• DocumentCode
    1754023
  • Title

    Improvement and Application of a Real-timing Analog Circuit Fault Diagnosis Method

  • Author

    Hongyan, Zheng ; Hongbo, Li ; Fanjing, Zeng ; Tiefeng, Li

  • Author_Institution
    Inst. of Inf. Eng., Inf. Eng. Univ., Zhengzhou, China
  • Volume
    1
  • fYear
    2011
  • fDate
    28-29 March 2011
  • Firstpage
    155
  • Lastpage
    158
  • Abstract
    The paper first makes a thorough research on the method for analog circuit fault diagnosis based on kurtosis and negentropy, and then theoretically analyses it´s advantage and disadvantage, which is followed by introducing the idea of centroid to overcome the method´s shortcoming, making the improved method can extract the signal´s feature more efficiency. Finally, it applies the improved method to an actual circuit. The simulation result shows that the improved method not only improves the fault diagnosis ratio of neural network but also can be used in the real-timing condition such as online fault diagnosis.
  • Keywords
    analogue circuits; fault diagnosis; neural nets; kurtosis; negentropy; neural network; online fault diagnosis; real-timing analog circuit fault diagnosis method; Analog circuits; Artificial neural networks; Circuit faults; Data mining; Fault diagnosis; Feature extraction; Training; centroid; fault diagnosis; kurtosis; negentropy; neural network; real-timing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Computation Technology and Automation (ICICTA), 2011 International Conference on
  • Conference_Location
    Shenzhen, Guangdong
  • Print_ISBN
    978-1-61284-289-9
  • Type

    conf

  • DOI
    10.1109/ICICTA.2011.47
  • Filename
    5750579