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Adaptive agent-based system for process fault diagnosis / Sinem Perk in Industrial & engineering chemistry research, Vol. 50 N° 15 (Août 2011) 

Public ISBD [article]  in Industrial & engineering chemistry research > Vol. 50 N° 15 (Août 2011) . - pp. 9138-9155 Titre : Adaptive agent-based system for process fault diagnosis Type de document : texte imprimé Auteurs : Sinem Perk, Auteur ; Fouad Teymour, Auteur ; Ali Cinar, Auteur Année de publication : 2011 Article en page(s) : pp. 9138-9155 Note générale : Chimie industrielle Langues : Anglais (eng) Mots-clés : Fault  diagnostic Résumé : An adaptive agent-based hierarchical framework for fault type classification and diagnosis in continuous chemical processes is presented. Classification techniques such as Fisher's discriminant analysis (FDA) and partial least-squares discriminant analysis (PLSDA) and diagnosis tools such as variable contribution plots are used by agents in this supervision system. After an abnormality is detected, the classification results reported by different diagnosis agents are summarized via a performance-based criterion, and a consensus diagnosis decision is formed. In the agent management layer of the proposed system, the performances of diagnosis agents are evaluated under different fault scenarios, and the collective performance of the supervision system is improved via performance-based consensus decision and adaptation. The effectiveness of the proposed adaptive agent-based framework for the classification of faults is illustrated using a simulated continuous stirred tank reactor (CSTR) network. DEWEY : 660 ISSN : 0888-5885 En ligne : http://cat.inist.fr/?aModele=afficheN&cpsidt=24395862 [article] Adaptive agent-based system for process fault diagnosis [texte imprimé] / Sinem Perk, Auteur ; Fouad Teymour, Auteur ; Ali Cinar, Auteur . - 2011 . - pp. 9138-9155. Chimie industrielle Langues : Anglais (eng) in Industrial & engineering chemistry research > Vol. 50 N° 15 (Août 2011) . - pp. 9138-9155 Mots-clés : Fault  diagnostic Résumé : An adaptive agent-based hierarchical framework for fault type classification and diagnosis in continuous chemical processes is presented. Classification techniques such as Fisher's discriminant analysis (FDA) and partial least-squares discriminant analysis (PLSDA) and diagnosis tools such as variable contribution plots are used by agents in this supervision system. After an abnormality is detected, the classification results reported by different diagnosis agents are summarized via a performance-based criterion, and a consensus diagnosis decision is formed. In the agent management layer of the proposed system, the performances of diagnosis agents are evaluated under different fault scenarios, and the collective performance of the supervision system is improved via performance-based consensus decision and adaptation. The effectiveness of the proposed adaptive agent-based framework for the classification of faults is illustrated using a simulated continuous stirred tank reactor (CSTR) network. DEWEY : 660 ISSN : 0888-5885 En ligne : http://cat.inist.fr/?aModele=afficheN&cpsidt=24395862

Statistical Monitoring of Complex Chemical Processes Using Agent-Based Systems / Sinem Perk in Industrial & engineering chemistry research, Vol. 49 N° 11 (Juin 2010) 

Public ISBD [article]  in Industrial & engineering chemistry research > Vol. 49 N° 11 (Juin 2010) . - pp. 5080–5093 Titre : Statistical Monitoring of Complex Chemical Processes Using Agent-Based Systems Type de document : texte imprimé Auteurs : Sinem Perk, Auteur ; Fouad Teymour, Auteur ; Ali Cinar, Auteur Année de publication : 2010 Article en page(s) : pp. 5080–5093 Note générale : Industrial chemistry Langues : Anglais (eng) Mots-clés : Chemical  Processes Résumé : It is highly desirable to have a statistical process monitoring (SPM) system that detects the abnormalities in process operations quickly with as few missed and false alarms as possible while the process operates under various operating conditions. An agent-based combined monitoring and fault detection framework is proposed in this study. In this framework, different SPM techniques compete with and complement each other to enhance detection speed and accuracy. SPM techniques from literature such as principal component analysis (PCA), multiblock PCA (MBPCA), and dynamic PCA (DPCA) techniques are implemented in this agent-based process supervision system. An agent performance assessment and agent management layer provides dynamic adaptation of the supervision system and improves the performance of SPM. The statistical information coming from each of the statistical techniques is summarized through a consensus mechanism. The performance of the agent-based consensus mechanism using different consensus criteria is tested for system disturbances of various magnitudes. The effectiveness of the proposed agent-based framework with different consensus criteria is evaluated based on fault detection times and missed alarm rates and the adaptation of the supervision system is illustrated. ISSN : 0888-5885 En ligne : http://pubs.acs.org/doi/abs/10.1021/ie901368j [article] Statistical Monitoring of Complex Chemical Processes Using Agent-Based Systems [texte imprimé] / Sinem Perk, Auteur ; Fouad Teymour, Auteur ; Ali Cinar, Auteur . - 2010 . - pp. 5080–5093. Industrial chemistry Langues : Anglais (eng) in Industrial & engineering chemistry research > Vol. 49 N° 11 (Juin 2010) . - pp. 5080–5093 Mots-clés : Chemical  Processes Résumé : It is highly desirable to have a statistical process monitoring (SPM) system that detects the abnormalities in process operations quickly with as few missed and false alarms as possible while the process operates under various operating conditions. An agent-based combined monitoring and fault detection framework is proposed in this study. In this framework, different SPM techniques compete with and complement each other to enhance detection speed and accuracy. SPM techniques from literature such as principal component analysis (PCA), multiblock PCA (MBPCA), and dynamic PCA (DPCA) techniques are implemented in this agent-based process supervision system. An agent performance assessment and agent management layer provides dynamic adaptation of the supervision system and improves the performance of SPM. The statistical information coming from each of the statistical techniques is summarized through a consensus mechanism. The performance of the agent-based consensus mechanism using different consensus criteria is tested for system disturbances of various magnitudes. The effectiveness of the proposed agent-based framework with different consensus criteria is evaluated based on fault detection times and missed alarm rates and the adaptation of the supervision system is illustrated. ISSN : 0888-5885 En ligne : http://pubs.acs.org/doi/abs/10.1021/ie901368j