Author(s)

Yao Mo¹, Ying Zhang¹, XueWen Li¹, Peng Zhang¹, Yin Bo^2*, RongWen Chen²

Affiliation(s)

¹Shiyan City Water Source Co., Ltd., Shiyan 442012, Hubei, China.

²Changjiang Survey, Planning, Design and Research Co., Ltd., Wuhan 430010, Hubei, China.

Corresponding Author

Yin Bo

ABSTRACT

To address the challenges encountered during Tunnel Boring Machine (TBM) construction in extremely hard rock and uneven soft-hard strata, this study designs and optimizes an adaptive cutterhead system. Existing research indicates that traditional cutterhead systems possess limitations when dealing with complex strata, primarily manifested in restricted rock-breaking efficiency and excessive cutter wear. This study first analyzes the mechanical model of rock fragmentation in extremely hard rock and the interface effects within uneven soft-hard strata. A multi-degree-of-freedom (MDOF) coupled vibration model for cutterhead-rock mass dynamics is proposed, followed by a parameter sensitivity analysis. Based on these findings, and adhering to specific design principles and performance indicators, the overall architecture of the adaptive cutterhead system is constructed, comprising mechanical, sensing, and control subsystems. The comparative selection of key module schemes involves a cutter layout adjustment mechanism and a rotational speed-thrust synergistic control unit. Regarding structural optimization, this study employs high-stiffness, lightweight topology optimization alongside wear-resistant material selection and surface strengthening to enhance disc cutter performance. Additionally, a modular system for replaceable cutters is designed. In terms of adaptive control strategies, real-time recognition of rock mass conditions, adaptive matching of rotational speed and thrust, and dynamic optimization of cutter layout are realized. The implementation of control algorithms integrates reinforcement learning-based decision models with real-time optimization algorithms. Through simulation analysis, the proposed adaptive system demonstrates significant advantages in rock-breaking efficiency and cutter wear prediction. Physical model tests further validate the adaptive adjustment performance, showing strong correlation with simulation results. Field application confirms that the system effectively improves boring efficiency, extends cutter lifespan, and yields significant economic benefits. The theoretical innovations and technical breakthroughs presented offer new insights for the design and optimization of TBM cutterhead systems, while engineering verification proves their feasibility in practical applications. Future research may further explore intelligent development directions and multi-machine collaborative tunneling technologies to address increasingly complex geological conditions and enhance the intelligence level and efficiency of TBM construction.

KEYWORDS

Tunnel Boring Machine (TBM); Adaptive cutterhead system; Extremely hard rock; Uneven soft-hard strata; Coupled dynamics; Topology optimization; Reinforcement learning; Rock-breaking efficiency

CITE THIS PAPER

Yao Mo, Ying Zhang, XueWen Li, Peng Zhang, Yin Bo, RongWen Chen. Design and optimization of TBM adaptive cutterhead system for extremely hard rock and uneven soft-hard strata. World Journal of Engineering Research. 2025, 3(5): 74-89. DOI: https://doi.org/10.61784/wjer3063.

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