Fault diagnostics and supervised testing : How fault diagnostic tools can be proactive?


Autoria(s): Najafi, M.; Auslander, D.M.; Bartlett, P.L.; Haves, P.
Contribuinte(s)

Grigoriadis , K.

Data(s)

2008

Resumo

The topic of fault detection and diagnostics (FDD) is studied from the perspective of proactive testing. Unlike most research focus in the diagnosis area in which system outputs are analyzed for diagnosis purposes, in this paper the focus is on the other side of the problem: manipulating system inputs for better diagnosis reasoning. In other words, the question of how diagnostic mechanisms can direct system inputs for better diagnosis analysis is addressed here. It is shown how the problem can be formulated as decision making problem coupled with a Bayesian Network based diagnostic mechanism. The developed mechanism is applied to the problem of supervised testing in HVAC systems.

Identificador

http://eprints.qut.edu.au/44002/

Publicador

ACTA Press

Relação

http://www.iasted.org/newsletter/2008/isc1.htm

Najafi, M., Auslander, D.M. , Bartlett, P.L., & Haves, P. (2008) Fault diagnostics and supervised testing : How fault diagnostic tools can be proactive? In Grigoriadis , K. (Ed.) Proceeding (633) Intelligent Systems and Control - 2008, ACTA Press, Orlando, USA , pp. 34-45.

Direitos

Copyright 2008 ACTA Press

Fonte

Faculty of Science and Technology; Mathematical Sciences

Palavras-Chave #010200 APPLIED MATHEMATICS #Fault Diagnosis #HVAC Systems #Machine Learning #Bayesian Networks
Tipo

Conference Paper