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Proceedings Paper

Design of intelligent diagnosis system based on CBR for jet engine
Author(s): Bo Xu; Xingshan Li; Jinsong Yu
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Paper Abstract

Condition monitoring and fault diagnosis are crucial for insuring flight safety. According to characteristics of complex systems, this paper proposes an intelligent system for off-line fault detection and diagnosis for gas path components in jet engine. Based on a machine learning methodology named Case-based Reasoning (CBR), this system consists of two types of case-bases, static case-base and dynamic case-base. Dynamic time warping (DTW) is used to retrieve dynamic cases by assessing the similarity between two dynamic sequence samples.

Paper Details

Date Published: 2 September 2003
PDF: 4 pages
Proc. SPIE 5253, Fifth International Symposium on Instrumentation and Control Technology, (2 September 2003); doi: 10.1117/12.522341
Show Author Affiliations
Bo Xu, Beijing Univ. of Aeronautics and Astronautics (China)
Xingshan Li, Beijing Univ. of Aeronautics and Astronautics (China)
Jinsong Yu, Beijing Univ. of Aeronautics and Astronautics (China)


Published in SPIE Proceedings Vol. 5253:
Fifth International Symposium on Instrumentation and Control Technology
Guangjun Zhang; Huijie Zhao; Zhongyu Wang, Editor(s)

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