NDLI: Prediction system of open-end rotor spinning process based on LM-neural network for bamboo charcoal fibers

Content Provider	Springer Nature Link
Author	Su, Te Li Kuo, Chung Feng Jeffrey Wei, Hsin Jung
Copyright Year	2011
Abstract	In line with the environmental protection trends of the 21st century, bamboo charcoal fiber is invented to meet the requirements of the fields of science and technology. Its special functionalities, namely, antistatic, moisture adsorptive, perspiring, antibacterial, deodorizing, anti-radiation, and far infrared properties make it extremely suitable for applications in medicine, sports, and recreational fields, as well as an important breakthrough for environmentally-friendly textile materials. To achieve rapid manufacturing, this study processes bamboo charcoal fibers by open-end (OE) rotor spinning. The Taguchi orthogonal array is applied to the design of this experiment, and the significant factors of fibers quality are obtained through ANOVA in order to facilitate the follow-up processes of quality control. The process prediction system is built based on the test data, and is combined with the back-propagation neural network and the Levenberg-Marquardt (LM) algorithm in order to establish an OE rotor spinning process prediction system. The rotor speed, feed speed, and winding speed are set as the network input parameters, while the yarn strength, the hairiness, the unevenness, and the imperfections indicator (I.P.I.) are the output parameters. Through network learning and training, this system reports a prediction error below 5 %, proving that this prediction system has excellent predictability.
Starting Page	657
Ending Page	663
Page Count	7
File Format	PDF
ISSN	12299197
Journal	Fibers and Polymers
Volume Number	12
Issue Number	5
e-ISSN	18750052
Language	English
Publisher	The Korean Fiber Society
Publisher Date	2011-07-30
Publisher Place	Heidelberg
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Bamboo charcoal Open-end rotor spinning Taguchi method Neural network Polymer Sciences
Content Type	Text
Resource Type	Article
Subject	Chemistry Chemical Engineering Polymers and Plastics

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