NDLI: Local/global fault diagnosis of event-driven controlled systems based on probabilistic inference

Content Provider	IEEE Xplore Digital Library
Author	Inagaki, S. Suzuki, T. Saito, M. Aoki, T.
Copyright Year	2007
Description	Author affiliation: Nagoya Univ., Nagoya (Inagaki, S.; Suzuki, T.; Saito, M.)
Abstract	This paper presents a new local/global fault diagnosis strategy for the event-driven controlled systems such as the programmable logic controller (PLC). First of all, the controlled plant is decomposed into some subsystems, and the global diagnosis is formulated using the Bayesian network (BN), which represents the causal relationship between the fault and observation in subsystems. Second, the local diagnoser is developed using the conventional timed Markov model (TMM), and the local diagnosis results are used to specify the conditional probability assigned to each arc in the BN. By exploiting the local/global diagnosis architecture, the computational burden for the diagnosis can be drastically reduced. As the result, large scale diagnosis problems in the practical situation can be solved. Finally, the usefulness of the proposed strategy is verified through some experimental results of an automatic transfer line.
Starting Page	2633
Ending Page	2638
File Size	748129
Page Count	6
File Format	PDF
ISBN	9781424414970
ISSN	01912216
DOI	10.1109/CDC.2007.4434263
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2007-12-12
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Fault diagnosis Control systems Programmable control Automatic control Computer architecture Large-scale systems Bayesian methods Electrical equipment industry Production facilities USA Councils
Content Type	Text
Resource Type	Article

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