• DocumentCode
    2667744
  • Title

    Recognition of pump state by RBF neural network

  • Author

    Wu, Jimei ; Wu, Qiumin

  • Author_Institution
    Dept. of Printing Eng., Xi´´an Univ. of Technol.
  • fYear
    0
  • fDate
    0-0 0
  • Firstpage
    224
  • Lastpage
    227
  • Abstract
    The arising of neural network theory is a breakthrough from machine processing to man´s thinking mode. On the basis of the traditional BP and RBF neural network, this article applies a new algorithm user-defined step radial basis function to recognize ZYB03-60 vacuum air press pump. It turns out that the algorithm can train studying-speed faster and it is of good self-adaptation to data
  • Keywords
    mechanical engineering computing; radial basis function networks; vacuum pumps; RBF neural network; pump state recognition; user-defined step radial basis function; vacuum air press pump; Blades; Character recognition; Frequency; Friction; Monitoring; Neural networks; Printing; Pumps; Temperature; Testing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Robotics and Biomimetics (ROBIO). 2005 IEEE International Conference on
  • Conference_Location
    Shatin
  • Print_ISBN
    0-7803-9315-5
  • Type

    conf

  • DOI
    10.1109/ROBIO.2005.246267
  • Filename
    1708626