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Communication Dans Un Congrès Année : 2010

Fault detection of univariate non-Gaussian data with Bayesian network

Résumé

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.
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Dates et versions

inria-00517031 , version 1 (13-09-2010)

Identifiants

  • HAL Id : inria-00517031 , version 1

Citer

Sylvain Verron, Teodor Tiplica, Abdessamad Kobi. Fault detection of univariate non-Gaussian data with Bayesian network. IEEE International Conference on Industrial Technology (ICIT'10), 2010, Vina del Mar, Chile. ⟨inria-00517031⟩

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