• DocumentCode
    1897851
  • Title

    Application of BP Neural Network in the Control of Hydraulic Die Forging Hammer

  • Author

    Yan, Li ; Jianwei, Li ; Jun, Liu

  • Author_Institution
    Mech. & Electr. Eng. Coll., Henan Agric. Univ., Zhengzhou, China
  • Volume
    1
  • fYear
    2009
  • fDate
    10-11 Oct. 2009
  • Firstpage
    39
  • Lastpage
    41
  • Abstract
    It is an essential problem in the control of hydraulic die forging hammer that the mathematical model between deformation and forging energy, and it is nonlinear in nature. For its pretty nonlinear function approximation ability, BP neural network is suitable for resolving the problem. The architecture and the arithmetic of BP neural network were introduced. Furthermore, the BP neural network model was established. At the same time, the process and principle of the modeling also were expounded. Then, it was explained that how to use the BP neural network model in the control process. The result of experiment showed that the method takes effect very well. Other applications of BP neural network in the control of hydraulic die forging hammer was also introduced. At last, the disadvantage of the method was discussed briefly.
  • Keywords
    backpropagation; forging; hammers (machines); hydraulic systems; neurocontrollers; nonlinear functions; BP neural network; deformation; forging energy; hydraulic die forging hammer control; nonlinear function approximation; Adaptive control; Arithmetic; Automatic control; Energy resolution; Feeds; Function approximation; Mathematical model; Neural networks; Neurons; Size control; BP Neural Network; Hydraulic Die Forging Hammer; forging energy;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Computation Technology and Automation, 2009. ICICTA '09. Second International Conference on
  • Conference_Location
    Changsha, Hunan
  • Print_ISBN
    978-0-7695-3804-4
  • Type

    conf

  • DOI
    10.1109/ICICTA.2009.17
  • Filename
    5287715