Study on the prediction methods of aero engine fault parameters

DOI

10.2991/ipemec-15.2015.83How to use a DOI?

Keywords

aero-engine; characteristic parameters; prediction methods

Abstract

This paper uses the least squares method, BP neural network and gray GM(1,1) model for trend forecasts and predicting the remaining life of the aero-engine fault parameters. By comparing the results of the three methods, the least squares method and BP neural network method predicting results are more exact than the gray GM(1,1) model. The three methods are also used for predicting the actual data, and the result is close to the real.

Copyright

© 2015, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Dewang Li
AU  - Dongxiang Jiang
PY  - 2015/05
DA  - 2015/05
TI  - Study on the prediction methods of aero engine fault parameters
BT  - Proceedings of the 2015 International Power, Electronics and Materials Engineering Conference
PB  - Atlantis Press
SP  - 435
EP  - 440
SN  - 2352-5401
UR  - https://doi.org/10.2991/ipemec-15.2015.83
DO  - 10.2991/ipemec-15.2015.83
ID  - Li2015/05
ER  -