Research Papers: Gas Turbines: Controls, Diagnostics, and Instrumentation

Developing Data Mining-Based Prognostic Models for CF-18 Aircraft

[+] Author and Article Information
Marvin Zaluski, Sylvain Létourneau, Jeff Bird, Chunsheng Yang

 National Research Council of Canada, Ottawa, ON, K1A 0R6, Canada

J. Eng. Gas Turbines Power 133(10), 101601 (May 06, 2011) (8 pages) doi:10.1115/1.4002812 History: Received June 04, 2010; Revised June 28, 2010; Published May 06, 2011; Online May 06, 2011

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.

Copyright © 2011 by American Society of Mechanical Engineers
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Figure 1

Overview of data mining-based methodology

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Figure 2

Data gathering and labeling processes in EBM3

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Figure 3

EBM3 experimentation in model building

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Figure 4

EBM3 experimentation model evaluation

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Figure 5

Scoring function



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