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 :
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