DocumentCode
3516265
Title
Predicting Cotton Yarn Hairiness in Rotor Spinning
Author
Bo, Zhao
Author_Institution
Coll. of Textiles, Zhongyuan Univ. of Technol., Zhengzhou, China
Volume
2
fYear
2010
fDate
11-12 Nov. 2010
Firstpage
127
Lastpage
130
Abstract
Yarn hairiness is an important yarn property like yarn evenness and strength. This property is affected by many fiber performances and processing parameters, which makes its prediction difficult also. In this study, we predicted the hairiness of the cotton yarn in rotor spinning using the ANN model. On the basis of the results obtained, with help of ANN analysis, we can predict the hairiness of the cotton easily and accurately. The results show that the ANN model yields more accurate and stable predictions, which indicates that the ANN theory is an effective and viable modeling method.
Keywords
cotton fabrics; neural nets; production engineering computing; rotors; spinning (textiles); spinning machines; yarn; ANN model; artificial neural network; cotton yarn hairiness; rotor spinning; yarn evenness; yarn property; yarn strength; artificial neural network; cotton; hairiness; prediction; rotor spun; yarn;
fLanguage
English
Publisher
ieee
Conference_Titel
Optoelectronics and Image Processing (ICOIP), 2010 International Conference on
Conference_Location
Haiko
Print_ISBN
978-1-4244-8683-0
Type
conf
DOI
10.1109/ICOIP.2010.264
Filename
5663233
Link To Document