15th European Conference on Artificial Intelligence
|July 21-26 2002 Lyon France|
Serge Boverie, Didier Dubois, Xavier Guérandel, Olivier de Mouzon, Henri Prade
A causal diagnosis solution relying on experts' knowledge concentrates on the different malfunctions that may disturb the data acquisition process and tells the engine dyno test bench tuning engineer which malfunction has occurred or which malfunctions are most likely suspected. The use of fuzzy sets and possibility theory provides better feedback and knowledge representation. The general architecture of the system is described, and a prototype of the fault-diagnosis part of this system is presented. It concerns the implementation of an (off-line) automatic knowledge formalization system and the implementation of the (on-line) possibilistic causal diagnosis process.
Citation: Serge Boverie, Didier Dubois, Xavier Guérandel, Olivier de Mouzon, Henri Prade: Online Diagnosis of Engine Dyno Test Benches: A Possibilistic Approach. In F. van Harmelen (ed.): ECAI2002, Proceedings of the 15th European Conference on Artificial Intelligence, IOS Press, Amsterdam, 2002, pp.658-662.