Effects of clearance on aeroengine performance based on neural network

Wen Chen; Shuming Li; Jie Bai

doi:10.1117/12.521663

2 September 2003 Effects of clearance on aeroengine performance based on neural network

Wen Chen, Shuming Li, Jie Bai

Proceedings Volume 5253, Fifth International Symposium on Instrumentation and Control Technology; (2003) https://doi.org/10.1117/12.521663
Event: Fifth International Symposium on Instrumentation and Control Technology, 2003, Beijing, China

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.

Citation Download Citation

Wen Chen, Shuming Li, and Jie Bai "Effects of clearance on aeroengine performance based on neural network", Proc. SPIE 5253, Fifth International Symposium on Instrumentation and Control Technology, (2 September 2003); https://doi.org/10.1117/12.521663

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available