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Communication Dans Un Congrès Année : 2009

Multiple Sensor fault detection and isolation of an air quality monitoring network using RBF-NLPCA model

Résumé

This paper presents a data-driven method based on nonlinear principal component analysis to detect and isolate multiple sensor faults. The RBF-NLPCA model is obtained by combining a principal curve algorithm and two three layer radial basis function (RBF) networks. The reconstruction approach for multiple sensors is proposed in the non linear case and successfully applied for multiple sensor fault detection and isolation of an air quality monitoring network. The proposed approach reduces considerably the number of reconstruction combinations and allows to determine replacement values for the faulty sensors.
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Dates et versions

hal-00401743 , version 1 (05-07-2009)

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  • HAL Id : hal-00401743 , version 1

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Mohamed-Faouzi Harkat, Gilles Mourot, José Ragot. Multiple Sensor fault detection and isolation of an air quality monitoring network using RBF-NLPCA model. 7th IFAC Symposium on Fault Detection, Supervision and Safety of Technical Processes, Safeprocess 2009, Jun 2009, Barcelonne, Spain. pp.CDROM. ⟨hal-00401743⟩
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