Application of PSO Algorithm to Gearbox Fault Diagnosis

DOI

10.2991/iske.2007.168How to use a DOI?

Keywords

particle swarm optimization(PSO); swarm intelligence; neural network; fault diagnosis

Abstract

After an introduction of the principle of particle swarm optimization (PSO) algorithm based on swarm intelligence, and of the modified version of the PSO algorithm, a neural network system for gearbox fault diagnosis has been established. After being trained by PSO algorithm, the neural network system is applied to fault diagnosis. Comparison of the diagnostic results between the PSO-based algorithm and the BP-based algorithm indicates that the network system based on PSO algorithm is of better training performance, and of less overall output error compared with those of the BP algorithm. It has been proved that the neural network system for fault diagnosis based on PSO algorithm is of higher probability of identifying multi-fault symptoms, and of rapid convergence and higher diagnosis accuracy, and that the neural network system for fault diagnosis expects a wide application in the field of mechanic fault diagnosis because of its higher searching efficiency.

Copyright

© 2007, 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  - Hongxia Pan
PY  - 2007/10
DA  - 2007/10
TI  - Application of PSO Algorithm to Gearbox Fault Diagnosis
BT  - Proceedings of the 2007 International Conference on Intelligent Systems and Knowledge Engineering (ISKE 2007)
PB  - Atlantis Press
SP  - 990
EP  - 994
SN  - 1951-6851
UR  - https://doi.org/10.2991/iske.2007.168
DO  - 10.2991/iske.2007.168
ID  - Pan2007/10
ER  -