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Cutter wear evaluation from operational parameters in EPB tunneling of Chengdu Metro

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doi: 10.1016/j.tust.2019.103043
Authors:Rong Xuening; Lu Hao; Wang Mingyang; Wen Zhu; Rong Xiaoli
Author Affiliations:Primary:
Nanjing University of Science and Technology, School of Mechanical Engineering, Nanjing, China
University of People's Liberation Army (PLA), China
Volume Title:Tunnelling and Underground Space Technology
Source:Tunnelling and Underground Space Technology, Vol.93. Publisher: Elsevier, Oxford-New York, International. ISSN: 0886-7798
Publication Date:2019
Note:In English. 19 refs.; illus., incl. 5 tables
Summary:Cutterhead inspection and maintenance is an important reason for operational delays in EPB tunneling project. In order to minimize the number of maintenance stops, non-entry evaluation of cutter wear is required. This study introduces a new prediction model for cutter wear based on automatically recorded operational parameters including cutterhead torque, rotational speed and flow rate of foaming liquid. Real-time operational data was processed to obtain two robust input variables including work done by cutterhead torque and volume of foaming liquid. Field data from 20 tunnel sections of Chengdu Metro were then analyzed to develop quantitative relationships between the two input variables and cutter wear. These tunnel sections were excavated by two types of EPB machines in gravels and weathered rocks. The analyzed real-time operational data covers an excavated length of 14140 m. To ignore the influence of tunnel diameter, prediction model of cutter wear per unit volume of excavation was also developed. The proposed models provide reasonable evaluation of tool wear (R2 up to 0.857) in gravels and weathered rocks, for which cutter wear prediction based on geological parameters is rather difficult because of huge variation of the materials.
Subjects:Abrasion; Construction; Earth pressure; Excavations; Prediction; Rock mechanics; Tunnel boring machines; Tunnels; Weathered materials; Asia; China; Far East; Sichuan China; Chengdu Metro
Record ID:865629-1
Copyright Information:GeoRef, Copyright 2021 American Geosciences Institute. Reference includes data from CAPCAS, Elsevier Scientific Publishers, Amsterdam, Netherlands
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