Measurement and Enhancing Prediction of EPBM Torque using Actual Machine Data

Date
2023-11
Authors
Koohsari, Ali
Kalatehjari, Roohollah
Moosazadeh, Sayfoddin
Hajihassani, Mohsen
Tarafrava, Mostafa
Supervisor
Item type
Journal Article
Degree name
Journal Title
Journal ISSN
Volume Title
Publisher
Elsevier BV
Abstract

The cutterhead torque of an Earth Pressure Balance Machine (EPBM) plays a critical role in determining the performance of mechanized tunneling in urban areas. However, as this parameter is not directly set by the operator but is a function of geological conditions, thrust force, screw conveyor revolution speed, and soil conditions, it is closely linked to geotechnical parameters and machine settings. Despite previous attempts to predict EPBM torque using Shi's physical model, accuracy has been lacking. This study aims to improve the accuracy of this prediction by utilizing actual data from an EPBM used in a metro line tunneling project to identify the primary factors influencing torque and to modify related equations accordingly. To evaluate the performance of existing models and the predictions made by the presented method, various metrics are utilized, including the correlation between all torque values, the relationship between torque and thrust values, and the connection between thrust pressure and penetration. The results indicate that in addition to geotechnical parameters, machine settings such as thrust force, cutterhead revolution speed, arching pressure, soil conditions, and chamber pressure significantly impact the torque value. The study found that the thrust force exerted by the EPBM is a key factor influencing torque.

Description
Keywords
46 Information and Computing Sciences , 49 Mathematical Sciences , 0102 Applied Mathematics , 0801 Artificial Intelligence and Image Processing , 0913 Mechanical Engineering , Electrical & Electronic Engineering , 46 Information and computing sciences , 49 Mathematical sciences
Source
Measurement, ISSN: 0263-2241 (Print), Elsevier BV, 113780-113780. doi: 10.1016/j.measurement.2023.113780
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