新一代信息技术赋能煤矿装备数智化转型升级

金智新, 闫志蕊, 王宏伟, 李正龙, 史凌凯

金智新,闫志蕊,王宏伟,等. 新一代信息技术赋能煤矿装备数智化转型升级[J]. 工矿自动化,2023,49(6):19-31. DOI: 10.13272/j.issn.1671-251x.18123
引用本文: 金智新,闫志蕊,王宏伟,等. 新一代信息技术赋能煤矿装备数智化转型升级[J]. 工矿自动化,2023,49(6):19-31. DOI: 10.13272/j.issn.1671-251x.18123
JIN Zhixin, YAN Zhirui, WANG Hongwei, et al. The new generation of information technology empowers the digital and intelligent transformation and upgrading of coal mining equipment[J]. Journal of Mine Automation,2023,49(6):19-31. DOI: 10.13272/j.issn.1671-251x.18123
Citation: JIN Zhixin, YAN Zhirui, WANG Hongwei, et al. The new generation of information technology empowers the digital and intelligent transformation and upgrading of coal mining equipment[J]. Journal of Mine Automation,2023,49(6):19-31. DOI: 10.13272/j.issn.1671-251x.18123

新一代信息技术赋能煤矿装备数智化转型升级

基金项目: 中国工程院咨询研究项目(2022SX2,2021SX3);山西省科技计划揭榜招标资助项目(20201101005);山西省基础研究计划资助项目(202203021212275)。
详细信息
    作者简介:

    金智新(1959—),男,辽宁锦州人,教授级高级工程师,中国工程院院士,博士,主要研究方向为煤炭智能开采技术与煤矿安全工程管理,E-mail:jinzhixin@tyut.edu.cn

    通讯作者:

    闫志蕊(1993—),女,山西吕梁人,博士研究生,主要研究方向为煤矿机电智能化控制技术,E-mail:mjlayue29@163.com

  • 中图分类号: TD67

The new generation of information technology empowers the digital and intelligent transformation and upgrading of coal mining equipment

  • 摘要: 当前,煤矿智能化建设正处于初级向中高级智能化过渡探索期,现有智能装备自主创新能力尚需加强,核心技术“卡脖子”,井下复杂赋存条件下可靠性问题突出,如何利用新一代信息技术,纵深推动煤矿装备数智化转型升级,以数字化、智能化推动煤炭安全高效绿色开采具有重要意义。回顾了我国煤炭开采技术与装备智能化发展的演进过程,分析了煤炭开采各阶段的生产特征,认为煤矿智能化彻底改变了煤炭生产方式,生产要素以智能装备、智能化系统和复合型技术人才为主,从本质上提升了煤矿安全高效生产水平,助推煤矿实现减人增安提效。其中智能煤矿装备是煤矿智能化的核心要素,面对未来煤矿装备数智化转型发展的需求,探索了新一代信息技术与煤矿装备融合发展的路径,即以装备为智能化载体,通过新一代信息技术赋予装备智能感知与分析、智能判断与推理、智能决策与控制、智能诊断与学习的类人化智能化能力,并构建了物联网、5G、大数据、云计算、人工智能技术赋能煤矿装备智能感知、智能传输、智能分析、智能计算和智能决策的系统架构。深入分析了煤矿装备数智化发展过程中存在的理论、技术和人才难题,提出了煤矿装备数智化发展的建议:夯实基础是第一要务,须构建煤矿装备智能化顶层设计理论体系,加强关键核心技术攻关,加快新型基础设施建设,夯实煤矿智能化发展根基;煤矿装备智能化技术与煤矿特殊应用场景协同耦合发展,贴近煤矿井下现场需求,形成煤矿专用场景智能化技术,探索装备数智融合创新模式;智能技术与绿色开采技术相互融合促进,打造数字化、智能化、绿色化装备,开发煤炭智能高效低碳开采新模式,促进煤炭生产节能降耗;建立健全煤矿智能化人才培养体系,培养多学科交叉复合型人才,为煤矿智能化建设增强人才储备力量。
    Abstract: Currently, the intelligent construction of coal mines is in a transitional exploration period from primary to intermediate and advanced intelligence. The independent innovation capability of existing intelligent equipment still needs to be strengthened. The core technologies are bottleneck problems. The reliability problem under complex underground storage conditions is prominent. It is of great significance to use the new generation of information technology to promote the digital transformation and upgrading of coal mine equipment, and to promote safe, efficient, and green coal mining through digitization and intelligence. This paper reviews the evolution process of intelligent development of coal mining technology and equipment in China. This paper analyzes the production characteristics of each stage of coal mining. It is considered that the coal mine intelligence has completely changed the coal production mode. The production factors are mainly intelligent equipment, intelligent systems, and compound technical talents. They have essentially improved the level of safe and efficient production of coal mines, and helped the coal mines to reduce personnel, increase safety and improve efficiency. Among them, intelligent coal mine equipment is the core element of coal mine intelligence. Considering the demand for the digital and intelligent transformation and development of future coal mine equipment, we have explored the path of integrating the new generation of information technology and coal mine equipment. It uses equipment as an intelligent carrier. It endows the equipment with humanized intelligent capabilities such as intelligent perception and analysis, intelligent judgment and reasoning, intelligent decision-making and control, intelligent diagnosis and learning through the new generation of information technology. The system architecture of the Internet of things, 5G, big data, cloud computing, and artificial intelligence technology enabling intelligent perception, intelligent transmission, intelligent analysis, intelligent computing and intelligent decision-making of coal mine equipment has been constructed. The paper analyzes the theoretical, technical, and talent challenges in the development of digital intelligence in coal mining equipment. The paper proposes suggestions for the development of digital intelligence in coal mining equipment. Consolidating the foundation is the priority. It is necessary to build a top-level design theoretical system for intelligent coal mining equipment, strengthen key core technology research, accelerate the construction of new infrastructure, and consolidate the foundation of intelligent coal mining development. The intelligent technology for coal mining equipment and special application scenarios in coal mines develop in collaboration and coupling. It is suggested to meet the on-site needs of coal mines, form the intelligent technology for coal mine specific scenarios, and explore innovative models of equipment digital intelligence integration. The intelligent technology and green mining technology integrate and develop. It is suggested to create digital, intelligent, and green equipment. It is suggested to develop new models of intelligent, efficient, and low-carbon coal mining, and promote energy conservation and consumption reduction in coal production. It is suggested to establish a sound system for cultivating intelligent talents in coal mines, cultivate interdisciplinary and composite talents, and enhance talent reserves for the construction of intelligent coal mines.
  • 图  1   煤炭开采技术的演进及生产特征

    Figure  1.   Evolution and production characteristics of coal mining technology

    图  2   中国GDP与煤炭产量随煤矿智能化发展的变化

    Figure  2.   Relationship between China's GDP and coal production with the development of coal mine intelligence

    图  3   2002−2022年中国煤矿安全生产形势变化

    Figure  3.   Changes in China's coal mine safety production situation from 2002 to 2022

    图  4   煤矿智能装备系统类人化结构对照

    Figure  4.   Comparison of humanized structure of intelligent equipment system in coal mine

    图  5   煤矿装备物联网智能感知系统架构

    Figure  5.   Architecture of IoT intelligent perception system for coal mine equipment

    图  6   基于5G的掘进装备远程集控网络架构

    Figure  6.   Remote centralized control network architecture for tunneling equipment based on 5G

    图  7   煤矿装备大数据平台

    Figure  7.   Coal mine equipment big data platform

    图  8   煤矿装备大数据“云−边−端”协同应用架构

    Figure  8.   The "cloud-edge-terminal" collaborative application architecture of big data for coal mine equipment

    图  9   “煤矿机器人+人工智能”智能协同模式

    Figure  9.   Intelligent collaborative mode of "coal mine robot + artificial intelligence"

  • [1] 李首滨. 基于工业互联网的煤矿智能一体化管控平台[J]. 智能矿山,2022,3(4):2-11.

    LI Shoubin. Intelligent integrated control platform for coal mine based on industrial Internet[J]. Journal of Intelligent Mine,2022,3(4):2-11.

    [2] 王国法, 刘峰. 中国煤矿智能化发展报告(2022年)[M]. 北京: 应急管理出版社, 2022.

    WANG Guofa, LIU Feng. China coal mine intelligence development report (2022)[M]. Beijing: Emergency Management Press, 2022.

    [3] 黄曾华. 综采装备单机智能化向智能协同模式转型的探索研究[J]. 煤炭科学技术,2021,49(4):169-175. DOI: 10.13199/j.cnki.cst.2021.04.020

    HUANG Zenghua. Exploration and research on transformation from intelligent single machine equipment to intelligent synergy in coal mine[J]. Coal Science and Technology,2021,49(4):169-175. DOI: 10.13199/j.cnki.cst.2021.04.020

    [4] 金智新,王宏伟,付翔. HCPS理论体系下新一代智能煤矿发展路径[J]. 工矿自动化,2022,48(10):1-12.

    JIN Zhixin,WANG Hongwei,FU Xiang. Development path of new generation intelligent coal mine under HCPS theory system[J]. Journal of Mine Automation,2022,48(10):1-12.

    [5] 中国煤炭工业协会. 2022煤炭行业发展年度报告[R]. 北京: 中国煤炭工业协会, 2023.

    China National Coal Association. 2022 annual report on the development of the coal industry[R]. Beijing: China National Coal Association, 2023.

    [6] 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.

    [7] 张建锋, 肖利华, 许诗军. 数智化: 数字政府、数字经济与数字社会大融合[M]. 北京: 电子工业出版社, 2022.

    ZHANG Jianfeng, XIAO Lihua, XU Shijun. Digital intelligence: the integration of digital government, digital economy, and digital society[M]. Beijing: Publishing House of Electronics Industry, 2022.

    [8] 陈国青,任明,卫强,等. 数智赋能:信息系统研究的新跃迁[J]. 管理世界,2022,38(1):180-196. DOI: 10.3969/j.issn.1002-5502.2022.01.013

    CHEN Guoqing,REN Ming,WEI Qiang,et al. Data-intelligence empowerment:a new leap of information systems research[J]. Journal of Management World,2022,38(1):180-196. DOI: 10.3969/j.issn.1002-5502.2022.01.013

    [9] 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. DOI: 10.13225/j.cnki.jccs.2018.2041

    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. DOI: 10.13225/j.cnki.jccs.2018.2041

    [10] 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

    [11] 王国法,徐亚军,张金虎,等. 煤矿智能化开采新进展[J]. 煤炭科学技术,2021,49(1):1-10. DOI: 10.13199/j.cnki.cst.2021.01.001

    WANG Guofa,XU Yajun,ZHANG Jinhu,et al. New development of intelligent mining in coal mines[J]. Coal Science and Technology,2021,49(1):1-10. DOI: 10.13199/j.cnki.cst.2021.01.001

    [12] 金智新,曹孟涛,王宏伟. “中等收入”与新“双控”背景下煤炭行业转型发展新机遇[J]. 煤炭科学技术,2023,51(1):45-58.

    JIN Zhixin,CAO Mengtao,WANG Hongwei. New opportunities for coal industry transformation and development under the background of the level of a moderately developed country and a new "dual control" system[J]. Coal Science and Technology,2023,51(1):45-58.

    [13] 许日杰,杨科,吴劲松,等. 麻地梁煤矿智能化开采研究[J]. 工矿自动化,2021,47(11):9-15. DOI: 10.13272/j.issn.1671-251x.2021080034

    XU Rijie,YANG Ke,WU Jinsong,et al. Research on intelligent mining in Madiliang Coal Mine[J]. Industry and Mine Automation,2021,47(11):9-15. DOI: 10.13272/j.issn.1671-251x.2021080034

    [14] 崔亚仲,任艳艳,白明亮. 神东矿区煤炭智能化建设实践[J]. 煤炭科学技术,2022,50(增刊1):218-226.

    CUI Yazhong,REN Yanyan,BAI Mingliang. Practice of intelligent construction of Shendong Coal Mine[J]. Coal Science and Technology,2022,50(S1):218-226.

    [15] 丁恩杰,廖玉波,张雷,等. 煤矿信息化建设回顾与展望[J]. 工矿自动化,2020,46(7):5-11. DOI: 10.13272/j.issn.1671-251x.17624

    DING Enjie,LIAO Yubo,ZHANG Lei,et al. Review and prospect of coal mine informatization construction[J]. Industry and Mine Automation,2020,46(7):5-11. DOI: 10.13272/j.issn.1671-251x.17624

    [16] 袁亮,俞啸,丁恩杰,等. 矿山物联网人-机-环状态感知关键技术研究[J]. 通信学报,2020,41(2):1-12. DOI: 10.11959/j.issn.1000-436x.2020036

    YUAN Liang,YU Xiao,DING Enjie,et al. Research on key technologies of human-machine-environment states perception in mine Internet of things[J]. Journal on Communications,2020,41(2):1-12. DOI: 10.11959/j.issn.1000-436x.2020036

    [17] 丁恩杰,俞啸,廖玉波,等. 基于物联网的矿山机械设备状态智能感知与诊断[J]. 煤炭学报,2020,45(6):2308-2319. DOI: 10.13225/j.cnki.jccs.zn20.0340

    DING Enjie,YU Xiao,LIAO Yubo,et al. Key technology of mine equipment state perception and online diagnosis under Internet of Things[J]. Journal of China Coal Society,2020,45(6):2308-2319. DOI: 10.13225/j.cnki.jccs.zn20.0340

    [18] 孙继平. 煤矿智能化与矿用5G和网络硬切片技术[J]. 工矿自动化,2021,47(8):1-6. DOI: 10.13272/j.issn.1671-251x.17821

    SUN Jiping. Coal mine intelligence,mine 5G and network hard slicing technology[J]. Industry and Mine Automation,2021,47(8):1-6. DOI: 10.13272/j.issn.1671-251x.17821

    [19] 张立亚. 煤矿5G通信系统安全应用技术研究[J]. 工矿自动化,2021,47(12):8-12,45. DOI: 10.13272/j.issn.1671-251x.17854

    ZHANG Liya. Research on safety application technology of coal mine 5G communication system[J]. Industry and Mine Automation,2021,47(12):8-12,45. DOI: 10.13272/j.issn.1671-251x.17854

    [20] 王国法,张铁岗,王成山,等. 基于新一代信息技术的能源与矿业治理体系发展战略研究[J]. 中国工程科学,2022,24(1):176-189.

    WANG Guofa,ZHANG Tiegang,WANG Chengshan,et al. Development of energy and mining governance system based on new-generation information technology[J]. Strategic Study of CAE,2022,24(1):176-189.

    [21] 崔亚仲,白明亮,李波. 智能矿山大数据关键技术与发展研究[J]. 煤炭科学技术,2019,47(3):66-74.

    CUI Yazhong,BAI Mingliang,LI Bo. Key technology and development research on big data of intelligent mine[J]. Coal Science and Technology,2019,47(3):66-74.

    [22] 曹现刚,马宏伟,段雍,等. 煤矿设备智能维护与健康管理技术研究现状与展望[J]. 智能矿山,2020,1(1):105-111.

    CAO Xiangang,MA Hongwei,DUAN Yong,et al. Research status and prospects of intelligent maintenance and health management technology for coal mine equipment[J]. Journal of Intelligent Mine,2020,1(1):105-111.

    [23] 王国法,任怀伟,赵国瑞,等. 智能化煤矿数据模型及复杂巨系统耦合技术体系[J]. 煤炭学报,2022,47(1):61-74. DOI: 10.13225/j.cnki.jccs.YG21.1860

    WANG Guofa,REN Huaiwei,ZHAO Guorui,et al. Digital model and giant system coupling technology system of smart coal mine[J]. Journal of China Coal Society,2022,47(1):61-74. DOI: 10.13225/j.cnki.jccs.YG21.1860

    [24] 马小平,胡延军,缪燕子. 物联网、大数据及云计算技术在煤矿安全生产中的应用研究[J]. 工矿自动化,2014,40(4):5-9.

    MA Xiaoping,HU Yanjun,MIAO Yanzi. Application research of technologies of Internet of things,big data and cloud computing in coal mine safety production[J]. Industry and Mine Automation,2014,40(4):5-9.

    [25] 姜德义,魏立科,王翀,等. 智慧矿山边缘云协同计算技术架构与基础保障关键技术探讨[J]. 煤炭学报,2020,45(1):484-492. DOI: 10.13225/j.cnki.jccs.YG19.1371

    JIANG Deyi,WEI Like,WANG Chong,et al. Discussion on the technology architecture and key basic support technology for intelligent mine edge-cloud collaborative computing[J]. Journal of China Coal Society,2020,45(1):484-492. DOI: 10.13225/j.cnki.jccs.YG19.1371

    [26] 马小平,杨雪苗,胡延军,等. 人工智能技术在矿山智能化建设中的应用初探[J]. 工矿自动化,2020,46(5):8-14. DOI: 10.13272/j.issn.1671-251x.17593

    MA Xiaoping,YANG Xuemiao,HU Yanjun,et al. Preliminary study on application of artificial intelligence technology in mine intelligent construction[J]. Industry and Mine Automation,2020,46(5):8-14. DOI: 10.13272/j.issn.1671-251x.17593

    [27] 康迎春. 我国煤矿智能化建设存在的主要问题及对策分析[J]. 智能矿山,2022,3(5):11-17.

    KANG Yingchun. Analysis of the main problems and countermeasures in the intelligent construction of coal mines in China[J]. Journal of Intelligent Mine,2022,3(5):11-17.

图(9)
计量
  • 文章访问数:  1174
  • HTML全文浏览量:  75
  • PDF下载量:  123
  • 被引次数: 0
出版历程
  • 收稿日期:  2023-05-14
  • 修回日期:  2023-06-05
  • 网络出版日期:  2023-06-18
  • 刊出日期:  2023-06-24

目录

    /

    返回文章
    返回