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Full-scale rotary cutting experiments are carried out using tunnel-boring machine disc cutters. Thrust, torque and vibration sensors are equipped on the rotary cutting machine (RCM). A stacking ensemble-learning model for real-time prediction of rock mass classification using features of mathematical statistics is proposed. Three signals, thrust, torque and a novel vibration spectrogram-based local amplification feature, are fed into the model and trained separately. The results show that the stacked ensemble-learning model has better accuracy and stability than any single model, showing a good application prospect in the rock mass classification.<\/jats:p>","DOI":"10.3390\/s24196320","type":"journal-article","created":{"date-parts":[[2024,9,30]],"date-time":"2024-09-30T07:19:37Z","timestamp":1727680777000},"page":"6320","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Experiment Study on Rock Mass Classification Based on RCM-Equipped Sensors and Diversified Ensemble-Learning Model"],"prefix":"10.3390","volume":"24","author":[{"given":"Feng","family":"Li","sequence":"first","affiliation":[{"name":"College of Civil and Transportation Engineering, Shenzhen University, Shenzhen 518060, China"},{"name":"National Key Laboratory of Green and Long-Life Road Engineering in Extreme Environment (Shenzhen), Shenzhen University, Shenzhen 518060, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8512-4931","authenticated-orcid":false,"given":"Huike","family":"Zeng","sequence":"additional","affiliation":[{"name":"School of Qilu Transportation, Shandong University, Jinan 250061, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4383-6962","authenticated-orcid":false,"given":"Hongbin","family":"Xu","sequence":"additional","affiliation":[{"name":"College of Civil and Transportation Engineering, Shenzhen University, Shenzhen 518060, China"},{"name":"National Key Laboratory of Green and Long-Life Road Engineering in Extreme Environment (Shenzhen), Shenzhen University, Shenzhen 518060, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Haokai","family":"Sun","sequence":"additional","affiliation":[{"name":"School of Qilu Transportation, Shandong University, Jinan 250061, China"},{"name":"Geotechnical and Structural Engineering Research Center, Shandong University, Jinan 250061, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2024,9,29]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"13","DOI":"10.1016\/j.tust.2021.104196","article-title":"An integrated parameter prediction framework for intelligent TBM excavation in hard rock","volume":"118","author":"Wang","year":"2021","journal-title":"Tunn. 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Constr."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"4","DOI":"10.1016\/j.tust.2016.04.002","article-title":"TBM tunnelling under adverse geological conditions: An overview","volume":"57","author":"Gong","year":"2016","journal-title":"Tunn. Undergr. Space Technol."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"187","DOI":"10.1016\/j.tust.2018.07.018","article-title":"Development and in-situ application of a real-time monitoring system for the interaction between TBM and surrounding rock","volume":"81","author":"Huang","year":"2018","journal-title":"Tunn. Undergr. Space Technol."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"16","DOI":"10.1016\/j.tust.2022.104398","article-title":"Microseismic characteristics of rockburst development in deep TBM tunnels with alternating soft-hard strata and application to rockburst warning: A case study of the Neelum-Jhelum hydropower project","volume":"122","author":"Feng","year":"2022","journal-title":"Tunn. 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