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
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;
Conference_Titel :
Information Processing, 2009. APCIP 2009. Asia-Pacific Conference on
Conference_Location :
Shenzhen
Print_ISBN :
978-0-7695-3699-6
DOI :
10.1109/APCIP.2009.66
