Artificial Intelligence Based Technology For Characterization Of Subsurface Rocks Surrounding Tunnel Boring Machine (TBM) And TBM Automatic Control

Description

Tunneling is an engineering process of creating a covered passageway through an obstruction (e.g., solid rocks), and it has been widely used in constructions of underground structures for a variety of applications, such as transportation (e.g., railways or highways), water supply, drainage, sewage, hydroelectricity, storage space, and mining. With thousands of kilometers of new tunnels being constructed annually in China, tunneling safety and efficiency are of great importance, particularly during operation of tunneling boring machine (TBM), because collapse of tunnels during construction often leads to both casualty of TBM operators and expensive over-budget plus project delay. This project aims to improve TBM safety and efficiency by devE:lloping machine learning algorithms and software for unmanned TBM. It will leverage on output from recent research projects funded by Research Grants Council and a database with billions of TBM operation data entries collected from recent tunneling projects in China. The machine learning algorithms and software developed in this project will be a key for realization of self-driving TBM. Since no operator is needed to stay underground inside a self-driving TBM, safety and health of the TBM operators are warranted. The project outcomes will be beneficial to tunneling practice worldwide.