Two Kinds of Neural Network Fusion of Aero-engine Rotor Vibration Signal Fault Diagnosis

DOI

10.2991/icmmcce-15.2015.295How to use a DOI?

Keywords

Aero-engine rotor; Vibration signal; BP neural network; Probabilistic neural network.

Abstract

In order to improve the accuracy of fault diagnosis, this paper puts forward a method of wavelet packet combining neural network fusion. By wavelet packet decomposition and reconstruction of normal and fault vibration signals of aero-engine rotor, the feature vector from the vibration signal can be extracted. Then put the feature vectors which are the input vector of neural network into the BP (Back Propagation) neural network and PNN(Probabilistic Neural Network),and the paper puts forward an algorithm to fuse the results of BP and PNN. It turns out that the method can recognize the fault patterns well and improve the accuracy of diagnosis.

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/).

Download article (PDF)

TY  - CONF
AU  - Feng Ding
AU  - Zhaoyang Wang
AU  - Fengwei Qin
PY  - 2015/12
DA  - 2015/12
TI  - Two Kinds of Neural Network Fusion of Aero-engine Rotor Vibration Signal Fault Diagnosis
BT  - Proceedings of the 4th International Conference on Mechatronics, Materials, Chemistry and Computer Engineering 2015
PB  - Atlantis Press
SN  - 2352-538X
UR  - https://doi.org/10.2991/icmmcce-15.2015.295
DO  - 10.2991/icmmcce-15.2015.295
ID  - Ding2015/12
ER  -