Fault diagnosis with dynamic fuzzy discrete event system approach

2006-01-01
Kilic, Erdal
Karasu, Caglar
Leblebicioğlu, Mehmet Kemal
Determining faults is a challenging task in complex systems. A discrete event system (DES) or a fuzzy discrete event system (FDES) approach with a fuzzy rule-base may resolve the ambiguity in a fault diagnosis problem especially in the case of multiple faults. In this study, an FDES approach with a fuzzy rule-base is used as a means of indicating the degree and priority of faults, especially in the case of multiple faults. The fuzzy rule-base is constructed using event-fault relations. Fuzzy events occurring any time with different membership degrees are obtained using k-means clustering algorithm. The fuzzy sub-event sequences are used to construct super events. The study is concluded by giving some examples about the distinguishability of fault types (parameter, actuator) in an unmanned small helicopter.
ARTIFICIAL INTELLIGENCE AND NEURAL NETWORKS

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Citation Formats
E. Kilic, C. Karasu, and M. K. Leblebicioğlu, “Fault diagnosis with dynamic fuzzy discrete event system approach,” ARTIFICIAL INTELLIGENCE AND NEURAL NETWORKS, pp. 117–124, 2006, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/54833.