Proceedings of the 2012 2nd International Conference on Computer and Information Application (ICCIA 2012)

Gear fault diagnosis method of intelligence based on genetic algorithm to optimize the BP neural network

Authors
Jie Fang
Corresponding Author
Jie Fang
Available Online May 2014.
DOI
https://doi.org/10.2991/iccia.2012.197How to use a DOI?
Keywords
Artificial Neural, BP neural network, Gear fault intelligent diagnosis, Vibration Signal
Abstract

The work of the gear transmission is very complex, and its failure in the form and features tend to show non-linear mapping. Fault signal is often submerged in conventional vibration signal and noise, it is not easy using traditional signal processing methods to extract fault features which in a difficult to gear fault diagnosis. This paper based on the genetic algorithm to optimize the structure of the BP neural network model for the intelligent diagnosis system which is used in gear fault diagnosis.The experimental results show that this method can be effectively used for the diagnosis and identification of the gears common fault type.

Copyright
© 2013, 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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Volume Title
Proceedings of the 2012 2nd International Conference on Computer and Information Application (ICCIA 2012)
Series
Advances in Intelligent Systems Research
Publication Date
May 2014
ISBN
978-94-91216-41-1
ISSN
1951-6851
DOI
https://doi.org/10.2991/iccia.2012.197How to use a DOI?
Copyright
© 2013, 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/).

Cite this article

TY  - CONF
AU  - Jie Fang
PY  - 2014/05
DA  - 2014/05
TI  - Gear fault diagnosis method of intelligence based on genetic algorithm to optimize the BP neural network
BT  - Proceedings of the 2012 2nd International Conference on Computer and Information Application (ICCIA 2012)
PB  - Atlantis Press
SP  - 815
EP  - 818
SN  - 1951-6851
UR  - https://doi.org/10.2991/iccia.2012.197
DO  - https://doi.org/10.2991/iccia.2012.197
ID  - Fang2014/05
ER  -