@inproceedings{05c6f194830f4981a53851fef9988922,
title = "Bayesian network for fault diagnosis",
abstract = "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.",
keywords = "Bayesian networks, Bond graph, Model-based fault diagnosis, Probability reasoning",
author = "Lo, {C. H.} and Wong, {Y. K.} and Rad, {A. B.}",
note = "Publisher Copyright: {\textcopyright} 2003 EUCA.; 2003 European Control Conference, ECC 2003 ; Conference date: 01-09-2003 Through 04-09-2003",
year = "2003",
month = apr,
day = "13",
doi = "10.23919/ecc.2003.7085154",
language = "English",
series = "European Control Conference, ECC 2003",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "1381--1386",
booktitle = "European Control Conference, ECC 2003",
}