Fault Detection of the Tennessee Eastman Process using Online Reduced Kernel PCA* Conference Paper

abstract

• 2018 European Control Association (EUCA). In this paper, we propose an online reduced kernel principal component analysis (KPCA) method for process monitoring. The developed method consists in updating the KPCA model depending on the dictionary which contains linearly independent kernel functions and then using this new reduced KPCA model for process monitoring. The process monitoring performances are studied using Tennessee Eastman Process (TEP). The results demonstrate the effectiveness of the developed online KPCA technique compared to the classical online KPCA method.

name of conference

• 2018 European Control Conference (ECC)

authors

• Nounou, Mohamed

published proceedings

• 2018 European Control Conference (ECC)

author list (cited authors)

• Fazai, R., Mansouri, M., Taouali, O., Harkat, M., Bouguila, N., & Nounou, M.

citation count

• 1

complete list of authors

• Fazai, Radhia||Mansouri, Majdi||Taouali, Okba||Harkat, Mohamed-Faouzi||Bouguila, Nassreddine||Nounou, Mohamed

publication date

• June 2018

publisher

• Institute of Electrical and Electronics Engineers (IEEE)  Publisher

Digital Object Identifier (DOI)

• 10.23919/ecc.2018.8550213

International Standard Book Number (ISBN) 13

• 9783952426982

start page

• 2697

end page

• 2702

volume

• 00

URL

• https://ieeexplore.ieee.org/xpl/conhome/8496738/proceeding