GENG Yue, DUAN Yingjuan, REN Jiami. Research on roof stability assessment method of coal roadway[J]. Journal of Mine Automation, 2018, 44(6): 35-39. DOI: 10.13272/j.issn.1671-251x.2017110060
Citation: GENG Yue, DUAN Yingjuan, REN Jiami. Research on roof stability assessment method of coal roadway[J]. Journal of Mine Automation, 2018, 44(6): 35-39. DOI: 10.13272/j.issn.1671-251x.2017110060

Research on roof stability assessment method of coal roadway

More Information
  • Existing roof stability assessment methods of coal roadway were summarized and analyzed, which included single index method and compound index method in classic methods and supervised learning method and unsupervised learning method in machine learning methods. It was pointed out that the classic methods assessed roof by single index or for a certain type of coal rock so that assessment result is incomplete or unreliable, and the machine learning method needed a large number of hand-crafted labeling of roof monitoring data with large workload and poor actual application effect. A new roof stability assessment mode of coal roadway based on generative adversarial network in deep learning was proposed according to advantage of extracting features from roof monitoring data automatically of the deep learningmethod, so as to decrease labor workload.
  • Related Articles

    [1]LI Dianze, XU Huajie, ZHANG Bo. Rock fracture type recognition based on deep feature learning of microseismic signals[J]. Journal of Mine Automation, 2025, 51(3): 156-164. DOI: 10.13272/j.issn.1671-251x.2024080043
    [2]ZUO Mingming, ZHANG Xi, YANG Zihao, SUN Qifei, ZHANG Mengchao, ZHANG Yuan, LI Hu. Intelligent monitoring method for conveyor belt misalignment based on deep learning[J]. Journal of Mine Automation, 2024, 50(12): 166-172, 182. DOI: 10.13272/j.issn.1671-251x.2024030043
    [3]WANG Taiji. A method for estimating the step size of underground personnel based on generative adversarial networks[J]. Journal of Mine Automation, 2024, 50(6): 103-111. DOI: 10.13272/j.issn.1671-251x.2024020039
    [4]HAO Qinxia, LI Huimin. Recognition model of IIoT equipment in coal mine[J]. Journal of Mine Automation, 2024, 50(3): 99-107. DOI: 10.13272/j.issn.1671-251x.2023100092
    [5]CAO Zhengyuan, JIANG Wei, FANG Chenghui. Intelligent detection method for coal flow foreign objects based on dual attention generative adversarial network[J]. Journal of Mine Automation, 2023, 49(12): 56-62. DOI: 10.13272/j.issn.1671-251x.18094
    [6]ZHANG Liya. Foreign object detection method for belt conveyor based on generative adversarial nets[J]. Journal of Mine Automation, 2023, 49(11): 53-59. DOI: 10.13272/j.issn.1671-251x.2023080046
    [7]LI Jincai, FU Wenlong, WANG Renming, CHEN Xing, MENG Jiaxin. Intelligent fault diagnosis of rolling bearings based on deep network[J]. Journal of Mine Automation, 2022, 48(4): 78-88. DOI: 10.13272/j.issn.1671-251x.2022010008
    [8]ZHANG Lang, ZHANG Yinghui, ZHANG Yibin, LI Zuo. Research on fault diagnosis method of ventilation network based on machine learning[J]. Journal of Mine Automation, 2022, 48(3): 91-98. DOI: 10.13272/j.issn.1671-251x.2021120093
    [9]LI Changwen, CHENG Zeyin, ZHANG Xiaogang, DING Hua. Fault diagnosis of shearer rocker gear based on deep residual network[J]. Journal of Mine Automation, 2021, 47(3): 71-78. DOI: 10.13272/j.issn.1671-251x.2020110043
    [10]TANG Shiyu, ZHU Aichun, ZHANG Sai, CAO Qingfeng, CUI Ran, HUA Gang. Target detection of underground personnel based on deep convolutional neural network[J]. Journal of Mine Automation, 2018, 44(11): 32-36. DOI: 10.13272/j.issn.1671—251x.2018050068
  • Cited by

    Periodical cited type(11)

    1. 何勇华. 综放工作面液压支架直线度调整技术研究与实践. 煤矿机械. 2025(02): 153-157 .
    2. 姚钰鹏,商楚浩,刘清. 基于工艺引擎的规划放煤控制系统. 工矿自动化. 2024(09): 41-46+107 . 本站查看
    3. 王家臣,杨胜利,李良晖,张锦旺,魏炜杰. 智能放煤理论与技术研究进展. 工矿自动化. 2024(09): 1-12 . 本站查看
    4. 常树峰. 基于图像识别技术的综放工作面安全智能监控方法. 矿业装备. 2024(10): 7-9 .
    5. 邬喜仓,张学亮,阮进林,王志强. 保德煤矿智能综放工作面建设关键技术研究. 工矿自动化. 2023(02): 141-148 . 本站查看
    6. 那建勇. 综放工作面智能化放煤工艺研究. 矿业装备. 2023(03): 34-36 .
    7. 张光磊,汪海涛,张磊. 基于虚拟现实技术的综放工作面仿真研究. 自动化技术与应用. 2023(06): 62-65+86 .
    8. 吕延森,张学亮,阮进林,高鹏. 保德煤矿智能综放开采关键技术及展望. 煤炭科学技术. 2022(S1): 233-243 .
    9. 王中举,李宣睿,王金峰. 选煤厂煤矸分选工艺优化设计. 工矿自动化. 2022(S2): 144-146 . 本站查看
    10. 李俊士,郭资鉴. 智能放煤控制系统测试平台设计. 煤炭科学技术. 2021(S1): 124-130 .
    11. 崔青. 煤矿井下打钻视频监控系统的设计与实现. 电脑知识与技术. 2021(28): 59-60 .

    Other cited types(2)

Catalog

    Article Metrics

    Article views (101) PDF downloads (12) Cited by(13)
    Related

    /

    DownLoad:  Full-Size Img  PowerPoint
    Return
    Return