YANG Xiaocong, YIN Shenghua. Research status and prospects of efficient green mining technology and intelligent equipment for ultra large deep iron mines[J]. Chinese Journal of Engineering. DOI: 10.13374/j.issn2095-9389.2024.01.15.001
Citation: YANG Xiaocong, YIN Shenghua. Research status and prospects of efficient green mining technology and intelligent equipment for ultra large deep iron mines[J]. Chinese Journal of Engineering. DOI: 10.13374/j.issn2095-9389.2024.01.15.001

Research status and prospects of efficient green mining technology and intelligent equipment for ultra large deep iron mines

  • China’s iron ore deposits are generally characterized by substantial thickness and low grade, and this presents challenges for traditional mining methods to satisfy market demands economically and efficiently. To maintain a competitive edge in the market while complying with environmental and low-carbon development principles, large-scale, low-cost, environmentally friendly, and low-carbon mining models that can handle tens of millions of tons annually must be adopted. Such models not only considerably lower the unit cost of ore extraction but also minimize the environmental effect, lower the carbon emissions, and attain sustainable resource development and utilization. This paper studies the new mining models, advanced safety technologies, green requirements, and intelligent trends in the efficient, green exploitation of large-scale deep mines. This study aims to address three crucial issues: the principles and methods for the continuous large-scale mining of deep thick ore bodies, the mechanisms and mechanical behaviors of catastrophic events triggered by strong cyclic disturbances in high-stress rock masses, and the adaptive intelligent energy-saving ventilation mechanisms for deep hot mines with multiple fans. This paper aims to advance five key technologies: spatiotemporal collaborative continuous mining techniques for deep inclined thick ore bodies, efficient sensing devices for large-scale mining dynamic environments and disaster prevention and control technologies, high-flow continuous steady-state preparation and transportation technologies for tailings paste, multistage dynamic intelligent ventilation and direct cooling technologies for thermal hazard prevention in deep hot mines, and intelligent decision-making and collaborative operation control technologies for the equipment chain in stope mining operations. These innovations aim to attain the efficient continuous mining of thick ore bodies with large parameters; the effective disaster prevention and control for rock mechanics and dynamic disasters in large-scale mining; the efficient utilization of mining and processing of solid waste through backfilling, intelligent energy-saving ventilation, and thermal hazard prevention; and the efficient collaboration of intelligent stope mining operation chains. The eventual objective is to develop new theories, technologies, methods, and equipment for the green, intelligent mining of metallic mines at depths surpassing one kilometer, to create a demonstrative mine, and to form a technological system for the efficient, green mining of large-scale deep mines that can be widely applied. This paper aspires to improve the capacity for large-scale green development of deep strategic mineral resources in China comprehensively and to provide a theoretical foundation and technical support for the large-scale green exploitation of deep mineral resources. By addressing these key issues and developing the associated technologies, this paper aims to improve the efficiency, safety, and sustainability of mining operations in deep iron ore deposits remarkably, ultimately contributing to the long-term viability and competitiveness of the mining industry in China.
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