Classification of Textile Polymer Composites: Recent Trends and Challenges
Status PubMed-not-MEDLINE Jazyk angličtina Země Švýcarsko Médium electronic
Typ dokumentu časopisecké články, přehledy
Grantová podpora
CZ.02.1.01/0.0/0.0/16?025/0007293
European Union (European Structural and Investment Funds-Operational Programme Research, Development and Education)
PubMed
34451132
PubMed Central
PMC8398028
DOI
10.3390/polym13162592
PII: polym13162592
Knihovny.cz E-zdroje
- Klíčová slova
- Sequential Monte Carlo methods, artificial neural network, classification, fiber reinforced polymer composites, fuzzy logic,
- Publikační typ
- časopisecké články MeSH
- přehledy MeSH
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.
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