Using gated experts in fault diagnosis and prognosis
Using gated experts in fault diagnosis and prognosis
01 August 2004
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.
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File Name : Using Gated Experts in Fault Diagnosis and Prognosis 2004.pdf