• DocumentCode
    496854
  • Title

    Research of Failure Detection Based on the Intelligent Information Fusion Technology

  • Author

    Long, Hao ; Wu, Xuetao ; Song, Shujie

  • Author_Institution
    Coll. of Automatics, Beijing Union Univ., Beijing, China
  • Volume
    1
  • fYear
    2009
  • fDate
    18-19 July 2009
  • Firstpage
    233
  • Lastpage
    236
  • Abstract
    The new failure detection algorithm based on intelligent information fusion is proposed, in which the non-stationary signalpsilas growth of residual error is suppressed; In order to enhance the Signal-to-Noise of weak information of residual errors, the wavelet frequency-signal analyzing technology is adopted to separate the non-stationary noise; The artificial neural network is used to eliminate the influence of the non-linear deviation signal to the residual error decision, so the applicable scope of the algorithm is expanded. The simulation results indicate that, this algorithmpsilas technical performance is superior, and the improvement effect is obvious.
  • Keywords
    neural nets; sensor fusion; wavelet transforms; artificial neural network; failure detection algorithm; intelligent information fusion technology; nonlinear deviation signal; nonstationary signal; residual error decision; residual error growth; residual error weak information; wavelet frequency-signal analyzing technology; Algorithm design and analysis; Artificial intelligence; Computer errors; Detection algorithms; Failure analysis; Frequency; Information analysis; Intelligent networks; Signal analysis; Wavelet analysis; Artificial Neural Network (ANN); Failure Detection; Intelligent Information Fusion; Wavelet Analysis;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Information Processing, 2009. APCIP 2009. Asia-Pacific Conference on
  • Conference_Location
    Shenzhen
  • Print_ISBN
    978-0-7695-3699-6
  • Type

    conf

  • DOI
    10.1109/APCIP.2009.66
  • Filename
    5197039