| Citation: |
LIU Xiangying. Research progress and prospects of intelligent mine ventilation[J]. Journal of Mine Automation，2025，51（4）：44-56. DOI: 10.13272/j.issn.1671-251x.18241
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The research progress has been analyzed from four aspects: ventilation parameter monitoring technology, real-time calculation methods for ventilation networks, emergency regulation technology for ventilation disasters, and the architecture of intelligent mine ventilation systems, focusing on ventilation parameter detection devices, optimization of measurement schemes, real-time monitoring and calculation of networks, anomaly diagnosis methods, and emergency regulation technologies. Currently, intelligent ventilation systems face three major challenges. First, existing ventilation parameter detection devices are insufficient in stability and accuracy, making it difficult for the system to achieve response within seconds and precise regulation. Second, the high uncertainty of the mine environment and the low level of automation in human-machine collaborative decision-making limit the adaptive optimization capabilities of the ventilation network. Third, real-time identification technologies of fire and gas compound disasters have not yet been broken through, restricting the effectiveness of emergency ventilation regulation in disaster conditions. To address these challenges, the future research directions should focus on: ① Developing new sensor devices with strong anti-interference capabilities to construct a spatiotemporal dynamic monitoring network that integrates "fixed-point monitoring+mobile inspection", enabling precise multi-parameter ventilation perception. ② Establishing an ultra-real-time simulation model for the ventilation network based on digital twin technology, and combining reinforcement learning and game theory methods to optimize the coordination between local decision-making and global strategy, thereby driving intelligent decision-making systems toward a cloud-edge-device collaborative mode. ③ Building a digital twin-driven disaster evolution simulation platform, integrating dynamic evacuation path planning and rapid deployment of robot clusters, thereby forming a three-tier emergency response system of "disaster warning-regional isolation-intelligent rescue".
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