Abstract
A neural network approach for online detection and isolation of faults in rotating machines is proposed. The methodology is based on clustering of shaft vibration monitoring data by using fuzzy ART neural networks. Fault isolation is obtained by retrieving stored associations among known physical faults and clusters. The proposed scheme is implemented to detect and isolate different operation modes in an hydro generator.
Published Version
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