DocumentCode :
3514751
Title :
Introducing dynamics in a fault diagnostic application using Bayesian Belief Networks
Author :
Lampis, Mariapia ; Andrews, John
Author_Institution :
Aeronaut. & Automotive Eng. Dept., Loughborough Univ., Loughborough, UK
fYear :
2009
fDate :
20-24 July 2009
Firstpage :
186
Lastpage :
190
Abstract :
Fault diagnostic techniques are required to determine whether a fault has occurred in a system and to identify the component failures that may have caused it. This task can be complicated when dealing with complex systems and dynamic behaviour, in particular, introduces further difficulties. This paper presents a method for fault detection on dynamic systems using Bayesian Belief Networks (BBNs). Possible trends are identified for the variables in the systems that are monitored by the sensors. Fault Trees (FTs) are built to represent the causality of the trends and these are then converted into BBNs. The networks developed for different sections are connected together to form a unique concise network. For a combination of sensors which deviate from the expected trends, calculating the updated probability enables a list of potential causes for the system scenarios to be obtained. A simple water tank system has been used to validate the method.
Keywords :
Bayes methods; belief networks; fault diagnosis; probability; system recovery; tree data structures; Bayesian belief network; complex system; component failure; dynamic behaviour; fault diagnostic application; fault tree; probability; unique concise network; water tank system; Aerodynamics; Automotive engineering; Bayesian methods; Electronic mail; Fault detection; Fault diagnosis; Fault trees; Probability; Sensor systems; Vehicle dynamics; Bayesian Belief Networks; Fault Diagnostics; Fault Tree Analysis;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Reliability, Maintainability and Safety, 2009. ICRMS 2009. 8th International Conference on
Conference_Location :
Chengdu
Print_ISBN :
978-1-4244-4903-3
Electronic_ISBN :
978-1-4244-4905-7
Type :
conf
DOI :
10.1109/ICRMS.2009.5270213
Filename :
5270213
Link To Document :
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