Research on key technologies of intelligent working face in coal

被引:0
|
作者
Peng C. [1 ,2 ]
Shiyang P. [1 ]
Tao Y. [1 ]
Xuexi C. [1 ]
Pengfei W. [1 ]
机构
[1] School of Safety Engineering, North China Institute of Science and Technology, Langfang
[2] State Key Laboratory Cultivation Base for Gas Geology and Gas Control, Henan Polytechnic University, Jiaozuo, Henan
关键词
Fully mechanised mining; Intelligent mining; Intelligent working face; Large mining height; Unmanned coalface;
D O I
10.1504/IJWMC.2021.117565
中图分类号
学科分类号
摘要
Mining of fully mechanised intelligent working face with large mining height (MFMIWF-LMH) is a technology which allows the mining of 3.5-8.8 m thick coal seams at one time using a whole set of fully mechanised mining intelligent equipment. The MFMIWF-LMH is characterised by complex production process, numerous types of equipment and severe mine pressure. In terms of mine pressure appearance, MFMIWF-LMH is likely to undergo a significant increase in the failure strength of surrounding rock, an obvious rise of the abutment pressure and peak value, and rib spalling and roof fall of coal wall. The study analyses the problems existing in MFMIWF-LMH and puts forward targeted solutions. In addition, it is proposed in the study that the system of MFMIWF-LMH is a complex systematic engineering whose key control technologies include general control network technology, coupling control technology of surrounding rock support, high-definition visualisation technology, rapid support-moving control technology, and equipment 3D virtual reality technology in the working face. The field engineering practice is a beneficial exploration for MFMIWF-LMH. Copyright © 2021 Inderscience Enterprises Ltd.
引用
收藏
页码:363 / 371
页数:8
相关论文
共 50 条
  • [21] Key technologies of data monitoring for coal machinery equipment in the intelligent IOT environment
    Li, Juanli
    Li, Menghui
    Yan, Fangyuan
    Miao, Dong
    2020 10TH INSTITUTE OF ELECTRICAL AND ELECTRONICS ENGINEERS INTERNATIONAL CONFERENCE ON CYBER TECHNOLOGY IN AUTOMATION, CONTROL, AND INTELLIGENT SYSTEMS (IEEE-CYBER 2020), 2020, : 368 - 373
  • [22] Key technologies and practices for safe, efficient, and intelligent mining of deep coal resources
    Li W.
    Sun X.
    Meitan Kexue Jishu/Coal Science and Technology (Peking), 2024, 52 (01): : 52 - 64
  • [23] Research on interpolation error analysis of geological modeling of intelligent working face
    An L.
    Han B.
    Li P.
    Dai Z.
    Wang X.
    Meitiandizhi Yu Kantan/Coal Geology and Exploration, 2022, 50 (06): : 184 - 189
  • [24] Numerical research on goaf coal pillar damaged by working face mining
    Guo, Xinyao
    Song, Yinghua
    Lv, Wei
    Guo, Hui
    Yang, Ang
    Metallurgical and Mining Industry, 2015, 7 (07): : 358 - 364
  • [25] Research on Key Technologies of intelligent adaptive infrared thermal imaging electronics
    Xu, Honglie
    Yang, Chunhua
    Wu, Jianjun
    Fan, Xiaoqing
    INTERNATIONAL CONFERENCE ON OPTICAL AND PHOTONIC ENGINEERING, ICOPEN 2022, 2022, 12550
  • [26] Research on Key Technologies of Intelligent Integrated System for Architectural Design Enterprises
    Fang, Changjian
    Lai, Yifeng
    Wen, Zhongjun
    6TH INTERNATIONAL CONFERENCE ON ENVIRONMENTAL SCIENCE AND CIVIL ENGINEERING, 2020, 455
  • [27] Research on Key Technologies of Intelligent Agriculture based on Agricultural Big Data
    Hao, Fengqi
    Luo, Xuan
    Mu, Chunhua
    2016 INTERNATIONAL CONFERENCE ON SMART CITY AND SYSTEMS ENGINEERING (ICSCSE), 2016, : 598 - 601
  • [28] Research on injection mould intelligent cost estimation system and key technologies
    Wang, H
    Zhou, XH
    Ruan, XY
    INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY, 2003, 21 (03): : 215 - 222
  • [29] Research on Injection Mould Intelligent Cost Estimation System and Key Technologies
    H. Wang
    X.-Y. Ruan
    X.H. Zhou
    The International Journal of Advanced Manufacturing Technology, 2003, 21 (3) : 215 - 222
  • [30] Research on injection mould intelligent cost estimation system and key technologies
    Wang, H. (wanghui1977@yahoo.com), 1600, Springer-Verlag London Ltd (21):