Developing data mining-based prognostic models for CF-18 aircraft

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Journal titleJournal of Engineering for Gas Turbines and Power
Article number101601
SubjectBuilt-in tests; Canadian forces; Complex systems; Data gathering; Data mining tasks; Data preprocessing; Data resources; Flight data; Fuel control; Generic data; Model development; Model evaluation; Prognostic model; Prognostics and health managements; Software tool; Statistical tools; Aircraft models; Aircraft parts and equipment; Data mining; Maintainability; Statistical mechanics; Testing; Information management
AbstractThe 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. © 2011 American Society of Mechanical Engineers.
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AffiliationNational Research Council Canada (NRC-CNRC)
Peer reviewedYes
NPARC number21271625
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Record identifier4ecb23c0-f8a5-42a6-b022-c4b40a3cd675
Record created2014-03-24
Record modified2016-05-09
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