Title :
Prediction of Hairiness of Polyester/Viscose/Cotton Blended Ring Spinning Yarn
Author_Institution :
Coll. of Textiles, Zhongyuan Univ. of Technol., Zhengzhou, China
Abstract :
The objective of this research is to predict the hairiness of polyester/viscose/cotton yarn by means of two modeling methods (multiple regression model and artificial neural network model). The hairiness of ring spun yarn is influenced by processing parameters (front roller speed, spindle speed, nip gauge, back draft zone time, and roving twist). Excellent agreement is obtained between these two approaches. The results show that the artificial neural network (ANN) gave reliable results than that of multiple regression models, which is an excellent method for predictors.
Keywords :
cotton fabrics; neural nets; production engineering computing; regression analysis; spinning (textiles); yarn; ANN model; artificial neural network; multiple regression model; polyester-viscose-cotton yarn; ring spinning; yarn hairiness prediction; artificial neural network; hairiness; polyester/viscose/ cotton; prediction; regression model; ring yarn;
Conference_Titel :
Optoelectronics and Image Processing (ICOIP), 2010 International Conference on
Conference_Location :
Haiko
Print_ISBN :
978-1-4244-8683-0
DOI :
10.1109/ICOIP.2010.263