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于健浩, 祝凌甫, 徐刚. 煤矿智能综采工作面安全高效开采适应性评价[J]. 煤炭科学技术, 2019, (3).
引用本文: 于健浩, 祝凌甫, 徐刚. 煤矿智能综采工作面安全高效开采适应性评价[J]. 煤炭科学技术, 2019, (3).
YU Jianhao, ZHU Lingfu, XU Gang. Safety and high efficiency adaptability evaluation of coal mine intelligent fully-mechanized mining face[J]. COAL SCIENCE AND TECHNOLOGY, 2019, (3).
Citation: YU Jianhao, ZHU Lingfu, XU Gang. Safety and high efficiency adaptability evaluation of coal mine intelligent fully-mechanized mining face[J]. COAL SCIENCE AND TECHNOLOGY, 2019, (3).

煤矿智能综采工作面安全高效开采适应性评价

Safety and high efficiency adaptability evaluation of coal mine intelligent fully-mechanized mining face

  • 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。

     

    Abstract: 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.

     

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