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The Effect of Fiber Properties on the Characteristics of Spliced Yarns Part I: Prediction of Spliced Yarns Tensile Properties

机译:纤维性能对拼接纱特性的影响第一部分:拼接纱拉伸性能的预测

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Abstract In this study, the effects of splicing parameters, fiber and yarn properties on the tenacity and elongation of spliced yarns were investigated in detail. For this purpose, yarns from eight different cotton types, having three different counts (29.5, 19.7 and 14.8 tex) and three different twist coefficients (α^sub tex^ 3653, α^sub tex^ 4038, α^sub tex^ 4423) were produced. Fiber properties measured using an Advanced Fiber Information System fiber tester were evaluated. Artificial neural network and response surface models were used to analyze spliced yarn tenacity and elongation as dependent variables. As independent variables, fiber properties together with the machine settings such as opening air, splicing air and splicing time, yarn twist and yarn count were chosen. As a result of the study, equations and neural network models that predict the tenacity and elongation of the spliced yarns were obtained. The obtained equations and models are statistically important and have high coefficient of multiple determination (R^sup 2^).
机译:摘要研究了拼接参数,纤维和纱线性能对拼接纱线的韧度和伸长率的影响。为此,来自八种不同棉种的纱线具有三种不同的支数(29.5、19.7和14.8 tex)和三种不同的捻系数(α^ sub tex ^ 3653,α^ sub tex ^ 4038,α^ sub tex ^ 4423)被生产了。评估了使用Advanced Fiber Information System纤维测试仪测得的纤维性能。人工神经网络和响应面模型用于分析拼接纱线的韧度和伸长率作为因变量。作为独立变量,选择纤维特性以及机器设置,例如开放空气,拼接空气和拼接时间,纱线捻度和纱线支数。作为研究的结果,获得了预测拼接纱线的韧性和伸长率的方程式和神经网络模型。所获得的方程和模型具有统计意义,并且具有较高的多重确定系数(R ^ sup 2 ^)。

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