Research on the Equipment Fault Diagnosis Based on GN-BP Neural Network
- 10.2991/amcce-17.2017.140How to use a DOI?
- Fault diagnosis; GA-BP; Network training; Data analyses
Neural network provides a new research method for equipment fault diagnosis with its inherent memory ability, self-learning ability and strong fault tolerance. In the basis of equipment fault diagnosis characterized mathematical, the research established the model of fault diagnosis for equipment based on GA-BP, and the diagnosis model has been applied in the theoretical analyses and test for fault diagnosis of gear box. Experimental results show that equipment fault diagnosis technology based on GA-BP neural network, it can optimize the tactics with genetic algorithm when the network trained model, and adjust precision using BP network, the model can accurately diagnosis the types of fault for equipment. The model of GA-BP neural network has higher prediction accuracy and adaptability than the traditional BP neural network and has important application in the field of fault diagnosis.
- © 2017, 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 - Jian Du AU - Yu-cai Dong AU - Jing Xia AU - HuiZhen Li PY - 2017/03 DA - 2017/03 TI - Research on the Equipment Fault Diagnosis Based on GN-BP Neural Network BT - Proceedings of the 2017 2nd International Conference on Automation, Mechanical Control and Computational Engineering (AMCCE 2017) PB - Atlantis Press SP - 791 EP - 796 SN - 2352-5401 UR - https://doi.org/10.2991/amcce-17.2017.140 DO - 10.2991/amcce-17.2017.140 ID - Du2017/03 ER -