Multiple sensor fault detection and isolation of an air quality monitoring network using RBF-NLPCA model
by Mohamed-Faouzi Harkat, Yvon Tharrault, Gilles Mourot, Jose Ragot
International Journal of Adaptive and Innovative Systems (IJAIS), Vol. 1, No. 3/4, 2010

Abstract: This paper presents a data-driven method based on non-linear 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.

Online publication date: Mon, 23-Aug-2010

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