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Fault detection of univariate non-Gaussian data with Bayesian network

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3 Author(s)
Sylvain Verron ; LASQUO/ISTIA, 62, av. Notre Dame du Lac, 49000 Angers, France ; Teodor Tiplica ; Abdessamad Kobi

The purpose of this article is to present a new method for fault detection with Bayesian network. The interest of this method is to propose a new structure of Bayesian network allowing to detect a fault in the case of a non-Gaussian signal. For that, a structure based on Gaussian mixture model is proposed. This particular structure allows to take into account the non-normality of the data. The effectiveness of the method is illustrated on a simple process corrupted by different faults.

Published in:

Industrial Technology (ICIT), 2010 IEEE International Conference on

Date of Conference:

14-17 March 2010