Bayesian Networks for Fault Detection under Lack of Historical Data

Authors:
Rui Máximo Esteves;Tomasz Wiktor Wlodarczyk;Chunming Rong;Einar Landre
Affiliations:
-;-;-;-
Venue:
ISPAN '09 Proceedings of the 2009 10th International Symposium on Pervasive Systems, Algorithms, and Networks
Year:
2009

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Fault detection and diagnosis of distributed parameter systems based on sensor networks and Bayesian networks

CONTROL'10 Proceedings of the 6th WSEAS international conference on Dynamical systems and control

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Abstract

In this paper we propose a Bayesian Network approach as a promissory data fusion technique for surveillance of sensors accuracy. We prove the usefulness of this method even in case when there is not enough feasible data to construct the model in traditional way. In presence of this data constrains we suggest an inversion of the causal relationship. This approach proves to be a possible solution to help the expert in the conditional probabilities assessment process. As a result a working model is constructed what would not be possible using traditional Bayesian Network approach.