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