Bayesian network for fault diagnosis

C. H. Lo, Y. K. Wong, A. B. Rad

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

3 Citations (Scopus)


Fault diagnosis based on artificial intelligence techniques often deals with uncertain knowledge and incomplete input data. Probability reasoning is a method to deal with uncertain information, and Bayesian network is a tool that brings it into the real world applications. This paper describes the application of Bayesian network for diagnosing faulty components from engineered systems. A general procedure for constructing the Bayesian network structure on the basis of a bond graph model is proposed. We demonstrate how the resulting Bayesian network can be applied to fault diagnosis in an engineered system.

Original languageEnglish
Title of host publicationEuropean Control Conference, ECC 2003
PublisherInstitute of Electrical and Electronics Engineers Inc.
Number of pages6
ISBN (Electronic)9783952417379
Publication statusPublished - 13 Apr 2003
Event2003 European Control Conference, ECC 2003 - Cambridge, United Kingdom
Duration: 1 Sept 20034 Sept 2003

Publication series

NameEuropean Control Conference, ECC 2003


Conference2003 European Control Conference, ECC 2003
Country/TerritoryUnited Kingdom


  • Bayesian networks
  • Bond graph
  • Model-based fault diagnosis
  • Probability reasoning


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