Prognostics assessment using fleet-wide ontology

Gabriela Medina-Oliva (1) , Alexandre Voisin (1) , Maxime Monnin (2) , Flavien Peysson (2) , Jean-Baptiste Léger (2)

1 CRAN - Centre de Recherche en Automatique de Nancy
2 PREDICT [Vandœuvre-lès-Nancy]

Large complex systems, such as power plants, ships and aircraft, are composed of multiple systems, subsystems and components. When they are considered as embedded in operating systems such as a fleet, mission readiness and maintenance management issues are raised. PHM (Prognostics and Health Management) plays a key role in controlling the performance level of such systems, at least on the basis of adapted PHM strategies and system developments. Moreover considering a fleet implies to provide managers and engineers a relevant synthesis of information and to keep this information updated in terms of the global health of the fleet as well as the current status of their maintenance efforts. In order to achieve PHM at a fleet level, it is thus necessary to manage relevant knowledge arising from both modeling and monitoring of the fleet. In that way, this paper presents a knowledge structuring scheme based on ontologies for fleet PHM management applied to marine domain, with emphasis on prognostics modeling.

Domaines: Modélisation et simulation

Gabriela Medina-Oliva, Alexandre Voisin, Maxime Monnin, Flavien Peysson, Jean-Baptiste Léger. Prognostics assessment using fleet-wide ontology. Annual Conference of the Prognostics and Health Management Society 2012, PHM Conference 2012, Sep 2012, Minneapolis, Minnesota, United States. pp.CDROM. ⟨hal-00748697⟩