MATEC Web Conf.
Volume 139, 20172017 3rd International Conference on Mechanical, Electronic and Information Technology Engineering (ICMITE 2017)
|Number of page(s)||5|
|Published online||05 December 2017|
Application of mind evolution Elman neural network model in gearbox fault diagnosis
1 Ordos Institute Of Technology, Inner Mongolia Ordos, 017000
* Corresponding author: email@example.com
Gearbox as an important component of the power system of agricultural machinery, plays a vital role in the normal operation of agricultural equipment. At present, the diagnosis of gearbox fault is mainly based on expert experience, and the accuracy is not guaranteed. In view of the achievements of Elman neural network in fault diagnosis, Elman neural network is used as the basic model of gearbox fault diagnosis. Considering that the Elman neural network is sensitive to the initial weight threshold and easy to fall into the local minimum, the mind evolution algorithm is introduced into the parameter optimization of the Elman neural network fault diagnosis model. Experimental results show that this assumption is successful, and the new model not only reduces diagnostic errors but also improves stability.
© The Authors, published by EDP Sciences, 2017
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (http://creativecommons.org/licenses/by/4.0/).
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.