Identification of Surrounding Rock in TBM Excavation with Deep Neural Network
- Resource Type
- Conference
- Authors
- Nie, ShiWu; Xue, Lin; Jia, GuoPeng; Ma, Yue; Chen, Jing; Huo, JunZhou
- Source
- 2019 2nd International Conference on Artificial Intelligence and Big Data (ICAIBD) Artificial Intelligence and Big Data (ICAIBD), 2019 2nd International Conference on. :251-255 May, 2019
- Subject
- Computing and Processing
Rocks
Biological neural networks
Mathematical model
Deep learning
Predictive models
Mechanical engineering
component
deep neural network
TBM
identification of surrounding rock
- Language
In this paper, based on the measured data of a water diversion project and combined with the existing research on the artificial neural network technology, a deep neural network model is trained to realize the real-time identification of surrounding rock in tunnel boring machine (TBM) excavation. The overall accuracy is above 85%. The result shows that deep learning technology can play a role in TBM geological prediction, and TBM operation can be guided by this method.