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A Review of Intelligent Unmanned Mining Current Situation and Development Trend

Author

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  • Kexue Zhang

    (Institute of Intelligent Unmanned Mining, North China Institute of Science and Technology, Beijing 101601, China
    Hebei Provincial Key Laboratory of Mine Intelligent Unmanned Mining Technology, North China Institute of Science and Technology, Beijing 101601, China
    State Key Laboratory for Geomechanics & Deep Underground Engineering, China University of Mining and Technology (Beijing), Beijing 100083, China
    China Coal Research Institute, Beijing 100013, China)

  • Lei Kang

    (Institute of Intelligent Unmanned Mining, North China Institute of Science and Technology, Beijing 101601, China
    Hebei Provincial Key Laboratory of Mine Intelligent Unmanned Mining Technology, North China Institute of Science and Technology, Beijing 101601, China
    These authors contributed equally to this work.)

  • Xuexi Chen

    (Institute of Intelligent Unmanned Mining, North China Institute of Science and Technology, Beijing 101601, China
    Hebei Provincial Key Laboratory of Mine Intelligent Unmanned Mining Technology, North China Institute of Science and Technology, Beijing 101601, China)

  • Manchao He

    (State Key Laboratory for Geomechanics & Deep Underground Engineering, China University of Mining and Technology (Beijing), Beijing 100083, China)

  • Chun Zhu

    (School of Earth Sciences and Engineering, Hohai University, Nanjing 210098, China)

  • Dong Li

    (Institute of Intelligent Unmanned Mining, North China Institute of Science and Technology, Beijing 101601, China
    Hebei Provincial Key Laboratory of Mine Intelligent Unmanned Mining Technology, North China Institute of Science and Technology, Beijing 101601, China)

Abstract

Intelligent unmanned mining is a key process in coal mine production, which has direct impact on the production safety, coal output, economic benefits and social benefits of coal mine enterprises. With the rapid development and popularization of 5G+ intelligent mines and coal mine intelligent equipment in China, the intelligentization of intelligent unmanned mining has become an important research topic. Especially with the promulgation of some Chinese policies and regulations, intelligent unmanned mining technology has become one of the key technologies of coal mine production. To understand the connotation, status quo and development trends of intelligent unmanned mining, this paper takes the relationship between key technologies and engineering application of intelligent unmanned mining in China as the perspective. It is proposed that the intelligent unmanned mining technology is in the whole process of working face mining. A research structure of unmanned follow-up operation and safe patrol is changing to the mode of intelligent adaptive mining, followed by the basic concepts and characteristics of intelligent unmanned mining. Relevant researches that maybe beneficial to the proposed research content are reviewed in four layers, which include basic theory, key technology, mining mode, and overall design system theory and technology. Finally, the current intelligent unmanned mining mode and future trends in this field in China are summarized.

Suggested Citation

  • Kexue Zhang & Lei Kang & Xuexi Chen & Manchao He & Chun Zhu & Dong Li, 2022. "A Review of Intelligent Unmanned Mining Current Situation and Development Trend," Energies, MDPI, vol. 15(2), pages 1-19, January.
    • Handle: RePEc:gam:jeners:v:15:y:2022:i:2:p:513-:d:722557
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    Citations

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    Cited by:

    1. Feng, Juqiang & Cai, Feng & Zhao, Yang & Zhang, Xing & Zhan, Xinju & Wang, Shunli, 2024. "A novel feature optimization and ensemble learning method for state-of-health prediction of mining lithium-ion batteries," Energy, Elsevier, vol. 299(C).
    2. Shuai Li & Lifeng Yu & Wanjun Jiang & Haoxuan Yu & Xinmin Wang, 2022. "The Recent Progress China Has Made in Green Mine Construction, Part I: Mining Groundwater Pollution and Sustainable Mining," IJERPH, MDPI, vol. 19(9), pages 1-19, May.
    3. Alexey Y. Bykovsky & Nikolay A. Vasiliev, 2023. "Parametrical T -Gate for Joint Processing of Quantum and Classic Optoelectronic Signals," J, MDPI, vol. 6(3), pages 1-27, July.
    4. Zhang, Yan & Wang, Yu-Hao & Zhao, Xu & Tong, Rui-Peng, 2023. "Dynamic probabilistic risk assessment of emergency response for intelligent coal mining face system, case study: Gas overrun scenario," Resources Policy, Elsevier, vol. 85(PB).
    5. Kexue Zhang & Junao Zhu & Manchao He & Yaodong Jiang & Chun Zhu & Dong Li & Lei Kang & Jiandong Sun & Zhiheng Chen & Xiaoling Wang & Haijiang Yang & Yongwei Wu & Xingcheng Yan, 2022. "Research on Intelligent Comprehensive Evaluation of Coal Seam Impact Risk Based on BP Neural Network Model," Energies, MDPI, vol. 15(9), pages 1-14, April.
    6. Xing, Zhizhong & Zhao, Shuanfeng & Guo, Wei & Meng, Fanyuan & Guo, Xiaojun & Wang, Shenquan & He, Haitao, 2023. "Coal resources under carbon peak: Segmentation of massive laser point clouds for coal mining in underground dusty environments using integrated graph deep learning model," Energy, Elsevier, vol. 285(C).
    7. Lin He & Dongliang Yuan & Lianwei Ren & Ming Huang & Wenyu Zhang & Jie Tan, 2023. "Evaluation Model Research of Coal Mine Intelligent Construction Based on FDEMATEL-ANP," Sustainability, MDPI, vol. 15(3), pages 1-21, January.
    8. Olga Zhironkina & Sergey Zhironkin, 2023. "Technological and Intellectual Transition to Mining 4.0: A Review," Energies, MDPI, vol. 16(3), pages 1-37, February.
    9. Fangtian Wang & Hongfei Qu & Wei Tian & Shilei Zhai & Liqiang Ma, 2022. "Ethical Construction and Development of Mining Engineering Based on the Safe, Efficient, Green, and Low-Carbon Concept," Sustainability, MDPI, vol. 14(21), pages 1-14, October.

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