高士岗, 高登彦, 欧阳一博, 柴敬, 张丁丁, 任文清. 中薄煤层智能开采技术及其装备[J]. 煤炭学报, 2020, 45(6). DOI: 10.13225/j.cnki.jccs.ZN20.0246
引用本文: 高士岗, 高登彦, 欧阳一博, 柴敬, 张丁丁, 任文清. 中薄煤层智能开采技术及其装备[J]. 煤炭学报, 2020, 45(6). DOI: 10.13225/j.cnki.jccs.ZN20.0246
GAO Shigang, GAO Dengyan, OUYANG Yibo, CHAI Jing, ZHANG Dingding, REN Wenqing. Intelligent mining technology and its equipment for medium thickness thin seam[J]. Journal of China Coal Society, 2020, 45(6). DOI: 10.13225/j.cnki.jccs.ZN20.0246
Citation: GAO Shigang, GAO Dengyan, OUYANG Yibo, CHAI Jing, ZHANG Dingding, REN Wenqing. Intelligent mining technology and its equipment for medium thickness thin seam[J]. Journal of China Coal Society, 2020, 45(6). DOI: 10.13225/j.cnki.jccs.ZN20.0246

中薄煤层智能开采技术及其装备

Intelligent mining technology and its equipment for medium thickness thin seam

  • 摘要: 针对我国薄煤层产量逐年增长和开采技术相对滞后的现状,提出了透明化自适应型中厚偏薄煤层智能开采模式。 以神东矿区为例,对当前的中厚偏薄煤层智能化开采技术进行了总结,介绍了中厚偏薄煤层智能开采情况,由此提出厚度1.0-1.7m的煤层称为中薄煤层的分类概念,以适应煤矿智能化开采和优先发展的需要。 首先,在综合处理多源异构信息的基础上,将三维初始地质模型、激光扫描动态数字化工作面、顶底煤厚度探测结果以及煤机姿身数字化,实时提交给智能开采系统进行超前规划,生成动态透明四维地质模型。随后,根据实时生成的动态四维地质模型,获取每个截割位置的顶、底板高度数据,结合煤机姿态参数和采煤机的绝对位置坐标,及工作面平直度要求,对未来几个割煤循环的采煤机调高策略进行提前规划,形成基于动态透明工作面智能化割煤技术。 提出了“十二工步”割煤工艺,建立采煤机电缆拖拽系统。 最终,以动态四维地质模型构建、采煤机智能化割煤、工作面自动调直、机器人巡检、采煤机电缆拖拽、液压支架自动跟机以及智能协同联控等技术为依托,建立了具备综采工作面全面感知、设备远程集控、协同联动、自动控制、多维数据融合、隐患自动辨识、流程数据驱动、智能辅助决策的中厚偏薄煤层智能化综采工作面开采体系,实现由可视化远程干预型智能开采模式向透明化智能自适应型智能开采模式的转变。 实践表明,动态四维地质模型的构建解决了薄煤层开采煤岩分界线识别,对未来10刀割煤循环给出调高策略,预设割煤轨迹与实际割煤轨迹趋势曲线位置偏差小于 0.3m。 榆家梁煤矿 43101 工作面实践,日割煤15刀,年产量达221.6万 t,生产工效提高15.08%;工作面无直接操作人员,仅有1人巡视。

     

    Abstract: Currently the thin coal seam output increases year by year and the mining technology lags behind. In this paper,a transparent adaptive and intelligent mining model for medium-thick to thin coal seams is proposed. Taking the Shendong Mining Area as an example,this paper summarizes the current intelligent mining technology for medium-thick to thin coal seams,and introduces the situation of intelligent mining for medium-thick to thin coal seams. The concept of classifying medium-thin coal seams as having a thickness of 1. 0-1. 7 m is put forward to meet the needs of intelligent mining and the priority development of coal mines. On the basis of comprehensive processing of multi-source and heterogeneous information,the three-dimensional initial geological model,laser scanning dynamic digitized working face,top and bottom coal thickness detection results and shearer attitude are digitized and submitted to intelligent min- ing system for planning in real time to generate dynamic and transparent four-dimensional geological model. Subse- quently,the dynamic real time four-dimensional geological model generated is used to acquire the top and bottom plate height data of each cutting position. This is combined with the shearer’s attitude parameters and the absolute position coordinates of the shearer,and the straightness requirements of the working face. The shearer height-adjustment strate- gy for the coal cutting cycle is planned in advance forming an intelligent coal cutting technology based on a dynamic and transparent working face. A “twelve-step” coal cutting process is proposed and the cable drag system of the shear- er established. Finally,using the technology of the dynamic four-dimensional geological model constructed,the authors have established a fully mechanized coal mining face for the intelligent coal cutting of the shearer, automatic face straightening,robot inspection,shearer cable dragging,hydraulic support automatic tracking and intelligent collabora- tive control. This includes the com-prehensive perception of the coal mining face,the remote centralized control of equipment,collaborative linkage,automatic control,multi-dimensional data fusion,the automatic identification of hid- den dangers,process data drive,and intelligent assisted decision-making. The result is the transformation of a visual re- mote intervention intelligent mining mode to a transparent intelligent adaptive intelligent mining mode. Practice shows that the construction of a dynamic four-dimensional geological model solves the identification of coal and rock bounda- ries in thin coal seam mining. The height adjustment strategy for the next 10 cycles of coal cutting can be provided with the position deviation between the preset coal cutting trajectory and the actual coal cutting trajectory trend curves being less than 0. 3 m. Application of this strategy at the 43101 working face of Yujialiang Coal Mine realized the daily 15 cuttings and annual output of 2. 216 million tons representing an increased production efficiency of 15. 08% without an operator at the working face and with only one person patrolling the operation.

     

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