Research and Application of Multi-Equipment Autonomous Mining System in the Deep of Sanshandao Gold Mine

This paper presents a comprehensive study on the development and implementation of an unmanned mining system for deep underground metal mines, focusing on the Sanshandao Gold Mine as a case study. The research addresses the challenges associated with mining in deep, challenging environments characterized by high temperatures and humidity. To address these challenges, the paper explores the theoretical foundations and key technologies of intelligent mining, aiming to minimize the underground workforce while ensuring safe and efficient operations. An unmanned mining system is designed, comprising four layers: comprehensive control, remote centralized control, mobile control center, and intelligent operation. The system integrates smart equipment, autonomous vehicle management, multi-equipment coordination, and real-time production optimization. Technologies such as image recognition, automatic control, and LiDAR are utilized in the remote control systems for rock drilling trolley, scrapers, and fixed rockbreakers. A multimodal integration network, including a fiber optic ring network, fixed wireless base stations, and WiFi base station coverage, ensures comprehensive and redundant communication services. A production and operation scheduling system is developed to provide remote control, real-time monitoring, and job statistical analysis, enhancing scheduling efficiency and production stability. The application of these innovations at the Sanshandao Gold Mine demonstrates their practical feasibility and potential to transform mining technology towards greater informatization, digitization, and intelligence. However, the study reveals that unmanned multi-equipment collaboration still lags behind manned or remotely controlled operations, with an efficiency rate of 61%. Ongoing research and development are needed to improve autonomous capabilities, enhance communication systems, and optimize system workflows to bridge this efficiency gap and promote the widespread adoption of intelligent mining technologies in the industry.