A case study for Fleet-wide semantic based predictive diagnostic

Autor: Medina-Oliva, G., Alexandre VOISIN, Monnin, M., Kosayyer, N., Léger, J. -B
Přispěvatelé: PREDICT [Vandœuvre-lès-Nancy], Centre de Recherche en Automatique de Nancy (CRAN), Centre National de la Recherche Scientifique (CNRS)-Université de Lorraine (UL), Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS), Voisin, Alexandre
Jazyk: angličtina
Rok vydání: 2013
Předmět:
Zdroj: 22nd Annual Conference of the European Safety and Reliability Conference, ESREL 2013
22nd Annual Conference of the European Safety and Reliability Conference, ESREL 2013, Sep 2013, Amsterdam, Netherlands. pp.CDROM
Safety, Reliability and Risk Analysis ISBN: 9781138001237
Scopus-Elsevier
Popis: International audience; Diagnosis is a critical activity in the PHM domain (Prognostics and Health Management) due to its impact on the downtime and on the global performances of a system. This activity becomes complex when dealing with large systems which are composed of multiple systems, subsystems and components of different technologies, different usages, etc. In order to ease diagnosis activities, this paper proposes to use a fleet-wide approach based on ontologies in order to capitalize knowledge and data to help decision makers to identify the causes of abnormal operations. In that sense, taking advantage of a fleet dimension implies to provide en-gineers more knowledge as well as relevant synthesis of information about the system behaviour. This paper presents a case-study concerning the occurrence of an abnormal situation for fuel engines in the marine do-main to illustrate how an ontology fleet-wide software application integrated in the KASEM e-maintenance platform facilitates diagnosis activities.
Databáze: OpenAIRE
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