• DocumentCode
    1589678
  • Title

    Fault Detection of Oil Pump Based on Fuzzy Neural Network

  • Author

    Tian, Jingwen ; Gao, Meijuan ; Cao, Liting ; Li, Kai

  • Author_Institution
    Beijing Union Univ., Beijing
  • Volume
    2
  • fYear
    2007
  • Firstpage
    636
  • Lastpage
    640
  • Abstract
    Considering the issues that the relationship between the fault of oil pump existent and fault information is a complicated and nonlinear system, and it is very difficult to found the process model to describe it. The fuzzy neural network has the advantages of both fuzzy theory and neural network. In this paper, a fault detection method of oil pump based on fuzzy neural network is presented, moreover, we construct the structure of fuzzy neural network that used for the fault detection of oil pump, and adopt the Levenberg-Marquart optimizing algorithm to train fuzzy neural network. With the ability of strong self-learning and function approach of fuzzy neural network, the detection method can truly diagnosticate the fault of oil pump by learning the fault information of oil pump. The real detection results show that this method is feasible and effective.
  • Keywords
    fault diagnosis; fuel pumps; fuzzy neural nets; mechanical engineering computing; Levenberg-Marquart optimizing algorithm; fault detection method; fault information; fuzzy neural network; fuzzy theory; nonlinear system; oil pump; Artificial neural networks; Costs; Fault detection; Fuzzy control; Fuzzy neural networks; Fuzzy systems; Neural networks; Neurons; Nonlinear systems; Petroleum;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Natural Computation, 2007. ICNC 2007. Third International Conference on
  • Conference_Location
    Haikou
  • Print_ISBN
    978-0-7695-2875-5
  • Type

    conf

  • DOI
    10.1109/ICNC.2007.375
  • Filename
    4344428