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Emerging Data Processing Technologies in MechanizedTunnelling

Emerging Data Processing Technologies in MechanizedTunnelling


J. Rostami / U. Maidl / J. Stascheit / U. Gwildis

Programmable Logic Controllers (PLC) or microprocessors are standard features on Tunnel Boring Machines (TBM) to monitor and record various sensory systems providing options for control and automation of machine processes. The data collected from these sensory systems and channelled through PLC is stored for real-time analysis and use by the operators and per typical construction specifications shared with the project management team representing the owner. Machine data automatically acquired during TBM advance is usually 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 with objectives such as 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 technological advances with implications on geotechnical exploration, subsurface risk allocation, TBM operation, face condition tracking, and claims management in the future.

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Year 2022
City Copenhagen
Country Denmark
ISBN 978-2-9701436-7-3