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
Citation: 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

Transparent mining mode and key technologies of fully mechanized working face

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  • Received Date: November 18, 2021
  • Revised Date: March 09, 2022
  • Available Online: March 04, 2022
  • In order to solve the problem that the intelligent mining technology based on adaptive working face geological conditions can not meet the practical engineering application requirements, a transparent mining mode of fully mechanized working face is proposed, which includes three stages, namely model construction, positioning of space to be mined and cutting control decision and execution. The mode is based on the coal seam occurrence exploration, and the 3D digital model of working face is taken as the object. The height adjustment control strategy of the shearer is formulated by cutting the 3D digital model and extracting the track coordinates of the roof and floor of the coal seam to be mined. Finally, the shearer adjusts the height control according to the cutting track parameters to achieve the goal of autonomous coal cutting. This paper expounds the key technologies of transparent mining in fully mechanized working face, such as establishment of 3D digital model, establishment of 3D laser point cloud model, model cutting and cutting planning and shearer height adjustment control. In the 43102 fully mechanized working face of Yujialiang Coal Mine of CHN Energy Shendong Coal Group Co., Ltd., the transparent mining mode and key technologies engineering application are carried out. The initial 3D geological model of the working face is constructed, and the borehole survey is completed along the boundary line between the roof and floor of the coal seam so as to realize the detection of the occurrence of the coal seam in the working face. After the acquired data is imported into the initial 3D geological model, a 3D digital model of the working face is obtained. Geological mapping is carried out daily during the mining process of the working face, and the error correction of the 3D digital model is realized through the mapping data. The real-time 3D laser point cloud model of the stope is constructed, the 3D coordinate data set at the junction of coal wall and roof in the 3D laser point cloud model is extracted to form a cutting line. The cutting line is used to cut the 3D digital model to obtain the contour curve of roof and floor in the next coal cutting cycle. By analyzing the changes of coal seam occurrence, the cutting plan is formulated to guide the automatic height adjustment control of the drum in the subsequent coal cutting cycle of the shearer. The application results show that the error of the 3D digital model is less than ±0.2 m, and the shearer can automatically cut coal according to the coal seam occurrence conditions of the working face.
  • [1]
    黄曾华. 可视远程干预无人化开采技术研究[J]. 煤炭科学技术,2016,44(10):131-135.

    HUANG Zenghua. Study on unmanned mining technology with visualized remote interference[J]. Coal Science and Technology,2016,44(10):131-135.
    [2]
    田成金. 煤炭智能化开采模式和关键技术研究[J]. 工矿自动化,2016,42(11):28-32.

    TIAN Chengjin. Research of intelligentized coal mining mode and key technologies[J]. Industry and Mine Automation,2016,42(11):28-32.
    [3]
    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.

    LI Shoubin. Progress and development trend of intelligent mining technology[J]. Coal Science and Technology,2019,47(10):102-110.
    [4]
    范京道,徐建军,张玉良,等. 不同煤层地质条件下智能化无人综采技术[J]. 煤炭科学技术,2019,47(3):43-52.

    FAN Jingdao,XU Jianjun,ZHANG Yuliang,et al. Intelligent unmanned fully-mechanized mining technology under conditions of different seams geology[J]. Coal Science and Technology,2019,47(3):43-52.
    [5]
    王国法,刘峰,庞义辉,等. 煤矿智能化−煤炭工业高质量发展的核心技术支撑[J]. 煤炭学报,2019,44(2):349-357.

    WANG Guofa,LIU Feng,PANG Yihui,et al. Coal mine intellectualization:the core technology of high quality development[J]. Journal of China Coal Society,2019,44(2):349-357.
    [6]
    葛世荣,王忠宾,王世博. 互联网+采煤机智能化关键技术研究[J]. 煤炭科学技术,2016,44(7):1-9.

    GE Shirong,WANG Zhongbin,WANG Shibo. Study on key technology of Internet plus intelligent coal shearer[J]. Coal Science and Technology,2016,44(7):1-9.
    [7]
    袁亮,张平松. 煤炭精准开采地质保障技术的发展现状及展望[J]. 煤炭学报,2019,44(8):2277-2284.

    YUAN Liang,ZHANG Pingsong. Development status and prospect of geological guarantee technology for precise coal mining[J]. Journal of China Coal Society,2019,44(8):2277-2284.
    [8]
    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,2021,47(2):1-6.

    MAO Shanjun,LU Shouming,LI Cunlu,et al. Key technology 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,2021,47(2):1-6.
    [9]
    毛明仓,张孝斌,张玉良. 基于透明地质大数据智能精准开采技术研究[J]. 煤炭科学技术,2021,49(1):286-293.

    MAO Mingcang,ZHANG Xiaobin,ZHANG Yuliang. Research on intelligent and precision mining technology base on transparent geological big data[J]. Coal Science and Technology,2021,49(1):286-293.
    [10]
    王国法,赵国瑞,任怀伟. 智慧煤矿与智能化开采关键核心技术分析[J]. 煤炭学报,2019,44(1):34-41.

    WANG Guofa,ZHAO Guorui,REN Huaiwei. Analysis on key technologies of intelligent coal mine and intelligent mining[J]. Journal of China Coal Society,2019,44(1):34-41.
    [11]
    王国法,庞义辉,任怀伟,等. 煤炭安全高效综采理论、技术与装备的创新和实践[J]. 煤炭学报,2018,43(4):903-913.

    WANG Guofa,PANG Yihui,REN Huaiwei,et al. Coal safe and efficient mining theory,technology and equipment innovation practice[J]. Journal of China Coal Society,2018,43(4):903-913.
    [12]
    任怀伟,王国法,赵国瑞,等. 智慧煤矿信息逻辑模型及开采系统决策控制方法[J]. 煤炭学报,2019,44(9):2923-2935.

    REN Huaiwei,WANG Guofa,ZHAO Guorui,et al. Smart coal mine logic model and decision control method of mining system[J]. Journal of China Coal Society,2019,44(9):2923-2935.
    [13]
    袁亮. 面向煤炭精准开采的物联网架构及关键技术[J]. 工矿自动化,2017,43(10):1-7.

    YUAN Liang. The framework and key technologies of Internet of things for precise coal mining[J]. Industry and Mine Automation,2017,43(10):1-7.
    [14]
    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.
    [15]
    王存飞,荣耀. 透明工作面的概念、架构与关键技术[J]. 煤炭科学技术,2019,47(7):156-163.

    WANG Cunfei,RONG Yao. Concept,architecture and key technologies for transparent longwall face[J]. Coal Science and Technology,2019,47(7):156-163.
    [16]
    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(增刊1):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.
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