Feng Liang

The development and maturation of TBM (tunnel boring machine) technology have significantly improved the accuracy and richness of excavation data, driving advancements in intelligent tunneling research. However, challenges remain in managing data noise and parameter coupling, limiting the interpretability of traditional machine learning models regarding TBM parameter relationships. This study proposes a cutterhead rotation speed prediction model based on dimensional analysis. By utilizing boxplot methods and low-pass filtering techniques, excavation data were preprocessed to select appropriate operational and mechanical parameters. A dimensionless model was established and integrated with elastic net regression to quantify parameters. Using TBM cluster data from a water diversion tunnel project in Xinjiang, the accuracy and generalizability of the model were validated. Results indicate that the proposed model achieves high prediction accuracy, effectively capturing trends in cutterhead rotation speed while demonstrating strong generalizability.

This study provides a theoretical foundation for optimizing tunnel boring machine (TBM) excavation parameters under diverse geological conditions, offering significant engineering value by enhancing construction efficiency and reducing costs. As the development of underground spaces advances, TBMs play a pivotal role in tunnel excavation. TBMs enhance safety in excavation by mechanically breaking rock, reducing the reliance on explosives, and the associated risks of blasts. The shield support minimizes surrounding rock collapse, advanced geological forecasting mitigates risks posed by complex geologies, and intelligent monitoring systems improve operational safety. To enhance TBM efficiency and safety, this study developed a 3D simulation model of rock breaking by disc cutters using the discrete element method. This study systematically examined the effects of excavation parameters, including disc-cutter diameter, cutter spacing, and penetration, on rock-breaking performance. The findings reveal, that as the disc-cutter diameter increases, the rolling force also increases, while the rock-breaking specific energy initially rises and then declines. The 19-inch disc cutter demonstrated a superior rock-breaking efficiency in conventional excavation operations. At a cutter spacing of 60 mm, the rock-breaking specific energy reached its lowest value, representing optimal efficiency. Furthermore, as the penetration increased, both the rolling force and rock fragmentation volume grew, whereas the specific energy decreased, further improving the rock-breaking efficiency.