The Application of BP Neural Network in the Thrust Hydraulic System for Shield Tunneling Machine
Geqiang Li, Yinting Ding, Kui Chen, Weifeng Han, Bingjing Guo
Available Online April 2017.
- 10.2991/eame-17.2017.39How to use a DOI?
- shield machine; thrust hydraulic system; BP neural network; simulation
This paper studies the problem of the precision of thrust speed and pressure compound control under the uncertain external load condition for shield tunneling machine. An controller about thrust speed and pressure is designed based on the traditional PID control algorithm combined with BP neural networks. By using AMEsim and Simulink software, the physical model and controller of the thrust system are established and joint simulation is conducted. The thrust system of shield machine model is simulated under the condition of different load and flow, which proves the stability and robustness of the controller with BP neural network algorithm.
- © 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 - Geqiang Li AU - Yinting Ding AU - Kui Chen AU - Weifeng Han AU - Bingjing Guo PY - 2017/04 DA - 2017/04 TI - The Application of BP Neural Network in the Thrust Hydraulic System for Shield Tunneling Machine BT - Proceedings of the 2017 2nd International Conference on Electrical, Automation and Mechanical Engineering (EAME 2017) PB - Atlantis Press SP - 160 EP - 163 SN - 2352-5401 UR - https://doi.org/10.2991/eame-17.2017.39 DO - 10.2991/eame-17.2017.39 ID - Li2017/04 ER -