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Developing data mining-based prognostic models for CF-18 aircraft / Marvin Zaluski in Transactions of the ASME . Journal of engineering for gas turbines and power, Vol. 133 N° 10 (Octobre 2011) 

Public ISBD [article]  in Transactions of the ASME . Journal of engineering for gas turbines and power > Vol. 133 N° 10 (Octobre 2011) . - 08 p. Titre : Developing data mining-based prognostic models for CF-18 aircraft Type de document : texte imprimé Auteurs : Marvin Zaluski, Auteur ; Sylvain Létourneau, Auteur ; Jeff Bird, Auteur Année de publication : 2011 Article en page(s) : 08 p. Note générale : Génie mécanique Langues : Anglais (eng) Mots-clés : Aerospace  computing  Aircraft  Data  mining Index. décimale : 620.1 Essais des matériaux. Défauts des matériaux. Protection des matériaux Résumé : The CF-18 (CF denotes Canadian Forces) aircraft is a complex system for which a variety of data are systematically being recorded: flight data from sensors, built-in test equipment data, and maintenance data. Without proper analytical and statistical tools, these data resources are of limited use to the operating organization. Focusing on data mining-based modeling, this paper investigates the use of readily available CF-18 data to support the development of prognostics and health management systems. A generic data mining methodology has been developed to build prognostic models from operational and maintenance data. This paper introduces the methodology and elaborates on challenges specific to the use of CF-18 data from the Canadian Forces. A number of key data mining tasks are examined including data gathering, information fusion, data preprocessing, model building, and model evaluation. The solutions developed to address these tasks are described. A software tool developed to automate the model development process is also presented. Finally, this paper discusses preliminary results on the creation of models to predict F404 no. 4 bearing and main fuel control failures on the CF-18. DEWEY : 620.1 ISSN : 0742-4795 En ligne : http://asmedl.aip.org/getabs/servlet/GetabsServlet?prog=normal&id=JETPEZ00013300 [...] [article] Developing data mining-based prognostic models for CF-18 aircraft [texte imprimé] / Marvin Zaluski, Auteur ; Sylvain Létourneau, Auteur ; Jeff Bird, Auteur . - 2011 . - 08 p. Génie mécanique Langues : Anglais (eng) in Transactions of the ASME . Journal of engineering for gas turbines and power > Vol. 133 N° 10 (Octobre 2011) . - 08 p. Mots-clés : Aerospace  computing  Aircraft  Data  mining Index. décimale : 620.1 Essais des matériaux. Défauts des matériaux. Protection des matériaux Résumé : The CF-18 (CF denotes Canadian Forces) aircraft is a complex system for which a variety of data are systematically being recorded: flight data from sensors, built-in test equipment data, and maintenance data. Without proper analytical and statistical tools, these data resources are of limited use to the operating organization. Focusing on data mining-based modeling, this paper investigates the use of readily available CF-18 data to support the development of prognostics and health management systems. A generic data mining methodology has been developed to build prognostic models from operational and maintenance data. This paper introduces the methodology and elaborates on challenges specific to the use of CF-18 data from the Canadian Forces. A number of key data mining tasks are examined including data gathering, information fusion, data preprocessing, model building, and model evaluation. The solutions developed to address these tasks are described. A software tool developed to automate the model development process is also presented. Finally, this paper discusses preliminary results on the creation of models to predict F404 no. 4 bearing and main fuel control failures on the CF-18. DEWEY : 620.1 ISSN : 0742-4795 En ligne : http://asmedl.aip.org/getabs/servlet/GetabsServlet?prog=normal&id=JETPEZ00013300 [...]