Emerging Data Processing Technologies for TBM Projects— State of the Art and Outlook - RETC2021

Tunnel Boring Machines (TBM) have more or less become the preferred method of tunneling in various ground conditions and Programmable Logic Controllers (PLC) or microprocessors are standard features on TBMs to monitor and record various sensory systems on the machine providing the possibility for machine automation and control. The data collected from these sensory systems and channeled through PLC is stored for real-time analysis or use by the operators. Based on typical construction specifications, part of the information collected in the process is shared with the project management team representing the owner. Machine data automatically acquired during TBM advance is typically processed by specialized software to offer the project team data visualization and evaluation options. Interfacing with Geographic Information System (GIS), Computer-Aided Design (CAD), 3-D geologic model, instrumentation data bases, and Document Management Systems (DMS) allows for developing Building Information Models (BIM) of the tunnel’s as-built condition. Application of Artificial Intelligence (AI) processes such as Machine Learning (ML) have already been used for analysis of data, including performance prediction of hard rock TBMs, and exhibited the potential of big data analytics in improving the productivity of the operations. This paper outlines anticipated disruptive technological advances with implications on geotechnical exploration, TBM operation, face condition tracking, subsurface risk allocation, and claims management in the future.