• 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