Particle Swarm Optimization Wavelet Neural Network Of Gearbox Fault Diagnosis

DOI

10.2991/icmse-15.2015.230How to use a DOI?

Keywords

Particle swarm optimization; Fault diagnosis; Wavelet neural network; Gear crack

Abstract

Gear box of the gear crack is the failure forms of gear transmission frequently. Wavelet neural network has the perfect theoretical system, clear the algorithm process, the powerful data identification and simulation function. As traditional gradient descending method of wavelet neural network is easy to fall into local minimum, slow convergence speed and a disadvantage of low efficiency, this article puts forward the particle swarm optimization wavelet neural network learning algorithm. Experiments show that the algorithm optimizes the various parameters of wavelet neural network, reduce the iteration times and improve the convergence precision.

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  - Hanxin Chen
AU  - Liu Yang
PY  - 2015/12
DA  - 2015/12
TI  - Particle Swarm Optimization Wavelet Neural Network Of Gearbox Fault Diagnosis
BT  - Proceedings of the 2015 6th International Conference on Manufacturing Science and Engineering
PB  - Atlantis Press
SP  - 1260
EP  - 1264
SN  - 2352-5401
UR  - https://doi.org/10.2991/icmse-15.2015.230
DO  - 10.2991/icmse-15.2015.230
ID  - Chen2015/12
ER  -