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水浸长焰煤自燃预测预报指标气体试验研究

Experimental study on spontaneous combustion prediction index gas of water immersed long flame coal

  • 摘要: 为解决补连塔矿22煤采空区长期浸水的遗煤自燃预测预报问题,针对含水煤样自燃预测预报研究较少的问题,通过对5种不同含水率的长焰煤进行程序升温试验研究,分析温度升高过程中的遗煤自热氧化气体产物及其浓度变化规律,对煤自燃预测预报指标气体进行优选。
    研究结果表明:浸水的遗煤低温氧化具有分阶段特性,在煤样浸水程度不同的复杂情况下,提出以φ(CO)/φ(CO2)、φ(O2)/Δ φ(CO2-CO)、φ(C2H4)/ φ(C2H6)以及C2H6、C2H4和C3H8作为煤自燃预测预报指标,并且当φ(CO)/φ(CO2)≤0.1或φ(O2)/Δ φ(CO2-CO)≥0.02时,则煤处于吸氧蓄热阶段(30~100 ℃),当0.8≤φ(C2H4)/ φ(C2H6)≤1.10时,则煤处于自热氧化阶段(100~140 ℃),当φ(CO)/φ(CO2)≥0.5或φ(O2)/Δφ(CO2-CO)≤0.005时,则煤处于加速氧化阶段(140~230 ℃)。
    研究结果对采空区遗煤的自燃防控具有一定的指导作用,结合现场实际情况,及时对参数指标进行修正,完善煤自燃预测预报指标,可有效预防煤自燃灾害事故的发生。

     

    Abstract: Prediction of spontaneous combustion of long-term water immersed coal is still a problem for coal mines, the research on which is limited. This paper presents an experimental study on predicting the spontaneous combustion of long-term water immersed coal in 22 gob of Bulianta Mine.A temperature programmed experiment on long flame coal with five different water cuts was conducted to analyze the changes of auto thermal oxidation gas products and their concentrations in the process of temperature increase. Then the index gas for coal spontaneous combustion prediction was optimized. The results show that the low-temperature oxidation of the water immersed coal has phased characteristics.It is proposed that φ (CO)/φ (CO2),φ (O2)/Δφ (CO2-CO),φ (C2H4)/φ(C2H6), and C2H6,C2H4 and C3H8 are used as prediction indexes for coal spontaneous combustion. When φ(CO)/φ(CO2)≤0.1 or φ(O2)/Δφ(CO2-CO)≥0.02, the coal is in the oxygen absorption and heat storage stage(30~100 ℃),when 0.8≤φ(C2H4)/φ(C2H6) ≤1.10, the coal is in the auto thermal oxidation stage(100~140 ℃), and when φ(CO)/φ(CO2)≥0.5 or φ(O2)/Δφ(CO2-CO)≤0.005, the coal is in the accelerated oxidation stage(140~230 ℃). The experimental results have the guiding role for the prevention and control of spontaneous combustion of coal in gob.In combination with the actual situation on the site, the parameter indicators should be corrected in time to improve the coal spontaneous combustion prediction index, which can effectively prevent coal spontaneous combustion disasters.

     

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