Machine learning forecasting models of disc cutters life of tunnel boring machine-Reference-Cited by-同舟云学术

Machine learning forecasting models of disc cutters life of tunnel boring machine

Published:2021-08 Issue: Volume:128 Page:103779
ISSN:0926-5805
Container-title:Automation in Construction
language:en
Short-container-title:Automation in Construction

Author:

Mahmoodzadeh Arsalan,Mohammadi Mokhtar,Hashim Ibrahim Hawkar,Nariman Abdulhamid Sazan,Farid Hama Ali Hunar,Mohammed Hasan Ahmed,Khishe Mohammad,Mahmud Hoger

Publisher

Elsevier BV

Subject

Building and Construction,Civil and Structural Engineering,Control and Systems Engineering

Reference38 articles.

1. Performance prediction of TBM disc cutting on marble rock under different load cases;Tan;KSCE J. Civ. Eng.,2018

2. Theoretical research and simulation analysis on the cutter spacing of double disc cutters breaking rock;Zhou;KSCE J. Civ. Eng.,2019

3. A TBM cutter life prediction method based on rock mass classification;Wang;KSCE J. Civ. Eng.,2020

4. Theoretical prediction of wear of disc cutters in tunnel boring machine and its application;Zhang;J. Rock Mech. Geotech. Eng.,2019

5. Testing conditions and geomechanical properties influencing the CERCHAR abrasiveness index (CAI) value;Plinninger;Int. J. Rock Mech. Min. Sci.,2003

Cited by 49 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. A generative adversarial learning strategy for spatial inspection of compaction quality;Advanced Engineering Informatics;2024-10

2. Towards reinforcement learning - driven TBM cutter changing policies;Automation in Construction;2024-09

3. Predicting existing tunnel deformation from adjacent foundation pit construction using hybrid machine learning;Automation in Construction;2024-09

4. Machine learning-based prediction model for disc cutter life in TBM excavation through hard rock formations;Tunnelling and Underground Space Technology;2024-08

5. Prediction of abnormal TBM disc cutter wear in mixed ground condition using interpretable machine learning with data augmentation;Journal of Rock Mechanics and Geotechnical Engineering;2024-08