DENG Jun, ZHANG Qi, CNEN Weile, et al. Coal spontaneous combustion disaster monitoring and early warning technologies and development trend for coal mines[J]. Safety in Coal Mines, 2024, 55(3): 99−110. doi: 10.13347/j.cnki.mkaq.20231578
    Citation: DENG Jun, ZHANG Qi, CNEN Weile, et al. Coal spontaneous combustion disaster monitoring and early warning technologies and development trend for coal mines[J]. Safety in Coal Mines, 2024, 55(3): 99−110. doi: 10.13347/j.cnki.mkaq.20231578

    Coal spontaneous combustion disaster monitoring and early warning technologies and development trend for coal mines

    • For reducing the incidence of mine fires, the limitations and shortcomings of the existing monitoring and early warning technologies for coal spontaneous combustion disaster are sorted out, and it is pointed out that the future development should focus on the application of advanced monitoring technology, the improvement of the accuracy of prediction technology, the development of early warning system and intelligent management. Aiming at the hidden, persistent, proliferation and difficult to control characteristics of coal spontaneous combustion disaster, the future development direction of coal spontaneous combustion disaster monitoring and early warning technology is proposed: improve the comprehensiveness of the method for determining the critical value of natural ignition of coal, and use emerging equipment and advanced technology to improve the method of determining the critical value of natural ignition of coal; for the complex coal spontaneous combustion environment of the mine, and the comprehensive and refined monitoring parameters of the spontaneous combustion of coal can be improved by studying new advanced technologies such as acoustic wave detection; promote the innovation of coal spontaneous combustion monitoring and early warning technology and the intelligence of decision-making, and use digital twin technology to provide accurate simulation and prediction capabilities, optimize prevention and control plans, provide training and emergency management, as well as the help in data analysis and decision support; focus on the intelligent integration of comprehensive perception, accurate prediction and prevention and control of coal spontaneous combustion disasters, and strengthen the research on technologies such as data analysis of coal spontaneous combustion disasters, active early warning before disasters, post-disaster accident management, and automatic closure of fire areas.
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