Classification of Textile Polymer Composites: Recent Trends and Challenges

被引:34
作者
Amor, Nesrine [1 ]
Noman, Muhammad Tayyab [1 ]
Petru, Michal [1 ]
机构
[1] Tech Univ Liberec, Inst Nanomat Adv Technol & Innovat CXI, Dept Machinery Construct, Liberec 46117, Czech Republic
关键词
classification; fiber reinforced polymer composites; artificial neural network; fuzzy logic; Sequential Monte Carlo methods; ARTIFICIAL NEURAL-NETWORK; PRINCIPAL COMPONENT ANALYSIS; PARTICLE FILTERING METHODS; FIBER-REINFORCED POLYMER; WOVEN BARRIER FABRICS; STATE ESTIMATION; MECHANICAL-PROPERTIES; TENSILE PROPERTIES; ELASTIC PROPERTIES; KNITTED FABRICS;
D O I
10.3390/polym13162592
中图分类号
O63 [高分子化学(高聚物)];
学科分类号
070305 ; 080501 ; 081704 ;
摘要
Polymer based textile composites have gained much attention in recent years and gradually transformed the growth of industries especially automobiles, construction, aerospace and composites. The inclusion of natural polymeric fibres as reinforcement in carbon fibre reinforced composites manufacturing delineates an economic way, enhances their surface, structural and mechanical properties by providing better bonding conditions. Almost all textile-based products are associated with quality, price and consumer's satisfaction. Therefore, classification of textiles products and fibre reinforced polymer composites is a challenging task. This paper focuses on the classification of various problems in textile processes and fibre reinforced polymer composites by artificial neural networks, genetic algorithm and fuzzy logic. Moreover, their limitations associated with state-of-the-art processes and some relatively new and sequential classification methods are also proposed and discussed in detail in this paper.
引用
收藏
页数:27
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