Published in: 2021 14th International Symposium on Computational Intelligence and Design (ISCID).
Towards a data-driven assistance system for operating segment erectors in tunnel boring machines
Authors
Hans Aoyang Zhou
Information Management in Mechanical Engineering, RWTH Aachen University, Aachen, Germany
Aymen Gannouni
Information Management in Mechanical Engineering, RWTH Aachen University, Aachen, Germany
Christian Gentz
Institute for Machine Elements and Systems Engineering, RWTH Aachen University, Aachen, Germany
Johannes Tröndle
Herrenknecht AG, Schwanau, Germany
Stephan Neumann
Institute for Machine Elements and Systems Engineering, RWTH Aachen University, Aachen, Germany
Anas Abdelrazeq
Information Management in Mechanical Engineering, RWTH Aachen University, Aachen, Germany
Georg Jacobs
Institute for Machine Elements and Systems Engineering, RWTH Aachen University, Aachen, Germany
Frank Hees
Information Management in Mechanical Engineering, RWTH Aachen University, Aachen, Germany
cover tunnel photo by: Matt Brown from London, England / CC BY
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https://ieeexplore.ieee.org/document/9679277/
Towards a data-driven assistance system for operating segment erectors in tunnel boring machines
ieeexplore.ieee.orgIn tunnel construction, heavy machinery like tunnel boring machines are used to increase the safety and efficiency of tunneling projects. Despite the fact that