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LI Sen,LI Zhongzhong,LIU Qing. Planned cutting and collaborative control system for fully-mechanized mining face based on transparent geology[J]. Coal Science and Technology,2023,51(4):175−184

. DOI: 10.13199/j.cnki.cst.2022-0514
Citation:

LI Sen,LI Zhongzhong,LIU Qing. Planned cutting and collaborative control system for fully-mechanized mining face based on transparent geology[J]. Coal Science and Technology,2023,51(4):175−184

. DOI: 10.13199/j.cnki.cst.2022-0514

Planned cutting and collaborative control system for fully-mechanized mining face based on transparent geology

Funds: 

National Natural Science Foundation of China (51974290); Major Science and Technology Innovation Project of Shandong Province (2020CXGC011501)

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  • Received Date: April 12, 2022
  • Available Online: May 14, 2023
  • With the gradual widespread application of intelligent coal mine, the geological transparency technology has become one of the important technical supports for intelligent mining. Aiming at how to use transparent geological technology achievements to control, equipment an intelligent collaborative mining planning system based on transparent geology was developed. The system is centered on intelligent planning center and mining control center. The intelligent planning center generates cutting templates and control strategies based on geological models. The mining control center collaborates with fully mechanized mining equipment to implement control strategies according to cutting templates. The system consists of two key technologies, namely cutting template planning technology and equipment collaborative control technology. Cutting template planning technology include drum height planning and cutting process planning. Drum height planning uses a forecasting method based on time series trends and machine learning.Cutting process planning defines the characteristics of individual process segments and form a process section planning table. Equipment collaborative control technology include collaborative control of shearer and support and coal flow load collaborative control. Collaborative control of shearer and support proposed a planning strategy, including process adaptation before cutting and real-time adjustment during cutting, so as to ensure the support can complete the automatic follow-up operation. Coal flow load collaborative control proposes a method based on linear programming to adjust the speed of shearers to achieve the balance of coal flow load. The field application and experiments shows that the shearer automatically implements the cutting process according to the plan. The maximum number of manual intervention is only 25 times per cut and the number of manual intervention is significantly reduced by 64.28%—68.75%. The current curve of the conveyor is stable and there is no no-load or stop phenomenon. It has certain reference significance for the further improvement of intelligent mining.

  • [1]
    王国法. 煤矿智能化最新技术进展与问题探讨[J]. 煤炭科学技术,2022,50(1):1−27.

    WANG Guofa. New technological progress of coal mine intelligence and its problems[J]. Coal Science and Technology,2022,50(1):1−27.
    [2]
    谷保泽,邱少杰. 透明化矿山建设关键技术探讨[J]. 工矿自动化,2021,47(S1):24−25.

    GU Baoze,QIU Shaojie. Discussion on key technologies for transparent mine constructio[J]. Industry and Mine Automation,2021,47(S1):24−25.
    [3]
    袁 亮. 煤炭精准开采科学构想[J]. 煤炭学报,2017,42(1):1−7. doi: 10.13225/j.cnki.jccs.2016.1661

    YUAN Liang. Scientific conception of precision coal mining[J]. Journal of China Coal Society,2017,42(1):1−7. doi: 10.13225/j.cnki.jccs.2016.1661
    [4]
    袁 亮,张平松. 煤炭精准开采透明地质条件的重构与思考[J]. 煤炭学报,2020,45(7):2346−2356.

    YUAN Liang,ZHANG Pingsong. Framework and thinking of transparent geological conditions for precise mining of coal[J]. Journal of China Coal Society,2020,45(7):2346−2356.
    [5]
    王国法,任怀伟,赵国瑞,等. 煤矿智能化十大“痛点”解析及对策[J]. 工矿自动化,2021,47(6):1−11.

    WANG Guofa,REN Huaiwei,ZHAO Guorui,et al. Analysis and countermeasures of ten 'pain points' of intelligent coal mine[J]. Industry and Mine Automation,2021,47(6):1−11.
    [6]
    李首滨. 智能化开采研究进展与发展趋势[J]. 煤炭科学技术,2019,47(10):102−110. doi: 10.13199/j.cnki.cst.2019.10.012

    LI Shoubin. Progress and development trend of intelligent mining technology[J]. Coal Science and Technology,2019,47(10):102−110. doi: 10.13199/j.cnki.cst.2019.10.012
    [7]
    王国法,富佳兴,孟令宇. 煤矿智能化创新团队建设与关键技术研发进展[J]. 工矿自动化,2022,48(12):1−15.

    WANG Guofa,FU Jiaxing,MENG Lingyu. Development of innovation team construction and key technology research in coal mine intelligence[J]. Journal of Mine Automation,2022,48(12):1−15.
    [8]
    程建远,朱梦博,王云宏,等. 煤炭智能精准开采工作面地质模型梯级构建及其关键技术[J]. 煤炭学报,2019,44(8):2285−2295.

    CHENG Jianyuan,ZHU Mengbo,WANG Yunhong,et al. Cascade construction of geological model of longwall panel for intelligent precision coal mining and its key technology[J]. Journal of China Coal Society,2019,44(8):2285−2295.
    [9]
    薛国华. 基于透明地质的综采工作面三维煤层建模[J]. 工矿自动化,2022,48(4):135−141.

    XUE Guohua. Three-dimensional coal seam modeling of fully mechanized working face based on transparent geology[J]. Journal of Mine Automation,2022,48(4):135−141.
    [10]
    卢新明,阚淑婷. 煤炭精准开采地质保障与透明地质云计算技术[J]. 煤炭学报,2019,44(8):2296−2305.

    LU Xinming,KAN Shuting. Geological guarantee and transparent geological cloud computing technology of precisioncoal mining[J]. Journal of China Coal Society,2019,44(8):2296−2305.
    [11]
    葛世荣,郝雪弟,田 凯,等. 采煤机自主导航截割原理及关键技术[J]. 煤炭学报,2021,46(3):774−788. doi: 10.13225/j.cnki.jccs.yt21.0114

    GE Shirong,HAO Xuedi,TIAN Kai,et al. Principle and key technology of autonomous navigation cutting for deep coal seam[J]. Journal of China Coal Society,2021,46(3):774−788. doi: 10.13225/j.cnki.jccs.yt21.0114
    [12]
    孙振明, 毛善君, 祁和刚, 等. 煤矿三维地质模型动态修正关键技术[J]. 煤炭学报, 2014, 39(5): 918−924.

    SUN Zhenming, MAO Shanjun, QI Hegang, et al. Key technologies for dynamic correction of coal mine 3D geological model[J], Journal of China Coal Society, 2014, 39(5): 918−924.
    [13]
    殷大发. 煤矿三维地质模型精度评价及动态更新技术探讨[J]. 煤矿开采,2018,23(4):20−24.

    YIN Dafa. Discussion on the accuracy evaluation and dynamic update technology of coal mine 3D geological model[J]. Coal Mining,2018,23(4):20−24.
    [14]
    刘万里, 张学亮, 王世博. 采煤工作面煤层三维模型构建及动态修正技术[ J]. 煤炭学报, 2020, 45(6): 1973−1983.

    LIU Wanli, ZHANG Xueliang, WANG Shibo. Modeling and dynamic correction technology of 3D coal seam model for coal-mining face[J]. Journal of China Coal Society, 2020, 45(6): 1973−1983.
    [15]
    王 昕,张学亮,刘 清. 智能开采工作面建设解决方案及对策建议[J]. 中国煤炭,2021,47(9):77−84. doi: 10.3969/j.issn.1006-530X.2021.09.011

    WANG Xin,ZHANG Xueliang,LIU Qing. Solutions and countermeasures for the construction of intelligent mining face[J]. China Coal,2021,47(9):77−84. doi: 10.3969/j.issn.1006-530X.2021.09.011
    [16]
    马 骋,宋 焘. 智能精准开采大数据分析决策系统关键技术[J]. 陕西煤炭,2021,40(5):57−61,84. doi: 10.3969/j.issn.1671-749X.2021.05.014

    MA Cheng,SONG Tao. Key technologies of intelligent precision mining big data analysis and decision system[J]. Shanxi Coal,2021,40(5):57−61,84. doi: 10.3969/j.issn.1671-749X.2021.05.014
    [17]
    贺海涛. 综采工作面智能化开采系统关键技术[J]. 煤炭科学技术,2021,49(S1):8−15.

    HE Haitao. Key technology of intelligent mining system in fully-mechanized mining face[J]. Coal Science and Technology,2021,49(S1):8−15.
    [18]
    毛善君,鲁守明,李存禄,等. 基于精确大地坐标的煤矿透明化智能综采工作面自适应割煤关键技术研究及系统应用[J]. 煤炭学报,2022,47(1):155−526.

    MAO Shanjun,LU Shouming,LI Cunlu,et al. Key technologies and system of adaptive coal cutting in transparent intelligent fully mechanized coal mining face based on precise geodetic coordinates[J]. Journal of China Coal Society,2022,47(1):155−526.
    [19]
    王 峰. 基于透明工作面的智能化开采概念、实现路径及关键技术[J]. 工矿自动化,2020,46(5):39−42.

    WANG Feng. Concept, realization path and key technologies of intelligent mining based on transparent longwall face[J]. Industry and Mine Automation,2020,46(5):39−42.
    [20]
    原长锁,王 峰. 综采工作面透明化开采模式及关键技术[J]. 工矿自动化,2022,48(3):11−15,31. doi: 10.13272/j.issn.1671-251x.2021110048

    YUAN Changsuo,WANG Feng. Transparent mining mode and key technologies of fully mechanized working face[J]. Journal of Mine Automation,2022,48(3):11−15,31. doi: 10.13272/j.issn.1671-251x.2021110048
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