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Growing structure multiple model systems for anomaly detection and fault diagnosis / Jianbo Liu in Transactions of the ASME . Journal of dynamic systems, measurement, and control, Vol. 131 N° 5 (Septembre 2009) 

Public ISBD [article]  in Transactions of the ASME . Journal of dynamic systems, measurement, and control > Vol. 131 N° 5 (Septembre 2009) . - 13 p. Titre : Growing structure multiple model systems for anomaly detection and fault diagnosis Type de document : texte imprimé Auteurs : Jianbo Liu, Auteur ; Dragan Djurdjanovic, Auteur ; Kenneth Marko, Auteur Année de publication : 2009 Article en page(s) : 13 p. Note générale : dynamic systems Langues : Anglais (eng) Mots-clés : growing  structure  multiple  model  system;  anomaly  detection;  nonlinear  system Résumé : A new anomaly detection scheme based on growing structure multiple model system (GSMMS) is proposed in this paper to detect and quantify the effects of anomalies. The GSMMS algorithm combines the advantages of growing self-organizing networks with efficient local model parameter estimation into an integrated framework for modeling and identification of general nonlinear dynamic systems. The identified model then serves as a foundation for building an effective anomaly detection and fault diagnosis system. By utilizing the information about system operation region provided by the GSMMS, the residual errors can be analyzed locally within each operation region. This local decision making scheme can accommodate for unequally distributed residual errors across different operational regions. The performance of the newly proposed method is evaluated through anomaly detection and quantification in an electronically controlled throttle system, which is simulated using a high-fidelity engine simulation software package provided by a major automotive manufacturer for control system development. DEWEY : 629.8 ISSN : 0022-0434 En ligne : http://dynamicsystems.asmedigitalcollection.asme.org/issue.aspx?journalid=117&is [...] [article] Growing structure multiple model systems for anomaly detection and fault diagnosis [texte imprimé] / Jianbo Liu, Auteur ; Dragan Djurdjanovic, Auteur ; Kenneth Marko, Auteur . - 2009 . - 13 p. dynamic systems Langues : Anglais (eng) in Transactions of the ASME . Journal of dynamic systems, measurement, and control > Vol. 131 N° 5 (Septembre 2009) . - 13 p. Mots-clés : growing  structure  multiple  model  system;  anomaly  detection;  nonlinear  system Résumé : A new anomaly detection scheme based on growing structure multiple model system (GSMMS) is proposed in this paper to detect and quantify the effects of anomalies. The GSMMS algorithm combines the advantages of growing self-organizing networks with efficient local model parameter estimation into an integrated framework for modeling and identification of general nonlinear dynamic systems. The identified model then serves as a foundation for building an effective anomaly detection and fault diagnosis system. By utilizing the information about system operation region provided by the GSMMS, the residual errors can be analyzed locally within each operation region. This local decision making scheme can accommodate for unequally distributed residual errors across different operational regions. The performance of the newly proposed method is evaluated through anomaly detection and quantification in an electronically controlled throttle system, which is simulated using a high-fidelity engine simulation software package provided by a major automotive manufacturer for control system development. DEWEY : 629.8 ISSN : 0022-0434 En ligne : http://dynamicsystems.asmedigitalcollection.asme.org/issue.aspx?journalid=117&is [...]