Soft ground micro TBM jack speed and torque prediction using machine learning models through operator data and micro TBM-log data synchronization
Kursat Kilic,
Owada Narihiro,
Hajime Ikeda
et al.
Abstract:Tunnel Boring Machines (TBMs) are pivotal in underground projects like subways, highways, and water supply tunnels. Predicting and monitoring jack speed and torque is crucial for optimizing TBM excavation efficiency. Conventionally, skilled operators manually adjust numerous tunnelling parameters to regulate the machine's progress. In contrast, machine learning (ML) algorithms offer a promising avenue where computers learn from operator actions to establish parameter relationships autonomously. This study intr… Show more
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