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New fault detection method based on reduced kernel principal component analysis (RKPCA)
Journal article   Peer reviewed

New fault detection method based on reduced kernel principal component analysis (RKPCA)

Okba Taouali, Ines Jaffel, Hajer Lahdhiri, Mohamed Faouzi Harkat and Hassani Messaoud
International journal of advanced manufacturing technology, Vol.85(5-8), pp.1547-1552
01/07/2016
DOI: https://doi.org/10.1007/s00170-015-8059-1

Abstract

Automation & Control Systems Engineering Engineering, Manufacturing Science & Technology Technology
This paper proposes a new method for fault detection using a reduced kernel principal component analysis (RKPCA). The proposed RKPCA method consists on approximating the retained principal components given by the KPCA method by a set of observation vectors which point to the directions of the largest variances with the retained principal components. The proposed method has been tested on a chemical reactor and the results were satisfactory.

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