• DocumentCode
    2975348
  • Title

    Intelligent Control System of Deep Drawing for Rectangular Box

  • Author

    Ma, Rui ; Zhao, Jun

  • Author_Institution
    Coll. of Mech. Eng., Yanshan Univ., Qinhuangdao, China
  • fYear
    2010
  • fDate
    25-27 June 2010
  • Firstpage
    5285
  • Lastpage
    5288
  • Abstract
    Based on the research achievements of intelligent deep drawing for an axis-symmetric part, the key technologies of intelligent deep drawing for a rectangular box are discussed in this paper. Signal monitoring and control can be realized nicely in the process of deep drawing by applying the technology of LabVIEW VI (virtual instrument). Real-time identification of material properties can be achieved with artificial neural network, and the network error is stepped downward to 2% by the application of LM (Levenberg-Marquarat) optimization algorithm. The real time predication of optimized processing parameters comes true based on predictive principle, in which the error of predication is within 10%. Based on the concept of real time monitoring, real time identifying, real time predicating and real time controlling, a control system of intelligent deep drawing for rectangular box has been developed recently.
  • Keywords
    deep drawing; neurocontrollers; process control; production engineering computing; virtual instrumentation; LabVIEW VI; Levenberg-Marquarat optimization algorithm; artificial neural network; axis-symmetric part; intelligent control system; intelligent deep drawing; material property; real time controlling; real time identifying; real time monitoring; real time predicating; rectangular box; signal monitoring; virtual instrument; Artificial intelligence; Artificial neural networks; Force; Intelligent control; Mechanical engineering; Parameter estimation; Real time systems; artificial neural network; deep drawing; intelligent control system; rectangular box;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Electrical and Control Engineering (ICECE), 2010 International Conference on
  • Conference_Location
    Wuhan
  • Print_ISBN
    978-1-4244-6880-5
  • Type

    conf

  • DOI
    10.1109/iCECE.2010.1283
  • Filename
    5629630