Green Technology used in Finishing Process Study of the Wrinkled Cotton Fabric by Radial Basis Function neurons. (Experimental and Modeling analysis)

M. S. Hesarian, J. Tavoosi
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引用次数: 1

Abstract

The wrinkling of cotton fabric is an important factor that affects a garment's appearance. This paper evaluated the use of a non-toxic green anti-wrinkle material in the finishing process to address this issue. For this purpose, the chemical structure of the wrinkled cotton sample was evaluated and treated with a scouring and anti-creasing finishing material. Due to the environmental issues created by the toxic material used as finishes, the type of anti-wrinkle material used in this study had the least possible environmental impact. The mechanism of this anti-crease finishing was based on the crosslinking of cellulose molecular chains. This process limited the chain movements made by wrinkling. Accordingly, the effect of the mentioned mechanism and structural parameters such as the thickness, weight, density of the weft yarn, and linear density of the weft yarn (Ne) were evaluated. The wrinkle degree of the samples was analyzed by using a radial basis function neural network (RBFN). This RBFN modeled the relationships between the degree of wrinkling in the fabrics and the mentioned parameters, especially the anti-crease finishing of the samples. The simulation results confirmed the effectiveness of the proposed method.
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基于径向基函数神经元的绿色技术在皱褶棉织物整理工艺研究中的应用。(实验与建模分析)
棉织物起皱是影响服装外观的重要因素。本文评价了在整理过程中使用无毒绿色抗皱材料来解决这一问题。为此,对皱褶棉样品的化学结构进行了评价,并用一种精练和抗皱整理材料进行了处理。由于使用有毒材料作为饰面所造成的环境问题,本研究中使用的抗皱材料类型对环境的影响最小。这种抗皱整理的机理是基于纤维素分子链的交联。这一过程限制了链条因起皱而产生的运动。据此,评价了上述机理和结构参数如纬纱粗细、重、密度和纬纱线密度(Ne)的影响。采用径向基函数神经网络(RBFN)对试样的起皱程度进行分析。该RBFN模拟了织物的起皱程度与上述参数之间的关系,特别是样品的抗皱整理。仿真结果验证了该方法的有效性。
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