Fault diagnosis using neuro-fuzzy network and Dempster-Shafer theory

This paper focuses on fault diagnosis using neuro-fuzzy network. It is shown that less reliable result may be derived as the network takes no consideration of previous state information in online fault diagnosis. To solve this problem, we combine a modified neuro-fuzzy network with the evidence update theory. Besides, a new updating rule that combining the Jeffery-like rule and linear combination rule is given. Simulation shows the effectiveness of this fault diagnosis method.