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Fabric hand evaluation through yarn surface analysis using mechanical stylus profilometry.

机译:通过使用机械测针轮廓仪进行纱线表面分析来评估织物手感。

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摘要

Fabric hand is an important characteristic to the textile industry. Fabric hand is influenced by fiber parameters including flexural rigidity and friction. It is also influenced by yarn parameters such as count, twist, CV%, hairiness, stiffness and softness. This study deals primarily with predicting the hand of knitted T-shirts from yam quality parameters. The work consists of a short literature review on the existing yarn parameters as well as fabric hand evaluation and prediction techniques. Roughness measurement and the latest development in measuring the roughness of textile material surfaces are also covered. Additionally, the two main components of softness, bulk and surface softness, are discussed. Subjective and objective hand evaluations are clarified and reviewed.; A device named the Mechanical Stylus Surface Analyzer (MSSA) that was previously developed to test the surface of paper tissues is discussed. In this work, the MSSA is modified to measure yarn surface characteristics. Using the surface profile as tested by the MSSA a novel yarn surface analysis parameter named Surface Response Average (SRA) was developed. A model for the fiber stylus-tip interaction was also developed. Ten T-shirts were produced from 10 different yarn samples and the T-shirts were ranked based on their hand by a panel of judges. The yarns used to make these T-shirts were tested by Uster III and MSSA.; The T-shirts were classified based on yarn parameters using linear and tree modeling techniques. The result shows that SRA has a correlation of 0.6 with fabric hand. When classifying the T-shirts to 3 classes of low, medium and high hand, the linear model has a classification rate of 69%. However using tree modeling it is possible to obtain a classification rate of 93% which is considered a significant result. It is therefore concluded that SRA is an important yarn surface parameter that can be used to predict fabric hand.
机译:织物手感是纺织工业的重要特征。织物手感受包括弯曲刚度和摩擦力在内的纤维参数的影响。它也受纱线参数的影响,例如支数,捻度,CV%,毛羽,刚度和柔软度。这项研究主要涉及根据纱线质量参数预测针织T恤的手感。这项工作包括对现有纱线参数以及织物手感评估和预测技术的简短文献综述。还介绍了粗糙度测量和测量纺织材料表面粗糙度的最新进展。另外,还讨论了柔软度的两个主要组成部分,膨松度和表面柔软度。明确和评估主观和客观的手部评估。讨论了一种名为机械测针表面分析仪(MSSA)的设备,该设备先前已开发用于测试纸巾的表面。在这项工作中,对MSSA进行了修改以测量纱线表面特性。使用由MSSA测试的表面轮廓,开发了一种名为表面响应平均值(SRA)的新型纱线表面分析参数。还开发了纤维笔针尖相互作用的模型。十个T恤衫是由10种不同的纱线样品制成的,并且由一个评审团根据他们的手来对T恤衫进行排名。用于制作这些T恤的纱线已通过Uster III和MSSA测试。使用线性和树模型技术根据纱线参数对T恤进行分类。结果表明,SRA与织物手感的相关性为0.6。将T恤衫分为低,中,高手三类时,线性模型的分类率为69%。但是,使用树模型可以实现93%的分类率,这被认为是重要的结果。因此可以得出结论,SRA是可用于预测织物手感的重要纱线表面参数。

著录项

  • 作者

    Peykamian, Shahram.;

  • 作者单位

    North Carolina State University.;

  • 授予单位 North Carolina State University.;
  • 学科 Textile Technology.
  • 学位 Ph.D.
  • 年度 1995
  • 页码 179 p.
  • 总页数 179
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 轻工业、手工业;
  • 关键词

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