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A Novel Method of Model-based Diagnosis by Propagating Failure Value


Dantong Ouyang, Liming Zhang, Xiangfu Zhao


Vol. 7  No. 11  pp. 263-267


Model-based diagnosis is a new intelligent diagnostic technique which can overcome the shortcomings of traditional diagnostic methods. In this paper, a novel method of propagating failure value in model-based diagnosis is proposed, and the computing procedure is characterized by combining revised SE-tree (set enumeration tree) with closed nodes to produce all the diagnoses. It can directly compute all minimal diagnoses (MDs), without computing all the conflict sets and therefore the hitting sets of the collection of the corresponding conflict sets like the classical methods, and then the combinatorial explosion caused by calling ATMS, known as an NP-complete problem, can be avoided as well. As the closed nodes are added into the SE-tree, the non-minimal diagnoses can never be produced, and the true resolutions can not be missed by pruning either. The program is easy to be realized, and the diagnosis efficiency is highly improved by this method to satisfy real-time requirement, even for a complex system.


model-based diagnosis, minimal diagnosis, set enumeration tree (SE-tree), failure value