DEVELOPMENT OF AN AUTOPILOT MODEL FOR SHIELD TUNNELING MACHINES BY MACHINE LEARNING

Abstract

 Although a shield tunneling machine should excavate a tunnel along its planned alignment, deviations occur between the planned alignment and the actual result. When this happens, it is necessary to draw a target alignment that returns deviations to the planned alignment gradually and to excavate with the shield machine along the target alignment. These operations are controlled by skilled engineers and trial-and-error operations, and labor-saving is an issue. In addition, skilled excavation managers and operators are aging, their skills may be lost in the near future. Therefore, machine learning is expected to play an important role in automating the operation of shield tunneling machines. However, related studies have been unable to automatically calculate the optimum operation parameters for excavation along the target alignment. Therefore, this study sought to use machine learning to develop an autopilot model, which is a method to automatically calculate optimal operation parameters of the shield machine for the straight section of a planned alignment.