In line with the sensitivity of coal drillings temperature and coalbed temperature to the dangerous zone of coal and gas outburst, two temperature sensitive indexes (△Tm, △tm) for forecasting dangerousness of coal f...In line with the sensitivity of coal drillings temperature and coalbed temperature to the dangerous zone of coal and gas outburst, two temperature sensitive indexes (△Tm, △tm) for forecasting dangerousness of coal face and heading face outburst are defined, and deal with the foundation on drillings and coalbed temperatures used as sensitive indexes and the principle and method of determining drillings and coalbed temperatures. On the basis of this, we put forward the method for forecasting dangerousness of coal face and heading face outburst by two temperature sensitive indexes and determine the critical values of two temperature sensitive indexes (△Tm= 5.5℃, △tm = 4.5℃) by in-situ observation and requirement for determining sensitive index.展开更多
The present situation of lacking fast and effective coal and gas outburst prediction techniques will lead to long out- burst prevention cycles and poor accurate prediction effects and slows down coal roadway drive spe...The present situation of lacking fast and effective coal and gas outburst prediction techniques will lead to long out- burst prevention cycles and poor accurate prediction effects and slows down coal roadway drive speed seriously. Also, due to historical and economic reasons, some coal mines in China are equipped with poor safety equipment, and the staff professional capability is low. What＇s worse, artificial and mine geological conditions have great influences on the traditional technologies of coal and gas outburst prediction. Therefore, seeking a new fast and efficient coal and gas outburst prediction method is nec- essary. By using system engineering theory, combined with the current mine production conditions and based on the coal and gas outburst composite hypothesis, a coal and gas outburst spatiotemporal forecasting system was established. This system can guide forecasting work schedule, optimize prediction technologies, carry out step-by-step prediction and eliminate hazard hier- archically. From the point of view of application, the proposed system improves the prediction efficiency and accuracy. On this basis, computational intelligence methods to construct disaster information analysis platform were used. Feed-back results pro- vide decision support to mine safety supervisors.展开更多
文摘In line with the sensitivity of coal drillings temperature and coalbed temperature to the dangerous zone of coal and gas outburst, two temperature sensitive indexes (△Tm, △tm) for forecasting dangerousness of coal face and heading face outburst are defined, and deal with the foundation on drillings and coalbed temperatures used as sensitive indexes and the principle and method of determining drillings and coalbed temperatures. On the basis of this, we put forward the method for forecasting dangerousness of coal face and heading face outburst by two temperature sensitive indexes and determine the critical values of two temperature sensitive indexes (△Tm= 5.5℃, △tm = 4.5℃) by in-situ observation and requirement for determining sensitive index.
文摘The present situation of lacking fast and effective coal and gas outburst prediction techniques will lead to long out- burst prevention cycles and poor accurate prediction effects and slows down coal roadway drive speed seriously. Also, due to historical and economic reasons, some coal mines in China are equipped with poor safety equipment, and the staff professional capability is low. What＇s worse, artificial and mine geological conditions have great influences on the traditional technologies of coal and gas outburst prediction. Therefore, seeking a new fast and efficient coal and gas outburst prediction method is nec- essary. By using system engineering theory, combined with the current mine production conditions and based on the coal and gas outburst composite hypothesis, a coal and gas outburst spatiotemporal forecasting system was established. This system can guide forecasting work schedule, optimize prediction technologies, carry out step-by-step prediction and eliminate hazard hier- archically. From the point of view of application, the proposed system improves the prediction efficiency and accuracy. On this basis, computational intelligence methods to construct disaster information analysis platform were used. Feed-back results pro- vide decision support to mine safety supervisors.
