Research on the technical architecture of the intelligent control system for excavation workface driven by digital twin technology

The excavation working face in underground coal mine is confronted with problems such as complex geological environment, insufficient equipment coordination, and lagging data interaction. To improve the remote monitoring of tunneling roadways, break through the autonomous operation of tunneling equipment and the coordination level of multiple equipment. It proposes a digital twin-driven intelligent control system architecture for excavation working faces. Through the deep integration of physical working faces, virtual working faces, twin data, and application service layers, a closed-loop system of "modeling - perception - decision-making - control" is constructed. This study utilizes technologies such as real-time perception of multi-source heterogeneous data and collaborative control to achieve monitoring of the operation status of excavation equipment groups under complex conditions, dynamic collection of environmental parameters, virtual-real mapping, and dynamic optimization of the entire process of excavation technology in virtual and real worlds. It solves problems such as lagging static model updates and low equipment coordination efficiency. This study reveals core issues in current control systems, including inconsistent conceptual descriptions and ambiguous core system functions. Based on digital twin technology, targeted solutions are proposed. Through key technologies including intelligent sensing, real-time correction, precise positioning and navigation, and remote control, the intelligent operation of the control system is supported. Through practical application cases, the feasibility of the system in real-time data-driven and equipment collaborative control. To address system deficiencies, efforts should focus on optimizing multi-source heterogeneous data perception, developing adaptive tunnel update algorithms, constructing efficient data transmission networks, developing multi-objective dynamic decision-making algorithms, and upgrading immersive remote control technologies. This provides technical support for realizing unmanned and autonomous operation of excavation working faces and offers theoretical and technical reference for intelligent control.