面向智能矿山的数字孪生技术研究进展

邢震

doi:10.13272/j.issn.1671-251x.2024010079

面向智能矿山的数字孪生技术研究进展

doi: 10.13272/j.issn.1671-251x.2024010079

邢震^{1, 2, 3,}

1.
中煤科工集团常州研究院有限公司，江苏常州　213015
2.
煤炭智能开采与岩层控制全国重点实验室，江苏常州　213015
3.
天地（常州）自动化股份有限公司，江苏常州　213015

基金项目: 天地科技股份有限公司科技创新创业资金专项项目（2021-TD-ZD004）。

详细信息

作者简介:
邢震（1987—），男，山东临沂人，副研究员，硕士，研究方向为智能矿山整体解决方案、生产协同管控及煤矿安全信息化，E-mail：694826672@qq.com

中图分类号: TD67
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出版历程
- 收稿日期: 2024-01-23
- 修回日期: 2024-03-11
- 网络出版日期: 2024-04-11

Research progress on digital twin technology for intelligent mines

XING Zhen^{1, 2, 3
,}

1.
CCTEG Changzhou Research Institute, Changzhou 213015, China
2.
State Key Laboratory of Intelligent Coal Mining and Strata Control, Changzhou 213015, China
3.
Tiandi (Changzhou) Automation Co., Ltd., Changzhou 213015, China

摘要

摘要: 智能矿山领域数字孪生技术的应用需面对较多复杂性、特殊性的技术突破。阐述了数字孪生在智能矿山领域的适用性，归纳梳理了数字孪生技术在煤矿安全、生产及运营管理等方面的研究及应用现状：在煤矿安全管理方面，数字孪生技术主要应用于灾害预警、风险管控、灾害救援等；在煤矿生产方面，数字孪生技术主要应用于采掘工作面区域整体、单机机械装备状态监测及控制、机械装备预测性维护。从物理实体、虚拟实体、连接交互、数字孪生数据及功能服务5个维度入手探讨了智能矿山领域数字孪生亟待解决的关键共性问题：物理实体维度需重点突破全面感知及控制装备的研发，虚拟实体维度需深入进行物理、行为、规则模型的研究，连接交互维度需攻关煤矿井下5G网络传输关键技术，数字孪生数据维度需解决高性能计算等问题，功能服务维度需研发仿真软件及人工智能算法，以便更好地适应现场环境。从矿井规划设计、开发、建设阶段的灾害预防性设计、生产系统设计、地质环境预测，矿井生产运营阶段的灾害预警及防控、生产调度决策优化、生产设备全生命周期管理等方面展望了数字孪生技术在智能矿山领域的发展趋势，认为宜针对关键部件或装备，核心环节，重要或危险场所、区域等进行精细化孪生。
- 数字孪生 /
- 智能矿山 /
- 灾害预测及防控 /
- 生产调度优化
Abstract: The application of digital twin technology in the field of intelligent mining needs to face many complex and special technological breakthroughs. This article elaborates on the applicability of digital twins in the field of intelligent mining, and summarizes the research and application status of digital twin technology in coal mine safety, production, and operation management. In terms of coal mine safety management, digital twin technology is mainly applied in disaster warning, risk control, disaster rescue, etc. In terms of coal mine production, digital twin technology is mainly applied in the overall mining working face area, monitoring and control of single machine mechanical equipment status, and predictive maintenance of mechanical equipment. Starting from five dimensions: physical entity, virtual entity, connection interaction, digital twin data, and functional services, this paper explores the key common problems that urgently need to be solved in the field of intelligent mining. The physical entity dimension needs to focus on breaking through the research and development of comprehensive perception and control equipment. The virtual entity dimension needs to conduct in-depth research on physical, behavioral, and rule models. The connection interaction dimension needs to tackle key technologies for underground 5G network transmission in coal mines. The twin data dimension needs to solve problems such as high-performance computing. The functional service dimension needs to develop simulation software and artificial intelligence algorithms to better adapt to the on-site environment. This article looks forward to the development trend of digital twin technology in the field of intelligent mining from the aspects of disaster prevention design, production system design, geological environment prediction in the planning, development, and construction stages of mines, disaster warning and prevention, optimization of production scheduling decisions, and full life cycle management of production equipment in the production and operation stage of mines. It is believed that fine twinning should be carried out for key components or equipment, core links, important or dangerous places, areas, etc.
- digital twin /
- intelligent mining /
- disaster warning and prevention /
- production scheduling optimization

HTML全文

图 1 数字孪生五维模型

Figure 1. The digital twin five-dimensional model

下载: 全尺寸图片幻灯片

图 2 数字孪生5个维度的研究现状

Figure 2. Research status of five dimensions of digital twin technology

下载: 全尺寸图片幻灯片

图 3 智能矿山领域数字孪生技术发展成熟度

Figure 3. Development maturity of digital twin technology in the field of intelligent mining

下载: 全尺寸图片幻灯片

图 4 针对数字孪生场景的网络切片技术

Figure 4. Digital twin data transmission based on 5G network slicing in coal mines

下载: 全尺寸图片幻灯片

参考文献(86)

[1]	王国法,刘峰,孟祥军,等. 煤矿智能化(初级阶段)研究与实践[J]. 煤炭科学技术,2019,47(8):1-36. WANG Guofa,LIU Feng,MENG Xiangjun,et al. Research and practice on intelligent coal mine construction(primary stage)[J]. Coal Science and Technology,2019,47(8):1-36.
[2]	王国法,任怀伟,赵国瑞,等. 煤矿智能化十大“痛点”解析及对策[J]. 工矿自动化,2021,47(6):1-11. WANG Guofa,REN Huaiwei,ZHAO Guorui,et al. Analysis and countermeasures of ten 'pain points' of intelligent coal mine[J]. Industry and Mine Automation,2021,47(6):1-11.
[3]	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. 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.
[4]	王国法,杜毅博,陈晓晶,等. 从煤矿机械化到自动化和智能化的发展与创新实践——纪念《工矿自动化》创刊50周年[J]. 工矿自动化,2023,49(6):1-18. WANG Guofa,DU Yibo,CHEN Xiaojing,et al. Development and innovative practice from coal mine mechanization to automation and intelligence:commemorating the 50th anniversary of the founding of Journal of Mine Automation[J]. Journal of Mine Automation,2023,49(6):1-18.
[5]	王国法. 煤矿智能化最新技术进展与问题探讨[J]. 煤炭科学技术,2022,50(1):1-27. WANG Guofa. New technological progress of coal mine intelligence and its problems[J]. Coal Science and Technology,2022,50(1):1-27.
[6]	高汶栋. 计算机集成制造系统[J]. 电世界,1995,36(9):6-7. GAO Wendong. Computer integrated manufacturing system[J]. Electrical World,1995,36(9):6-7.
[7]	邢震. 综放工作面采空区自燃危险区域监测技术及应用研究[J]. 煤炭工程,2017,49(11):130-132,137. XING Zhen. Research on monitoring technology for danger zone of spontaneous combustion in goaf of fully-mechanized top-coal caving face[J]. Coal Engineering,2017,49(11):130-132,137.
[8]	邢震. 高瓦斯矿井采空区瓦斯与煤自燃耦合规律研究[J]. 工矿自动化,2020,46(3):6-11,20. XING Zhen. Research on coupling law of gas and coal spontaneous combustion in goaf of high gas mine[J]. Industry and Mine Automation,2020,46(3):6-11,20.
[9]	周福宝,时国庆,王雁鸣,等. 矿井密闭全生命周期安全风险监测预警[J]. 工矿自动化,2023,49(6):48-56. ZHOU Fubao,SHI Guoqing,WANG Yanming,et al. Safety risks monitoring and warning throughout the full lifecycle of mine air stopping[J]. Journal of Mine Automation,2023,49(6):48-56.
[10]	张勇,宿国瑞,王鹏,等. 基于煤矿事故全过程的智慧应急云平台架构及关键技术研究[J]. 中国煤炭,2022,48(10):58-63. ZHANG Yong,SU Guorui,WANG Peng,et al. Research on the architecture and key technologies of intelligent emergency cloud platform based on the whole process of coal mine accident[J]. China Coal,2022,48(10):58-63.
[11]	田广宇,林泽东. 煤矿工作面超前预警模型与系统实现[J]. 软件导刊,2021,20(7):116-123. TIAN Guangyu,LIN Zedong. Advance warning model and system realization of coal mining face[J]. Software Guide,2021,20(7):116-123.
[12]	朱斌,张奎,张有为,等. 综掘面风流智能调控数字孪生系统[J]. 计算机集成制造系统,2023,29(6):2006-2018. ZHU Bin,ZHANG Kui,ZHANG Youwei,et al. Digital twin system for airflow intelligent control of fully-mechanized caving face[J]. Computer Integrated Manufacturing Systems,2023,29(6):2006-2018.
[13]	张有为. 综掘面风流调控数字孪生系统研究[D]. 西安:长安大学,2022. ZHANG Youwei. Study on digital twin system controlled by wind flow in fully mechanized excavation face[D]. Xi'an:Chang'an University,2022.
[14]	韩龙,王顺葵,陈广炎,等. 基于VR和数字孪生的煤矿井下巷道巡检机器人设计[J]. 科学技术创新,2023(19):217-220. HAN Long,WANG Shunkui,CHEN Guangyan,et al. VR and digital twin-based design of an underground coal mine tunnel inspection robot[J]. Scientific and Technological Innovation,2023(19):217-220.
[15]	李新,李飞,方世巍,等. 基于UE4的井下变电所巡检机器人数字孪生系统[J]. 煤矿安全,2021,52(11):130-133. LI Xin,LI Fei,FANG Shiwei,et al. Digital twin system of inspection robot in underground substation based on UE4[J]. Safety in Coal Mines,2021,52(11):130-133.
[16]	刘怡梦. 基于Kinect手势交互的综采工作面虚拟巡检系统设计与实现[D]. 太原:太原理工大学,2022. LIU Yimeng. Design and implementation of virtual inspection system for fully mechanized caving face based on Kinect gesture interaction[D]. Taiyuan:Taiyuan University of Technology,2022.
[17]	WANG Hongwei,WANG Zeliang,JIANG Yaodong,et al. New approach for the digital reconstruction of complex mine faults and its application in mining[J]. International Journal of Coal Science & Technology,2022,9(1). DOI: 10.1007/s40789-022-00506-z.
[18]	WANG Zhiquan. Prediction method of coal and gas outburst intensity based on digital twin and deep learning[J]. Frontiers in Energy Research,2022,10. DOI: 10.3389/FENRG.2022.891184.
[19]	王国法,庞义辉,李爽,等. 基于煤矿时空多源信息感知的智能安控闭环体系[J]. 矿业安全与环保,2022,49(4):1-11. WANG Guofa,PANG Yihui,LI Shuang,et al. Intelligent safety closed-loop management and control system based on multi-source information perception in coal mine[J]. Mining Safety & Environmental Protection,2022,49(4):1-11.
[20]	李爽,贺超,鹿乘,等. 煤矿智能双重预防机制与智能安全管控平台研究[J]. 煤炭科学技术,2023,51(1):464-473. LI Shuang,HE Chao,LU Cheng,et al. Research on intelligent dual prevention mechanism and intelligent security control platform of coal mine[J]. Coal Science and Technology,2023,51(1):464-473.
[21]	王佳奇,卢明银. 基于数字孪生的煤矿瓦斯事故安全管理[J]. 煤矿安全,2020,51(8):251-255. WANG Jiaqi,LU Mingyin. Mine gas accident safety management based on digital twin[J]. Safety in Coal Mines,2020,51(8):251-255.
[22]	李治理,邱向雷,刘海瑞,等. 煤矿防突信息管理数字孪生平台功能及应用[J]. 陕西煤炭,2023,42(4):177-181. LI Zhili,QIU Xianglei,LIU Hairui,et al. Function and application of information management digital twin platform for coal mine outburst prevention[J]. Shaanxi Coal,2023,42(4):177-181.
[23]	郭向阳,于亮亮,吴卫兵,等. 基于数字孪生的智慧煤矿安全管控平台研究[J]. 能源技术与管理,2022,47(4):134-136. GUO Xiangyang,YU Liangliang,WU Weibing,et al. Research on smart coal mine safety control platform based on digital twins[J]. Energy Technology and Management,2022,47(4):134-136.
[24]	郭泱泱. 元宇宙技术在煤矿安全培训和应急演练中的可行性研究[J]. 煤田地质与勘探,2022,50(1):144-148. GUO Yangyang. Feasibility study of the Metaverse technology in coal mine emergency training and drills[J]. Coal Geology & Exploration,2022,50(1):144-148.
[25]	葛世荣,王世博,管增伦,等. 数字孪生-应对智能化综采工作面技术挑战[J]. 工矿自动化,2022,48(7):1-12. GE Shirong,WANG Shibo,GUAN Zenglun,et al. Digital twin:meeting the technical challenges of intelligent fully mechanized working face[J]. Journal of Mine Automation,2022,48(7):1-12.
[26]	刘清,张龙,李天越,等. 综采工作面三机数字孪生及协同建模方法[J]. 工矿自动化,2023,49(2):47-55. LIU Qing,ZHANG Long,LI Tianyue,et al. A three machine digital twin and collaborative modeling method for fully mechanized working face[J]. Journal of Mine Automation,2023,49(2):47-55.
[27]	苗丙,葛世荣,郭一楠,等. 煤矿数字孪生智采工作面系统构建[J]. 矿业科学学报,2022,7(2):143-153. MIAO Bing,GE Shirong,GUO Yinan,et al. Construction of digital twin system for intelligent mining in coal mines[J]. Journal of Mining Science and Technology,2022,7(2):143-153.
[28]	葛世荣,张帆,王世博,等. 数字孪生智采工作面技术架构研究[J]. 煤炭学报,2020,45(6):1925-1936. GE Shirong,ZHNAG Fan,WANG Shibo,et al. Digital twin for smart coal mining workface:technological frame and construction[J]. Journal of China Coal Society,2020,45(6):1925-1936.
[29]	姜朔. 复杂煤层条件下综采工作面VR仿真系统及关键技术研究[D]. 太原:太原理工大学,2021. JIANG Shuo. Research on VR simulation system and key technology of fully mechanized coal-mining face under complex coal seam conditions[D]. Taiyuan:Taiyuan University of Technology,2021.
[30]	崔涛. 基于真实开采数据的采运装备虚拟规划方法研究[D]. 太原:太原理工大学,2022. CUI Tao. Research on virtual planning method of mining and transportation equipment based on real mining data[D]. Taiyuan:Taiyuan University of Technology,2022.
[31]	张帆,葛世荣. 矿山数字孪生构建方法与演化机理[J]. 煤炭学报,2023,48(1):510-522. ZHANG Fan,GE Shirong. Construction method and evolution mechanism of mine digital twins[J]. Journal of China Coal Society,2023,48(1):510-522.
[32]	蔡峰. 蒙陕地区中厚煤层智能化综采工作面关键技术应用研究[J]. 中国煤炭,2022,48(5):41-46. CAI Feng. Application study on the key technology for intelligent fully mechanized mining face in medium-thick coal seam in Inner Mongolia-Shaanxi region[J]. China Coal,2022,48(5):41-46.
[33]	雷晓荣,李明星,岳辉,等. 透明工作面数字孪生系统关键技术及实现[J]. 智能矿山,2022,3(7):50-56. LEI Xiaorong,LI Mingxing,YUE Hui,et al. Key technologies and implementation of digital twin system for transparent workface[J]. Journal of Intelligent Mine,2022,3(7):50-56.
[34]	迟焕磊,袁智,曹琰,等. 基于数字孪生的智能化工作面三维监测技术研究[J]. 煤炭科学技术,2021,49(10):153-161. CHI Huanlei,YUAN Zhi,CAO Yan,et al. Study on digital twin-based smart fully-mechanized coal mining workface monitoring technology[J]. Coal Science and Technology,2021,49(10):153-161.
[35]	符大利. 基于数字孪生驱动的综采工作面远程监控系统[J]. 煤炭技术,2022,41(4):175-178. FU Dali. Remote monitoring system of fully mechanized mining face based on digital twin drive[J]. Coal Technology,2022,41(4):175-178.
[36]	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,2022,47(1):515-526. MAO Shanjun,LU Shouming,LI Cunlu,et al. Key technologies and system of adaptive coal cutting in transparent intelligent fully mechanized coal mining face based on precisegeodetic coordinates[J]. Journal of China Coal Society,2022,47(1):515-526.
[37]	马宏伟,王世斌,毛清华,等. 煤矿巷道智能掘进关键共性技术[J]. 煤炭学报,2021,46(1):310-320. MA Hongwei,WANG Shibin,MAO Qinghua,et al. Key common technology of intelligent heading in coal mine roadway[J]. Journal of China Coal Society,2021,46(1):310-320.
[38]	吴淼,李瑞,王鹏江,等. 基于数字孪生的综掘巷道并行工艺技术初步研究[J]. 煤炭学报,2020,45(增刊1):506-513. WU Miao,LI Rui,WANG Pengjiang,et al. Preliminary study on the parallel technology of fully mechanized roadway based on digital twin[J]. Journal of China Coal Society,2020,45(S1):506-513.
[39]	王岩,张旭辉,曹现刚,等. 掘进工作面数字孪生体构建与平行智能控制方法[J]. 煤炭学报,2022,47(增刊1):384-394. WANG Yan,ZHANG Xuhui,CAO Xiangang,et al. Construction of digital twin and parallel intelligent control method for excavation face[J]. Journal of China Coal Society,2022,47(S1):384-394.
[40]	杨耀智. 煤矿远程智能掘进面临的挑战及发展趋势[J]. 内蒙古煤炭经济,2022(11):148-150. YANG Yaozhi. Challenges and development trends of remote intelligent mining in coal mines[J]. Inner Mongolia Coal Economy,2022(11):148-150.
[41]	王虹,王步康,张小峰,等. 煤矿智能快掘关键技术与工程实践[J]. 煤炭学报,2021,46(7):2068-2083. WANG Hong,WANG Bukang,ZHANG Xiaofeng,et al. Key technology and engineering practice of intelligent rapid heading in coal mine[J]. Journal of China Coal Society,2021,46(7):2068-2083.
[42]	徐伟锋,金向阳,张丽平. 煤矿掘进机器人视觉位姿感知与控制关键技术[J]. 煤矿机械,2022,43(5):181-184. XU Weifeng,JIN Xiangyang,ZHANG Liping. Key technology of vision pose perception and control of coal mine tunneling robot[J]. Coal Mine Machinery,2022,43(5):181-184.
[43]	张元鹏,路志国. 煤矿掘进远程智能控制系统的设计与发展[J]. 内蒙古煤炭经济,2023(3):157-159. ZHANG Yuanpeng,LU Zhiguo. Design and development of remote intelligent control system for coal mine excavation[J]. Inner Mongolia Coal Economy,2023(3):157-159.
[44]	雷孟宇,张旭辉,杨文娟,等. 煤矿掘进装备视觉位姿检测与控制研究现状与趋势[J]. 煤炭学报,2021,46(增刊2):1135-1148. LEI Mengyu,ZHANG Xuhui,YANG Wenjuan,et al. Current status and trend of research on visual pose detection and control of heading equipment in coal mines[J]. Journal of China Coal Society,2021,46(S2):1135-1148.
[45]	张旭辉,吕欣媛,王甜,等. 数字孪生驱动的掘进机器人决策控制系统研究[J]. 煤炭科学技术,2022,50(7):36-49. ZHANG Xuhui,LYU Xinyuan,WANG Tian,et al. Research on decision control system of tunneling robot driven by digital twin[J]. Coal Science and Technology,2022,50(7):36-49.
[46]	张旭辉,张超,王妙云,等. 数字孪生驱动的悬臂式掘进机虚拟操控技术[J]. 计算机集成制造系统,2021,27(6):1617-1628. ZHANG Xuhui,ZHANG Chao,WANG Miaoyun,et al. Digital twin-driven virtual control technology of cantilever roadheader[J]. Computer Integrated Manufacturing Systems,2021,27(6):1617-1628.
[47]	杨健健,张强,吴淼,等. 巷道智能化掘进的自主感知及调控技术研究进展[J]. 煤炭学报,2020,45(6):2045-2055. YANG Jianjian,ZHANG Qiang,WU Miao,et al. Research progress of autonomous perception and control technology for intelligent heading[J]. Journal of China Coal Society,2020,45(6):2045-2055.
[48]	任文涛,朱礼建,梁志斌,等. 唐口煤业10304综掘工作面数字孪生系统设计[J]. 采矿技术,2023,23(1):199-201. REN Wentao,ZHU Lijian,LIANG Zhibin,et al. Design of digital twin system for 10304 fully mechanized excavation face in Tangkou Coal Mine[J]. Mining Technology,2023,23(1):199-201.
[49]	COETZEE B J,SONNENDECKER P W. Fully automated coal quality control using digital twin material tracking and statistical model predictive control for yield optimization during production of semi soft coking-and station coal[J]. Journal of the Southern African Institute of Mining and Metallurgy,2022,122(8):429-435.
[50]	王开松,徐记顺,靳华伟,等. 基于UWB技术的矿井辅助运输装备监测[J]. 绥化学院学报,2022,42(3):147-151. WANG Kaisong,XU Jishun,JIN Huawei,et al. Monitoring of mine auxiliary transportation equipment based on UWB technology[J]. Journal of Suihua University,2022,42(3):147-151.
[51]	王伟. 基于数字孪生的掘进机截割状态监测技术研究[J]. 内蒙古煤炭经济,2021(9):50-51. WANG Wei. Research on the monitoring technology of cutting condition of tunneling machine based on digital twin[J]. Inner Mongolia Coal Economy,2021(9):50-51.
[52]	薛旭升,任众孚,毛清华,等. 基于数字孪生的煤矿掘进机器人纠偏控制研究[J]. 工矿自动化,2022,48(1):26-32. XUE Xusheng,REN Zhongfu,MAO Qinghua,et al. Research on deviation correction control of coal mine roadheader based on digital twin[J]. Industry and Mine Automation,2022,48(1):26-32.
[53]	胡志强,李季涛,王洪鑫. 基于数字孪生的煤矿企业调车作业监控系统[J]. 铁路计算机应用,2023,32(2):68-72. HU Zhiqiang,LI Jitao,WANG Hongxin. Monitoring system of shunting operation in coal mine enterprise based on digital twins[J]. Railway Computer Application,2023,32(2):68-72.
[54]	赵墨波. 数字孪生驱动的协作机器人状态监测方法研究[J]. 煤矿机械,2023,44(8):210-212. ZHAO Mobo. Research on state monitoring method of cooperative robot driven by digital twin[J]. Coal Mine Machinery,2023,44(8):210-212.
[55]	李晓雪,韩赛伟. 基于数字孪生的采煤机预测性维护研究[J]. 煤矿机械,2022,43(1):173-176. LI Xiaoxue,HAN Saiwei. Research on predictive maintenance of shearer based on digital twin[J]. Coal Mine Machinery,2022,43(1):173-176.
[56]	张旭辉,鞠佳杉,杨文娟,等. 基于数字孪生的复杂矿用设备预测性维护系统[J]. 工程设计学报,2022,29(5):643-650,664. ZHANG Xuhui,JU Jiashan,YANG Wenjuan,et al. Predictive maintenance system for complex mining equipment based on digital twin[J]. Chinese Journal of Engineering Design,2022,29(5):643-650,664.
[57]	经海翔,黄友锐,徐善永,等. 基于数字孪生和概率神经网络的矿用通风机预测性故障诊断研究[J]. 工矿自动化,2021,47(11):53-60. JING Haixiang,HUANG Yourui,XU Shanyong,et al. Research on the predictive fault diagnosis of mine ventilator based on digital twin and probabilistic neural network[J]. Industry and Mine Automation,2021,47(11):53-60.
[58]	鲁泽明,王秀莉. 基于数字孪生技术的矿用设备预测性维护方案研究[J]. 数字通信世界,2022(12):21-23. LU Zeming,WANG Xiuli. Research on predictive maintenance scheme of mining equipment based on digital twin technology[J]. Digital Communication World,2022(12):21-23.
[59]	刘送永,刘强,崔玉明,等. 煤矿悬臂式掘进机多信息监测系统设计与研究[J]. 煤炭学报,2023,48(6):2564-2578. LIU Songyong,LIU Qiang,CUI Yuming,et al. Design and research on multi-information monitoring system for roadheader[J]. Journal of China Coal Society,2023,48(6):2564-2578.
[60]	张旭辉,张雨萌,王岩,等. 融合数字孪生与混合现实技术的机电设备辅助维修方法[J]. 计算机集成制造系统,2021,27(8):2187-2195. ZHANG Xuhui,ZHANG Yumeng,WANG Yan,et al. Auxiliary maintenance method for electromechanical equipment integrating digital twin and mixed reality technology[J]. Computer Integrated Manufacturing Systems,2021,27(8):2187-2195.
[61]	张雨萌. 数字孪生驱动的矿用设备维修MR辅助指导系统[D]. 西安:西安科技大学,2020. ZHANG Yumeng. DT-driven aided guidance system of mine equipment maintenance using MR[D]. Xi'an:Xi'an University of Science and Technology,2020.
[62]	丁华,杨亮亮,杨兆建,等. 数字孪生与深度学习融合驱动的采煤机健康状态预测[J]. 中国机械工程,2020,31(7):815-823. DING Hua,YANG Liangliang,YANG Zhaojian,et al. Health prediction of shearers driven by digital twin and deep learning[J]. China Mechanical Engineering,2020,31(7):815-823.
[63]	HUANG Yourui,YUAN Biao,XU Shanyong,et al. Fault diagnosis of permanent magnet synchronous motor of coal mine belt conveyor based on digital twin and ISSA-RF[J]. Processes,2022,10(9). DOI: 10.3390/pr10091679.
[64]	ISLAVATH S R,DEB D,KUMAR H. Life cycle analysis and damage prediction of a longwall powered support using 3D numerical modelling techniques[J]. Arabian Journal of Geosciences,2019,12(14). DOI: 10.1007/s12517-019-4574-y.
[65]	SEMENOV Y,SEMENOVA O,KUVATAEV I. Solutions for digitalization of the coal industry implemented in UC Kuzbassrazrezugol[J]. E3S Web of Conferences,2020,174. DOI: 10.1051/e3sconf/202017401042.
[66]	马文昕. BIM+GIS数字孪生技术在煤矿全景数字化智能综合管控中的应用[J]. 中国高新科技,2022(16):39-41. MA Wenxin. Application of BIM+GIS digital twin technology in panoramic digital intelligent comprehensive management and control of coal mine[J]. China High and New Technology,2022(16):39-41.
[67]	CHEN Long,HU Xiaoming,WANG Ge,et al. Parallel mining operating systems:from digital twins to mining intelligence[C]. IEEE 1st International Conference on Digital Twins and Parallel Intelligence,Beijing,2021:469-473.
[68]	肖粲俊,刘红梅,石发强,等. 基于数字孪生的煤矿智能管控平台架构研究与实现[J]. 矿业安全与环保,2023,50(5):43-49. XIAO Canjun,LIU Hongmei,SHI Faqiang,et al. Research and implementation of intelligent control platform architecture for coal mine based on digital twin[J]. Mining Safety & Environmental Protection,2023,50(5):43-49.
[69]	宋立. 三维可视化生产管控平台在集团型矿山企业的实现及应用[J]. 中国金属通报,2022(3):234-236. SONG Li. Implementation and application of 3D visualized production control platform in group mining enterprises[J]. China Metal Bulletin,2022(3):234-236.
[70]	赵建文,孟旭辉. 数字孪生在煤矿电网中的应用研究[J]. 工矿自动化,2023,49(2):38-46. ZHAO Jianwen,MENG Xuhui. Research on the application of digital twin in coal mine power grid[J]. Journal of Mine Automation,2023,49(2):38-46.
[71]	赵银燕,杨凯. 柿竹园多金属矿三维可视化综合管控系统设计与实现[J]. 采矿技术,2022,22(6):4-9. ZHAO Yinyan,YANG Kai. Design and implementation of 3D visualized comprehensive control system for Shizhuyuan Polymetallic Mine[J]. Mining Technology,2022,22(6):4-9.
[72]	陶飞,刘蔚然,张萌,等. 数字孪生五维模型及十大领域应用[J]. 计算机集成制造系统,2019,25(1):1-18. TAO Fei,LIU Weiran,ZHANG Meng,et al. Five-dimension digital twin model and its ten applications[J]. Computer Integrated Manufacturing Systems,2019,25(1):1-18.
[73]	陶飞,张辰源,戚庆林,等. 数字孪生成熟度模型[J]. 计算机集成制造系统,2022,28(5):1267-1281. TAO Fei,ZHANG Chenyuan,QI Qinglin,et al. Digital twin maturity model[J]. Computer Integrated Manufacturing Systems,2022,28(5):1267-1281.
[74]	孟峰,张磊,赵子未,等. 基于物联网的智能传感器技术及其应用[J]. 工矿自动化,2021,47(增刊1):48-50. MENG Feng,ZHANG Lei,ZHAO Ziwei,et al. Application of intelligent sensor technology based on Internet of things[J]. Industry and Mine Automation,2021,47(S1):48-50.
[75]	陶飞,马昕,戚庆林,等. 数字孪生连接交互理论与关键技术[J]. 计算机集成制造系统,2023,29(1):1-10. TAO Fei,MA Xin,QI Qinglin,et al. Theory and key technologies of digital twin connection and interaction[J]. Computer Integrated Manufacturing Systems,2023,29(1):1-10.
[76]	包建军. 智能矿山高精度位置服务系统研究现状与展望[J]. 智能矿山,2021,2(3):46-52. BAO Jianjun. Research status and prospect of high precision location service system for intelligent mines[J]. Journal of Intelligent Mine,2021,2(3):46-52.
[77]	陶飞,张贺,戚庆林,等. 数字孪生模型构建理论及应用[J]. 计算机集成制造系统,2021,27(1):1-15. TAO Fei,ZHANG He,QI Qinglin,et al. Theory of digital twin modeling and its application[J]. Computer Integrated Manufacturing Systems,2021,27(1):1-15.
[78]	谢嘉成,王学文,杨兆建. 基于数字孪生的综采工作面生产系统设计与运行模式[J]. 计算机集成制造系统,2019,25(6):1381-1391. XIE Jiacheng,WANG Xuewen,YANG Zhaojian. Design and operation mode of production system of fully mechanized coal mining face based on digital twin theory[J]. Computer Integrated Manufacturing Systems,2019,25(6):1381-1391.
[79]	李鹏,程建远. 采掘工作面地质信息数字孪生技术[J]. 煤田地质与勘探,2022,50(11):174-186. LI Peng,CHENG Jianyuan. Digital twin technology of geological information in mining and excavation working face[J]. Coal Geology & Exploration,2022,50(11):174-186.
[80]	李伟,叶鸥,刘辉,等. 基于数字孪生技术的大型煤矿远程智能监控研究[J]. 计算机测量与控制,2023,31(11):204-211. LI Wei,YE Ou,LIU Hui,et al. Research on remote intelligent monitoring of large coal mines based on digital twin technology[J]. Computer Measurement & Control,2023,31(11):204-211.
[81]	邢震,韩安,陈晓晶,等. 基于工业互联网的智能矿山灾害数字孪生研究[J]. 工矿自动化,2023,49(2):23-30,55. XING Zhen,HAN An,CHEN Xiaojing,et al. Research on intelligent mine disaster digital twin based on industrial Internet[J]. Journal of Mine Automation,2023,49(2):23-30,55.
[82]	邢震. 浅埋厚煤层地表漏风对采空区煤自燃影响数值模拟研究[J]. 工矿自动化,2021,47(2):80-87,103. XING Zhen. Numerical simulation study on the influence of surface air leakage in shallow thick coal seam on coal spontaneous combustion in goaf[J]. Industry and Mine Automation,2021,47(2):80-87,103.
[83]	邢震. 特厚煤层自燃关键参数现场观测及动态数值模拟研究[J]. 煤炭工程,2020,52(2):111-115. XING Zhen. In-situ observation and dynamic numerical simulation research on the key parameters of extra-thick coal seam spontaneous combustion[J]. Coal Engineering,2020,52(2):111-115.
[84]	邢震. 数字孪生驱动的煤矿多元业务全局动态协同管控[J]. 工矿自动化,2023,49(7):60-66,82. XING Zhen. Global dynamic collaborative management and control of diversified business in coal mines driven by digital twins[J]. Journal of Mine Automation,2023,49(7):60-66,82.
[85]	郭一楠,杨帆,葛世荣,等. 知识驱动的智采数字孪生主动管控模式[J]. 煤炭学报,2023,48(增刊1):334-344. GUO Yinan,YANG Fan,GE Shirong,et al. Novel knowledge-driven active management and control scheme of smart coal mining face with digital twin[J]. Journal of China Coal Society,2023,48(S1):334-344.
[86]	尤秀松,葛世荣,郭一楠,等. 智采工作面三机数字孪生驱动控制架构 [J/OL]. 煤炭学报:1-11[2024-01-11]. http://kns.cnki.net/kcms/detail/11.2190.TD.20230926.1756.004.html. YOU Xiusong,GE Shirong,GUO Yinan,et al. Digital twin-driven control construction for three machines of smart coal mining face[J/OL]. Journal of China Coal Society:1-11[2024-01-11].http://kns.cnki.net/kcms/detail/11.2190.TD.20230926.1756.004.html.