Citation: | XIE Panshi,YANG Hang,WU Yongping,et al. Investigation into the monitoring and control of mechanical dynamics in inclined mining equipment utilizing digital twin technology[J]. Coal Science and Technology,2024,52(12):259−271. DOI: 10.12438/cst.2024-0011 |
Intelligent mining represents a critical path for the safe and efficient extraction of challenging coal resources, particularly those with steep and extreme inclinations, in China. Large-scale physical simulations leveraging digital twin technology are pivotal in addressing the intricate mechanical behaviors of coal and rock, as well as the intelligent control challenges posed by gravity and inclination effects. This study comprehensively delineates the design framework, structural features, and testing/detection methodologies of a large-scale coal mining face physical simulation system empowered by digital twin technology. This system facilitates data visualization, robust human-machine interaction, and process self-optimization during mining operations. Addressing the challenges traditional hydraulic supports encounter in areas such as real-time monitoring, predictive maintenance, design optimization, and physical modeling, a posture perception and simulation system was developed. This system, grounded in hydraulic support and digital twin technology, employs software like SolidWorks, Maya, and Unity3D to create digital twin models of hydraulic supports. Through the integration of various posture perception sensors, it gathers posture and load data from the physical hydraulic supports. This setup enables precise posture alignment and immediate feedback between the digital twins and their physical counterparts. The system's mapping between virtual and real domains is achieved through detailed analysis and processing of the gathered data. Ultimately, the feasibility and efficacy of this system are corroborated through a multi-functional, variable-angle large-scale "support-surrounding rock" system physical simulation platform. This platform conducts reliability and stability tests under various inclination conditions, validating the system's operational capabilities.
[1] |
谢和平,王金华,王国法,等. 煤炭革命新理念与煤炭科技发展构想[J]. 煤炭学报,2018,43(5):1187−1197.
XIE Heping,WANG Jinhua,WANG Guofa,et al. New ideas of coal revolution and layout of coal science and technology development[J]. Journal of China Coal Society,2018,43(5):1187−1197.
|
[2] |
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. doi: 10.3969/j.issn.0253-2336.2022.1.mtkxjs202201001
WANG Guofa. New technological progress of coal mine intelligence and its problems[J]. Coal Science and Technology,2022,50(1):1−27. doi: 10.3969/j.issn.0253-2336.2022.1.mtkxjs202201001
|
[3] |
伍永平,贠东风,解盘石,等. 大倾角煤层长壁综采:进展、实践、科学问题[J]. 煤炭学报,2020,45(1):24−34.
WU Yongping,YUN Dongfeng,XIE Panshi,et al. Progress,practice and scientific issues in steeply dipping coal seams fully-mechanized mining[J]. Journal of China Coal Society,2020,45(1):24−34.
|
[4] |
GRIEVES M. Intelligent digital twins and the development and management of complex systems[J]. Digital Twin,2022,2:8. doi: 10.12688/digitaltwin.17574.1
|
[5] |
ZHANG M,TAO F,HUANG B Q,et al. Digital twin data:methods and key technologies[J]. Digital Twin,2022,1:2. doi: 10.12688/digitaltwin.17467.2
|
[6] |
MERKLE L,SEGURA A S,TORBEN GRUMMEL J,et al. Architecture of a digital twin for enabling digital services for battery systems[C]//2019 IEEE International Conference on Industrial Cyber Physical Systems (ICPS). Taipei,China. IEEE,2019:155-160.
|
[7] |
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.
|
[8] |
王忠鑫,辛凤阳,宋波,等. 论露天煤矿智能化建设总体设计[J]. 煤炭科学技术,2022,50(2):37−46.
WANG Zhongxin,XIN Fengyang,SONG Bo,et al. Overall design of intelligent construction in open pit coal mines[J]. Coal Science and Technology,2022,50(2):37−46.
|
[9] |
张帆,葛世荣,李闯. 智慧矿山数字孪生技术研究综述[J]. 煤炭科学技术,2020,48(7):168−176.
ZHANG Fan,GE Shirong,LI Chuang. Research summary on digital twin technology for smart mines[J]. Coal Science and Technology,2020,48(7):168−176.
|
[10] |
Soni R,Bhatia M,Singh T. Digital twin:intersection of mind and machine[J]. International Journal of Computational Intelligence and IoT,2019,2(3):667−670
|
[11] |
DAVID J,LOBOV A,LANZ M. Attaining learning objectives by ontological reasoning using digital twins[J]. Procedia Manufacturing,2019,31:349−355. doi: 10.1016/j.promfg.2019.03.055
|
[12] |
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.
|
[13] |
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.
|
[14] |
张帆,李闯,李昊,等. 面向智能矿山与新工科的数字孪生技术研究[J]. 工矿自动化,2020,46(5):15−20.
ZHANG Fan,LI Chuang,LI Hao,et al. Research on digital twin technology for smart mine and new engineering discipline[J]. Industry and Mine Automation,2020,46(5):15−20.
|
[15] |
王学文,刘曙光,王雪松,等. AR/VR融合驱动的综采工作面智能监控关键技术研究与试验[J]. 煤炭学报,2022,47(2):969−985.
WANG Xuewen,LIU Shuguang,WANG Xuesong,et al. Research and test on key technologies of intelligent monitoring and control driven by AR/VR for fully mechanized coal-mining face[J]. Journal of China Coal Society,2022,47(2):969−985.
|
[16] |
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.
|
[17] |
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.
|
[18] |
阮锴燚,寇子明,王彦栋,等. 矿井提升系统数字孪生快速建模方法研究[J]. 煤炭科学技术,2023,51(9):219−230. doi: 10.12438/cst.2022-1321
RUAN Kaiyi,KOU Ziming,WANG Yandong,et al. Digital twin rapid construction method of a mining hoisting system[J]. Coal Science and Technology,2023,51(9):219−230. doi: 10.12438/cst.2022-1321
|
[19] |
路正雄,郭卫,张帆,等. 基于数据驱动的综采装备协同控制系统架构及关键技术[J]. 煤炭科学技术,2020,48(7):195−205.
LU Zhengxiong,GUO Wei,ZHANG Fan,et al. Collaborative control system architecture and key technologies of fully-mechanized mining equipment based on data drive[J]. Coal Science and Technology,2020,48(7):195−205.
|
[20] |
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. doi: 10.3969/j.issn.1004-132X.2020.07.007
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. doi: 10.3969/j.issn.1004-132X.2020.07.007
|
[21] |
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.
|
[22] |
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.
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.
|
[23] |
李娟莉,沈宏达,谢嘉成,等. 基于数字孪生的综采工作面工业虚拟服务系统[J]. 计算机集成制造系统,2021,27(2):445−455.
LI Juanli,SHEN Hongda,XIE Jiacheng,et al. Development of industrial virtual service system for fully mechanized mining face based on digital twin[J]. Computer Integrated Manufacturing Systems,2021,27(2):445−455.
|
[24] |
李娟莉,姜朔,谢嘉成,等. 基于采煤机截割路径的动态三维地质模型构建方法[J]. 东北大学学报(自然科学版),2021,42(5):706−712.
LI Juanli,JIANG Shuo,XIE Jiacheng,et al. Construction method of the dynamic 3-D geological model based on shearer cutting path[J]. Journal of Northeastern University (Natural Science),2021,42(5):706−712.
|
[25] |
TAO F,ZHANG H,LIU A,et al. Digital twin in industry:state-of-the-art[J]. IEEE Transactions on Industrial Informatics,2018,15(4):2405−2415.
|
[26] |
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.
|
[27] |
杨林瑶,陈思远,王晓,等. 数字孪生与平行系统:发展现状、对比及展望[J]. 自动化学报,2019,45(11):2001−2031.
YANG Linyao,CHEN Siyuan,WANG Xiao,et al. Digital twins and parallel systems:state of the art,comparisons and prospect[J]. Acta Automatica Sinica,2019,45(11):2001−2031.
|
[28] |
刘大同,郭凯,王本宽,等. 数字孪生技术综述与展望[J]. 仪器仪表学报,2018,39(11):1−10.
LIU Datong,GUO Kai,WANG Benkuan,et al. Summary and perspective survey on digital twin technology[J]. Chinese Journal of Scientific Instrument,2018,39(11):1−10.
|
[29] |
伍永平,闫壮壮,罗生虎,等. 煤岩组合体应力传递与强度特征倾角效应[J]. 煤炭科学技术,2023,51(1):105−116.
WU Yongping,YAN Zhuangzhuang,LUO Shenghu,et al. Dip effect of stress transfer and structural instability mechanism of coal-rock combination[J]. Coal Science and Technology,2023,51(1):105−116.
|
[30] |
伍永平,汤业鹏,解盘石,等. 含煤线夹矸岩体力学特性及变形破坏特征的数值实验[J]. 采矿与安全工程学报,2022,39(6):1198−1209.
WU Yongping,TANG Yepeng,XIE Panshi,et al. Numerical experimental study on mechanical properties and deformation and failure characteristics of the dirt band rock mass[J]. Journal of Mining & Safety Engineering,2022,39(6):1198−1209.
|
[31] |
伍永平,解盘石,贠东风,等. 大倾角层状采动煤岩体重力–倾角效应与岩层控制[J]. 煤炭学报,2023,48(1):100−113.
WU Yongping,XIE Panshi,YUN Dongfeng,et al. Gravity-dip effect and strata control in mining of the steeply dipping coal seam[J]. Journal of China Coal Society,2023,48(1):100−113.
|