different weft densities. Mechanical properties such as tensile strength, bending stiffness and elongation% in both the warp and weft directions were tested. The prediction model was based on Artificial Neural Networks (ANNs). For each model, thirty-nine samples were used for training and fifteen for testing prediction performance. Findings indicated that the ANN achieved a perfect performance in predicting all properties.
机织物力学性能的人工神经网络预测
摘要本研究旨在获得一个准确的机织物力学性能预测模型,以达到客户满意度。用不同支数和纬纱棉与涤纶在不同纬纱密度下的混纺比例生产平纹织物样品。测试了拉伸强度、弯曲刚度和经纬向伸长率等力学性能。预测模型是基于人工神经网络的。对于每个模型,三十九个样本用于训练,十五个样本用于测试预测性能。研究结果表明,人工神经网络在预测所有特性方面都取得了完美的性能。
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来源期刊
Fibres & Textiles in Eastern Europe
Fibres & Textiles in Eastern Europe 工程技术-材料科学:纺织
CiteScore
1.60
自引率
11.10%
发文量
12
审稿时长
13.5 months
期刊介绍: FIBRES & TEXTILES in Eastern Europe is a peer reviewed bimonthly scientific journal devoted to current problems of fibre, textile and fibrous products’ science as well as general economic problems of textile industry worldwide. The content of the journal is available online as free open access. FIBRES & TEXTILES in Eastern Europe constitutes a forum for the exchange of information and the establishment of mutual contact for cooperation between scientific centres, as well as between science and industry.
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