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On improving performance of aircraft engine gas path fault diagnosis

¹ Industrial Artificial Intelligence Lab, GE Global Research Center, Niskayuna, NY 12309, USA
² Department of MANE, Rensselaer Polytechnic Institute, Troy, NY 12181, USA
³ NASA Ames Research Center, Moffett Field, CA 94035, USA

^* To whom correspondence should be addressed. E-mail: yan{at}crd.ge.com.

	Abstract

Aircraft engine fault diagnosis plays a crucial role in cost-effective operations of aircraft engines. However, designing an engine fault diagnostic system with the desired performance is a challenging task, because of several characteristics associated with aircraft engines. Geared towards achieving the highest possible performance of fault diagnosis, this paper explores strategies on improving diagnosis performance. Specifically, we introduce flight regime mapping and a two-level multiple classifier system as means to improve classification performance. By designing a real-world aircraft fault diagnostic system, we demonstrate that the strategies adopted in this study are effective in improving the performance of aircraft engine fault diagnostic systems.

First published on June 10, 2009, doi:10.1177/0142331208092029

Transactions of the Institute of Measurement and Control 2009;31:275.

A more recent version of this article appeared on June 1, 2009


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