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Output relevant fault reconstruction and fault subspace extraction in total projection to latent structures models / Gang Li in Industrial & engineering chemistry research, Vol. 49 N° 19 (Octobre 2010) 

Public ISBD [article]  in Industrial & engineering chemistry research > Vol. 49 N° 19 (Octobre 2010) . - pp. 9175–9183 Titre : Output relevant fault reconstruction and fault subspace extraction in total projection to latent structures models Type de document : texte imprimé Auteurs : Gang Li, Auteur ; S. Joe Qin, Auteur ; Donghua Zhou, Auteur Année de publication : 2010 Article en page(s) : pp. 9175–9183 Note générale : Chimie industrielle Langues : Anglais (eng) Mots-clés : Operations  industrial  processes Résumé : Statistical data-driven process monitoring is critical for efficient operations of industrial processes. However, deviations from normal regions in the process data may or may not lead to poor quality of products. This paper proposes a new combined index for detecting output-relevant faults, which affect the output data, and studies the output-relevant fault detectability based on total projection to latent structures (T-PLS). Given actual fault direction, fault-free data can be reconstructed and output-relevant part of fault magnitude can be estimated. Two new methods are derived to extract output-relevant fault subspace from faulty data. A simulation example and a case study on the Tennessee Eastman process are used to show the effectiveness of the proposed methods. ISSN : 0888-5885 En ligne : http://pubs.acs.org/doi/abs/10.1021/ie901939n [article] Output relevant fault reconstruction and fault subspace extraction in total projection to latent structures models [texte imprimé] / Gang Li, Auteur ; S. Joe Qin, Auteur ; Donghua Zhou, Auteur . - 2010 . - pp. 9175–9183. Chimie industrielle Langues : Anglais (eng) in Industrial & engineering chemistry research > Vol. 49 N° 19 (Octobre 2010) . - pp. 9175–9183 Mots-clés : Operations  industrial  processes Résumé : Statistical data-driven process monitoring is critical for efficient operations of industrial processes. However, deviations from normal regions in the process data may or may not lead to poor quality of products. This paper proposes a new combined index for detecting output-relevant faults, which affect the output data, and studies the output-relevant fault detectability based on total projection to latent structures (T-PLS). Given actual fault direction, fault-free data can be reconstructed and output-relevant part of fault magnitude can be estimated. Two new methods are derived to extract output-relevant fault subspace from faulty data. A simulation example and a case study on the Tennessee Eastman process are used to show the effectiveness of the proposed methods. ISSN : 0888-5885 En ligne : http://pubs.acs.org/doi/abs/10.1021/ie901939n