基于瓦斯浓度监测反馈的采煤机截割速度自适应调节技术
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摘要
在高瓦斯薄煤层工作面实施自动化开采期间,对于工作面瓦斯浓度超限所造成的采煤机停机,开机率下降等技术难题,在现场实测薄煤层综采工作面瓦斯浓度的基础上,对工作面瓦斯浓度分布规律进行了理论分析,探讨了采煤机割煤速度对工作面瓦斯浓度的影响机制,结果表明:①上隅角及采煤机位置为采煤机割煤期间工作面瓦斯浓度监测的关键位置,且以监测上隅角瓦斯浓度为主;②上隅角瓦斯浓度与采煤机割煤速度基本成正相关关系、与煤机距上隅角距离基本成负相关关系。通过实时监测工作面的瓦斯浓度,调节工作面采煤机截割速度以达到降低工作面瓦斯浓度是可行的,现场工业性试验了采煤机截割速度的自适应调节技术,结果表明:经由瓦斯浓度实时监测来反馈调节工作面采煤机截割速度降低了高瓦斯薄煤层工作面瓦斯浓度超限概率,为实现高瓦斯薄煤层工作面的自动化开采提供了技术借鉴。
Because of gas overrun,the problem of frequent shutdown and low operating rate of shearer often appears during the period of automation mining in thin seam with high gas. Based on the field measurements and theoretical analysis about gas concentration in the panel,the influence mechanism between cutting speed and gas concentration is explored. Upper corner is the main gas monitoring point with shearer position during automatic mining. And there is a positive correlation between gas concentration in the upper corner and cutting speed basically. However,gas concentration in the upper corner is negatively correlated with the distance between the shearer and upper corner. Accordingly,self-adaptive adjustment technology of shearer cutting speed base on monitoring feedback of methane concentration was proposed. As a result of industrial field tests,the probability of gas concentration exceeding the limit was decreased. It can provide technical reference for automation mining in thin seam with high gas.
Because of gas overrun,the problem of frequent shutdown and low operating rate of shearer often appears during the period of automation mining in thin seam with high gas. Based on the field measurements and theoretical analysis about gas concentration in the panel,the influence mechanism between cutting speed and gas concentration is explored. Upper corner is the main gas monitoring point with shearer position during automatic mining. And there is a positive correlation between gas concentration in the upper corner and cutting speed basically. However,gas concentration in the upper corner is negatively correlated with the distance between the shearer and upper corner. Accordingly,self-adaptive adjustment technology of shearer cutting speed base on monitoring feedback of methane concentration was proposed. As a result of industrial field tests,the probability of gas concentration exceeding the limit was decreased. It can provide technical reference for automation mining in thin seam with high gas.
引文
[1]Wang Chen,Tu Shihao,Chen Min,et al.Optimal Selection of a Longwall Mining Method for a Thin Coal Seam Working Face[J].Arabian Journal for Science and Engineering,2016,41(9):3771-3781.
[2]袁亮.薄煤层开采技术与装备研究[J].煤矿开采,2011(3):15-18.
[3]袁亮.煤炭精准开采科学构想[J].煤炭学报,2017(1):1-7.
[4]王沉.薄煤层自动化长壁综采关键技术及决策支持系统研究[D].徐州:中国矿业大学,2016.
[5]王刚,方新秋,谢小平,等.薄煤层无人工作面自动化开采技术应用[J].工矿自动化,2013(8):9-13.
[6]宁桂峰.极薄煤层综采自动化应用研究[J].煤炭科学技术,2013(11):18-21.
[7]李春丽.基于无线技术的煤矿瓦斯监控系统的研制[J].煤矿机械,2015(5):95-96.
[8]董丁稳,屈世甲,王红.基于多测点关联分析的工作面瓦斯浓度实时预警[J].中国安全科学学报,2015(1):111-115.
[9]王其军,程久龙.基于免疫神经网络模型的瓦斯浓度智能预测[J].煤炭学报,2008(6):665-669.
[10]方新秋.薄煤层无人工作面煤与瓦斯共采关键技术[M].徐州:中国矿业大学出版社,2013.
[2]袁亮.薄煤层开采技术与装备研究[J].煤矿开采,2011(3):15-18.
[3]袁亮.煤炭精准开采科学构想[J].煤炭学报,2017(1):1-7.
[4]王沉.薄煤层自动化长壁综采关键技术及决策支持系统研究[D].徐州:中国矿业大学,2016.
[5]王刚,方新秋,谢小平,等.薄煤层无人工作面自动化开采技术应用[J].工矿自动化,2013(8):9-13.
[6]宁桂峰.极薄煤层综采自动化应用研究[J].煤炭科学技术,2013(11):18-21.
[7]李春丽.基于无线技术的煤矿瓦斯监控系统的研制[J].煤矿机械,2015(5):95-96.
[8]董丁稳,屈世甲,王红.基于多测点关联分析的工作面瓦斯浓度实时预警[J].中国安全科学学报,2015(1):111-115.
[9]王其军,程久龙.基于免疫神经网络模型的瓦斯浓度智能预测[J].煤炭学报,2008(6):665-669.
[10]方新秋.薄煤层无人工作面煤与瓦斯共采关键技术[M].徐州:中国矿业大学出版社,2013.