Behavior graphs for hybrid systems monitoring
Type de document :
Communication dans un congrès avec actes
Titre :
Behavior graphs for hybrid systems monitoring
Auteur(s) :
Takrouni, Asma [Auteur]
Cocquempot, Vincent [Auteur]
Systèmes Tolérants aux Fautes [STF]
Zanzouri, Nadia [Auteur]
Ksouri, Mekki [Auteur]
Cocquempot, Vincent [Auteur]
Systèmes Tolérants aux Fautes [STF]
Zanzouri, Nadia [Auteur]
Ksouri, Mekki [Auteur]
Titre de la manifestation scientifique :
IEEE ICCEE : International Conference on Computer and Electrical Engineering
Ville :
Dubai
Pays :
Émirats arabes unis
Date de début de la manifestation scientifique :
2009-12-28
Titre de l’ouvrage :
Computer and Electrical Engineering, 2009. ICCEE '09. Second International Conference
Date de publication :
2009-12-28
Mot(s)-clé(s) en anglais :
Fault detection and isolation
Hybrid systems
graphs
monitoring
Hybrid systems
graphs
monitoring
Discipline(s) HAL :
Sciences de l'ingénieur [physics]/Automatique / Robotique
Résumé en anglais : [en]
Hybrid Dynamical Systems (HDS) constitute a wide class of common industrial applications, where the behavior is determined by the interaction between continuous and discrete dynamics, i.e. behavioral modes succession. The ...
Lire la suite >Hybrid Dynamical Systems (HDS) constitute a wide class of common industrial applications, where the behavior is determined by the interaction between continuous and discrete dynamics, i.e. behavioral modes succession. The general principle of model-based Fault Detection and Isolation (FDI) algorithms is to compare the expected behavior of the system, given by a model, with its actual behavior, known through on-line observations. Faults in HDS may corrupt the two dynamics. In that paper, we propose to limit the set of possible mode candidates by using a priori information on the discrete evolution under normal and faulty hypothesis. Two kinds of graphs are derived from the initial hybrid model, namely Normal Behavior Graphs (NBG), Faulty Behavior Graphs (FBG). Using these graphs allows us not only to identify efficiently the actual mode but also to directly interpret (diagnose) the discrete faulty evolution in terms of faults. The whole FDI methodology is described and applied to a two tanks system example.Lire moins >
Lire la suite >Hybrid Dynamical Systems (HDS) constitute a wide class of common industrial applications, where the behavior is determined by the interaction between continuous and discrete dynamics, i.e. behavioral modes succession. The general principle of model-based Fault Detection and Isolation (FDI) algorithms is to compare the expected behavior of the system, given by a model, with its actual behavior, known through on-line observations. Faults in HDS may corrupt the two dynamics. In that paper, we propose to limit the set of possible mode candidates by using a priori information on the discrete evolution under normal and faulty hypothesis. Two kinds of graphs are derived from the initial hybrid model, namely Normal Behavior Graphs (NBG), Faulty Behavior Graphs (FBG). Using these graphs allows us not only to identify efficiently the actual mode but also to directly interpret (diagnose) the discrete faulty evolution in terms of faults. The whole FDI methodology is described and applied to a two tanks system example.Lire moins >
Langue :
Anglais
Comité de lecture :
Oui
Audience :
Internationale
Vulgarisation :
Non
Collections :
Source :