煤矿智能综采工作面安全高效开采适应性评价
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摘要
为研究煤层赋存情况、地质构造特征、开采技术条件等因素对智能综采工作面的影响程度,掌握不同条件下智能综采工作面安全高效开采的适应程度,对神东煤炭集团多家矿井智能综采工作面开展实地调研,通过现场技术咨询及分析工作面地质条件、开采技术条件、装备水平及智能综采过程中存在的问题,确定煤层稳定性、工作面倾斜长度、断层影响程度是影响智能综采适应性的主控因素。由此归纳出煤矿智能综采适应性评价指标体系,基于模糊综合评价法,通过对评价指标进行量化,采用AHP法确定因素权重,建立了智能综采适应性评价模型,实现了对智能综采工作面开采效能和安全性的智能评价,可为工作面采前地理信息系统提供静态决策支持。
In order to study the influence degree of coal seam occurrence,geological structure characteristics and mining technical conditions on intelligent fully-mechanized mining face,and master the adaptability of intelligent fully-mechanized mining face under different conditions,the intelligent comprehensive mining face of Shendong Coal Group was investigated.Through the technical consulting and analysis of the geological conditions of the working face,mining technical conditions,equipment level and the existing problems,the main controlling factors affecting the adaptability of intelligent comprehensive mining were obtained,including coal seam stability,working face length and degree of fault impact. Therefore,the index system of coal mine intelligent comprehensive mining adaptability evaluation was summarized.Based on the fuzzy comprehensive evaluation method,the evaluation indicators were quantified. And use the AHP method to determine the factor weights.Then establish the adaptive evaluation model for coal mine intelligent comprehensive mining,and the intelligent evaluation of mining efficiency and safety of intelligent fully-mechanized mining face was realized.
In order to study the influence degree of coal seam occurrence,geological structure characteristics and mining technical conditions on intelligent fully-mechanized mining face,and master the adaptability of intelligent fully-mechanized mining face under different conditions,the intelligent comprehensive mining face of Shendong Coal Group was investigated.Through the technical consulting and analysis of the geological conditions of the working face,mining technical conditions,equipment level and the existing problems,the main controlling factors affecting the adaptability of intelligent comprehensive mining were obtained,including coal seam stability,working face length and degree of fault impact. Therefore,the index system of coal mine intelligent comprehensive mining adaptability evaluation was summarized.Based on the fuzzy comprehensive evaluation method,the evaluation indicators were quantified. And use the AHP method to determine the factor weights.Then establish the adaptive evaluation model for coal mine intelligent comprehensive mining,and the intelligent evaluation of mining efficiency and safety of intelligent fully-mechanized mining face was realized.
引文
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[15] YU Jianhao.Prediction of top-coal caving and drawing characteristics using artificial neural networks in extremely thick coal seam[C].Proceedings of 2015 International Conference on Mechanical,Electronic and Information Technology Engineering,2015.
[16]于健浩.西南复杂难采煤层安全开采模式智能化决策[J].煤矿开采,2017,22(4):16-22.YU Jianhao. Intelligent decision making of safety mining model under complicated geological conditions in southwest China[J].Coal Mining Technology,2017,22(4):16-22.
[2]王显政.坚持创新驱动推动煤炭智能绿色开采与生态建设[J].中国煤炭工业,2018(1):8-10.WANG Xianzheng.Adhere to innovation drive promote smart green mining and ecological construction of coal[J]. China Coal Industry,2018(1):8-10.
[3]王国法,范京道,徐亚军,等.煤炭智能化开采关键技术创新进展与展望[J].工矿自动化,2018,44(2):5-12.WANG Guofa,FAN Jingdao,XU Yajun,et al.Innovation and prospect on key technologies of intelligent coal mining[J].Industry and Mine Automation,2018,44(2):5-12.
[4]李梅,杨帅伟,孙振明,等.智慧矿山框架与发展前景研究[J].煤炭科学技术,2017,45(1):121-128,134.LI Mei,YANG Shuaiwei,SUN Zhenming,et al.Study on framework and development prospects of intelligent mine[J]. Coal Science and Technology,2017,45(1):121-128,134.
[5]王国法,王虹,任怀伟,等.智慧煤矿2025情景目标和发展路径[J].煤炭学报,2018,43(2):295-305.WANG Guofa,WANG Hong,REN Huaiwei,et al. 2025 scenarios and development path of intelligent coal mine[J].Journal of China Coal Society,2018,43(2):295-305.
[6] YANG Jianjian.Intelligent recognition of cutting load of coal mining equipment based on vibration wavelet packet feature[C].Proceedings of 2017 9th International Conference on Modelling,Identification and Control(ICMIC 2017).Kunming University of Science and Technology,IEEE Control System Society Beijing Chapter,IEEE Beijing Section,2017:6.
[7]任怀伟,孟祥军,李政,等.8m大采高综采工作面智能控制系统关键技术研究[J].煤炭科学技术,2017,45(11):37-44.REN Huaiwei,MENG Xiangjun,LI Zheng,et al.Study on key technology of intelligent control system applied in 8m large mining height fully-mechanized face[J]. Coal Science and Technology,2017,45(11):37-44.
[8]康红普,王国法,姜鹏飞,等.煤矿千米深井围岩控制及智能开采技术构想[J].煤炭学报,2018,43(7):1789-1800.KANG Hongpu,WANG Guofa,JIANG Pengfei,et al.Conception for strata control and intelligent mining technology in deep coal mines with depth more than 1000m[J]. Journal of China Coal Society,2018,43(7):1789-1800.
[9]袁亮.煤炭精准开采科学构想[J].煤炭学报,2017,42(1):1-7.YUAN Liang.Scientific conception of precision coal mining[J].Journal of China Coal Society,2017,42(1):1-7.
[10]宋振骐,夏洪春,卢国志.“中国制造2025”背景下中厚煤层智能开采技术发展方向[J].同煤科技,2016(1):1-5,9.SONG Zhenqi,XIA Hongchun,LU Guozhi.Development direction of intelligent mining technology of medium-thickness coal seam under the background of"China-made 2025"[J].Science and Technology of Datong Coal Mining Administration,2016(1):1-5,9.
[11]徐建军.煤矿智能化综采技术现状及展望[J].陕西煤炭,2017,36(3):44-47,13.XU Jianjun.Current status and prospect of intelligent fully-mechanized mining technology in coal mine[J].Shaanxi Coal,2017,36(3):44-47,13.
[12]范建,于健浩.我国煤矿科学开采技术的新进展[J].煤矿开采,2014,19(5):4-7.FAN Jian,YU Jianhao. New progress of scientific mining technology in Chinese coal mine[J]. Coal Mining Technology,2014,19(5):4-7.
[13]杨伦标,高英仪.模糊数学原理及应用[M].广州:华南理工大学出版社,2000:86-91.
[14]王旭鸣.煤矿综采智能决策支持系统[J].煤矿机械,2015,36(9):263-265.WANG Xuming.Intelligent decision support system for coal mine[J].Coal Mine Machinery,2015,36(9):263-265.
[15] YU Jianhao.Prediction of top-coal caving and drawing characteristics using artificial neural networks in extremely thick coal seam[C].Proceedings of 2015 International Conference on Mechanical,Electronic and Information Technology Engineering,2015.
[16]于健浩.西南复杂难采煤层安全开采模式智能化决策[J].煤矿开采,2017,22(4):16-22.YU Jianhao. Intelligent decision making of safety mining model under complicated geological conditions in southwest China[J].Coal Mining Technology,2017,22(4):16-22.