• DocumentCode
    344345
  • Title

    Determination of the thickness control parameters of the rolling process through the sensitivity method, using neural networks

  • Author

    Zarate, L.E. ; Helman, H.

  • Author_Institution
    Dept. of Comput. Sci., Pontificial Catholic Univ. of Minas Gerais, Brazil
  • Volume
    1
  • fYear
    1999
  • fDate
    36342
  • Firstpage
    537
  • Abstract
    The single stand rolling mill governing equation is a nonlinear function on several parameters (entry thickness, front and back tensions, average yield stress and friction coefficient, etc.). Any alteration on one of them will cause alterations on the rolling load and, consequently, on the outgoing thickness. This paper presents a method for the calculation of the appropriate adjustment on the three control parameters (roll gap, front or back tensions), in which the sensitivity equation of the process, obtained by differentiating a neural network, is used
  • Keywords
    neurocontrollers; process control; rolling mills; sensitivity analysis; steel industry; thickness control; back tension; front tension; neural networks; neurocontrol; process control; roll gap; rolling mill; sensitivity method; thickness control; Artificial neural networks; Computer science; Differential equations; Milling machines; Neural networks; Neurons; Nonlinear equations; Stress; Strips; Thickness control;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Processing and Manufacturing of Materials, 1999. IPMM '99. Proceedings of the Second International Conference on
  • Conference_Location
    Honolulu, HI
  • Print_ISBN
    0-7803-5489-3
  • Type

    conf

  • DOI
    10.1109/IPMM.1999.792535
  • Filename
    792535