• DocumentCode
    514987
  • Title

    Fault Diagnosis of Asynchronous Induction Motor Based on BP Neural Network

  • Author

    Zhao Xiaodong ; Tang Xinliang ; Zhao Juan ; Zhang Yubin

  • Author_Institution
    Hebei Univ. of Sci. & Technol., Shijiazhuang, China
  • Volume
    2
  • fYear
    2010
  • fDate
    13-14 March 2010
  • Firstpage
    236
  • Lastpage
    239
  • Abstract
    For asynchronous induction motor, it is necessary to carry out fault diagnosis in time. The traditional fault diagnosis methods have the shortcomings such as the diagnosis slow speed, low accuracy. In this paper, for the common fault characteristics of asynchronous induction motor, the fault diagnosis method based on improved BP algorithm, by using of the diagnosis model, is adopted to diagnose the faults of asynchronous induction motor. The simulated experimental results show that the diagnosis method, a quicker diagnosis and a higher accuracy, is feasible. It can enhance the fault recognition rate and provide an effective amelioration method for keeping equipment reliable and efficient displaying functions.
  • Keywords
    backpropagation; electric machine analysis computing; fault diagnosis; induction motors; neural nets; BP algorithm; BP neural network; amelioration method; asynchronous induction motor; diagnosis method; diagnosis model; fault diagnosis methods; fault recognition rate; Artificial intelligence; Fault diagnosis; Feedforward systems; Frequency; Induction motors; Neural networks; Neurons; Signal analysis; Testing; Time measurement; Asynchronous Induction Motor; BP Algorithm; Fault Diagnosis; Neural Network;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Measuring Technology and Mechatronics Automation (ICMTMA), 2010 International Conference on
  • Conference_Location
    Changsha City
  • Print_ISBN
    978-1-4244-5001-5
  • Electronic_ISBN
    978-1-4244-5739-7
  • Type

    conf

  • DOI
    10.1109/ICMTMA.2010.417
  • Filename
    5460051