DocumentCode
2952009
Title
The development of cotton-yarn-quality predicting system
Author
Xiao, Ying ; Zhao, Shulin
Author_Institution
Sch. of Textiles, Tianj in Polytech. Univ., Tianjin, China
fYear
2011
fDate
30-31 July 2011
Firstpage
1
Lastpage
4
Abstract
A new cotton-yarn-quality predicting system was developed by using the merging programming technique of VB and Matlab in the paper. Using this system, the tenacity and evenness CV% of the cotton-yarn processing by conventional spinning at standard temperature and humidity can be predicted through inputting some fiber properties into the system, such as the percentage of impurities, the principal length, the percentage of short fiber, the degree of maturity, fiber strength and the value of Micronaire. And also it was verified that the system did the good job for predicting yarn tenacity and evenness CV% exactly with the relative error of less than 4% after the model being trained. The accuracy can meet the demand of spinning factories and so the predicting results would be useful for guiding the spinning practice.
Keywords
backpropagation; cotton; humidity; neural nets; production engineering computing; quality management; spinning (textiles); tensile strength; yarn; BP neural network; Matlab; Micronaire; VB; cotton-yarn processing; cotton-yarn-quality predicting system; fiber property; fiber strength; humidity; impurity; maturity; merging programming technique; principal length; spinning factory; temperature; yarn tenacity; Mathematical model; Optical fiber networks; Predictive models; Programming; Spinning; Training; Yarn;
fLanguage
English
Publisher
ieee
Conference_Titel
Control, Automation and Systems Engineering (CASE), 2011 International Conference on
Conference_Location
Singapore
Print_ISBN
978-1-4577-0859-6
Type
conf
DOI
10.1109/ICCASE.2011.5997556
Filename
5997556
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