Fault diagnosis with dynamic fuzzy discrete event system approach

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.


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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.