• 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