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Proceedings Paper

Effects of clearance on aeroengine performance based on neural network
Author(s): Wen Chen; Shuming Li; Jie Bai
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Paper Abstract

In recent years, neural network system has got extensive application in the field of aviation because of its strong learning ability, the distributed storage of knowledge, associated synchronization management and restrain of random error etc. There are a lot of network types. Among them, BP (Back Propagation) neural network is the most extensive one that been used. In this paper, BP neural network theory is briefly introduced and is applied to analyze the sample of PW4056 series aero engine. Correlation analysis and theory analysis is adopted to select the input variable. The method of this paper presents a new synthetically prediction. Result indicated that this method could get practical and effective network model. Compared with the traditional regression analysis, neural network have a wilder application foreground.

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: 10.1117/12.521663
Show Author Affiliations
Wen Chen, Civil Aviation Univ. of China (China)
Shuming Li, Civil Aviation Univ. of China (China)
Jie Bai, Civil Aviation Univ. of China (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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