DocumentCode :
2253895
Title :
Using gated experts in fault diagnosis and prognosis
Author :
Berenji, Hamid ; Wang, Yan ; Vengerov, David ; Langari, Rem ; Jamshidi, Mo
Author_Institution :
Intelligent Inference Syst. Corp, Moffett Field, CA, USA
Volume :
1
fYear :
2004
fDate :
25-29 July 2004
Firstpage :
463
Abstract :
Three individual experts have been developed based on extended auto associative neural networks (E-AANN), Kohonen self organizing maps (KSOM), and the radial basis function based clustering (RBFC) algorithms. An integrated method is proposed later to combine the set of individual experts managed by a gated experts algorithm, which assigns the experts based on their best performance regions. We have used a Matlab Simulink model of a chiller system and applied the individual experts and the integrated method to detect and recover sensor errors. It has been shown that the integrated method gets better performance in diagnostics and prognostics compared with each individual expert.
Keywords :
fault diagnosis; mathematics computing; pattern clustering; radial basis function networks; self-organising feature maps; sensors; Kohonen self organizing map; Matlab Simulink model; chiller system; extended auto associative neural network; fault diagnosis; fault prognosis; gated experts algorithm; radial basis function based clustering algorithm; sensor error; Clustering algorithms; Control engineering; Fault detection; Fault diagnosis; Intelligent systems; Mathematical model; NASA; Neural networks; Pattern recognition; Self organizing feature maps;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Fuzzy Systems, 2004. Proceedings. 2004 IEEE International Conference on
ISSN :
1098-7584
Print_ISBN :
0-7803-8353-2
Type :
conf
DOI :
10.1109/FUZZY.2004.1375773
Filename :
1375773
Link To Document :
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