• DocumentCode
    1926840
  • Title

    Fault Diagnosis of Induction Motor using Neural Networks

  • Author

    He, Qing ; Du, Dong-mei

  • Author_Institution
    North China Electr. Power Univ., Beijing
  • Volume
    2
  • fYear
    2007
  • fDate
    19-22 Aug. 2007
  • Firstpage
    1090
  • Lastpage
    1095
  • Abstract
    The fault diagnosis theory and its methods for inductor motor are summarized. Based on the method of current spectrum, a neural network method to diagnose the broken bar number of inductor motor is presented. The training patterns and the diagnosis results for the neural network are given. The broken bar number of inductor motor is diagnosed directly according to the working status parameters. The method is high intelligent and very reliable.
  • Keywords
    fault diagnosis; induction motors; neural nets; broken bar number; current spectrum; fault diagnosis; induction motor; neural networks; Circuit faults; Electric motors; Fault diagnosis; Frequency; Induction motors; Inductors; Magnetic flux; Neural networks; Rotors; Stator windings; Broken bar; Fault diagnosis; Induction motor; Neural networks;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Machine Learning and Cybernetics, 2007 International Conference on
  • Conference_Location
    Hong Kong
  • Print_ISBN
    978-1-4244-0973-0
  • Electronic_ISBN
    978-1-4244-0973-0
  • Type

    conf

  • DOI
    10.1109/ICMLC.2007.4370306
  • Filename
    4370306