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YANG Hongwei, QIAN Zhiliang. Research on gas overrun real-time early warning technology in mine[J]. COAL SCIENCE AND TECHNOLOGY, 2019, (8).
Citation: YANG Hongwei, QIAN Zhiliang. Research on gas overrun real-time early warning technology in mine[J]. COAL SCIENCE AND TECHNOLOGY, 2019, (8).

Research on gas overrun real-time early warning technology in mine

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  • Available Online: April 02, 2023
  • Published Date: August 24, 2019
  • In order to solve the problem of forecasting gas overrun,according to the precursory characteristics of coal body and working face environment before gas exceeds the limit,the index system of gas overrun early warning was established from the aspects of gas,ventilation,geological structure and management and other influencing factors,using the gas,the influencing factors of gas overrun in a coal mine,volume fraction change index as a real-time early warning indicator,and other indicators are used as trend early warning indicators.Based on the problem of high false alarm rate of single indicator of gas exceeding limit,a multi-index model of gas exceeding limit is established by using the theory of fuzzy mathematics,and the weights and evaluation values are determined.A real-time warning system for gas overrun in working face are established in a affiliated coal mine,and the three-level warning results of red,yellow and green gas overrun were output,and the probability of occurrence of gas overrun are obtained.According to the results of gas overrun warning,the corresponding measures can be taken and this can greatly reduce the number of gas overrun.The comparison between multi-index model warning and single-index model warning is made: the number of red warning times can be reduced by more than 50% and the number of yellow warning by more than 30%,indicating the multi-index quantitative model is more reasonable than the single-index model,which improves the accuracy of early warning,provides management basis for coal mine safety production and supply references for similar early warning index research.
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