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纺织聚合物复合材料的分类:最新趋势与挑战

Classification of Textile Polymer Composites: Recent Trends and Challenges.

作者信息

Amor Nesrine, Noman Muhammad Tayyab, Petru Michal

机构信息

Department of Machinery Construction, Institute for Nanomaterials, Advanced Technologies and Innovation (CXI), Technical University of Liberec, 461 17 Liberec, Czech Republic.

出版信息

Polymers (Basel). 2021 Aug 4;13(16):2592. doi: 10.3390/polym13162592.

Abstract

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.

摘要

近年来,基于聚合物的纺织复合材料备受关注,并逐渐改变了汽车、建筑、航空航天和复合材料等行业的发展。在碳纤维增强复合材料制造中加入天然聚合物纤维作为增强材料,描绘了一种经济的方式,通过提供更好的粘结条件来提高其表面、结构和机械性能。几乎所有基于纺织品的产品都与质量、价格和消费者满意度相关。因此,对纺织品和纤维增强聚合物复合材料进行分类是一项具有挑战性的任务。本文重点研究了利用人工神经网络、遗传算法和模糊逻辑对纺织工艺和纤维增强聚合物复合材料中的各种问题进行分类。此外,本文还提出并详细讨论了它们与现有工艺相关的局限性以及一些相对较新的顺序分类方法。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1893/8398028/ea2f67022eff/polymers-13-02592-g001.jpg

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