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One-Dimensional Convolutional Neural Network for Pipe Jacking EPB TBM Cutter Wear Prediction
(Open access)
One-Dimensional Convolutional Neural Network for Pipe Jacking EPB TBM Cutter Wear Prediction
by
Kursat Kilic1,*, Hisatoshi Toriya 1, Yoshino Kosugi 1 Tsuyoshi Adachi 1 and Youhei Kawamura 2
1 Department of Geosciences, Geotechnology and Materials Engineering for Resources, Graduate School of International Resource Sciences, Akita University, Akita 010-8502, Japan
2 Division of Sustainable Resources Engineering, Faculty of Engineering, Hokkaido University, Kita 13, Nishi 8, Kita-ku, Sapporo 060-8628, Japan
* Author to whom correspondence should be addressed.
Academic Editor: Daniel Dias
Appl. Sci. 2022, 12(5), 2410; https://doi.org/10.3390/app12052410
Received: 10 February 2022 / Revised: 24 February 2022 / Accepted: 24 February 2022 / Published: 25 February 2022
cover tunnel photo by: Matt Brown from London, England / CC BY
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One-Dimensional Convolutional Neural Network for Pipe Jacking EPB TBM Cutter Wear Prediction
www.mdpi.comAn earth pressure balance (EPB) TBM is used in soft ground conditions, and these conditions lead to the fluctuation and instability of machine parameters. Machine parameters influence cutter wear and tunnel excavation. For this reason, to evaluate...