Fault Detection and Classification using Kalman Filter and Hybrid Neuro-Fuzzy Systems

Abstract

In this paper, an efficient scheme to detect and classify faults in a system using kalman filtering and hybrid neuro-fuzzy computing techniques, respectively, is proposed. A fault is detected whenever the moving average of the Kalman filter residual exceeds a threshold value. The fault classification has been made effective by implementing a hybrid neuro… (More)

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