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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
Citation: 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

Digital twin rapid construction method of a mining hoisting system

Funds: 

National Natural Science Foundation of China(52274156,52174147); Shanxi Province Applied Basic Research Program Funding Project (201901D211009)

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  • Received Date: August 14, 2022
  • Available Online: August 01, 2023
  • The safe and reliable operation of the hoisting system is very important for the production of the whole mine. Therefore, it is necessary to realize the single-point global visualization and virtual remote cooperative linkage control of the mining hoisting system, so as to solve the problem that the traditional multi-point video surveillance can only cover some key components and obtain incomplete information. To solving the problem, the digital twin framework of a mining hoisting system that with the function of monitoring, control and servicing is constructed by industrial sensing, artificial intelligence, rapid modeling, cloud storage and other technologies. Based on the framework, a multi-dimensional and multi-scale digital twin rapid modeling method is proposed. Firstly, a large scale geometric model of the mining hoisting system is built by 3D laser scanning technology, filtering, Poisson 3D reconstruction and other point cloud processing algorithms. Secondly, using industrial sensor network, PLC data reading and conversion technology, the behavior model of mining hoisting system under massive data is established. Lastly the fault knowledge model of the mining hoisting system is constructed using the database technology, domain expert knowledge and cases. The multi-dimensional and multi-scale digital twin rapid modeling experiment is carried out in a mine, and the results are as follows. The efficiency of the geometric modeling method has improved 93% compared with the traditional CAD modeling method and the modeling result has great similar to the real mining hoisting system. The behavior modeling method realizes the mapping of real entity behavior without adding new sensors and without shutting down, saves a lot of cost and has strong real-time performance. The driving Scripts are written based on Unity3D software to deeply integrate behavioral model, knowledge model and geometric model. Synchronization and deduction of behavioral model are carried out based on the component level model with high fidelity of the geometric model and it can realize the non-delay cooperative linkage between virtual and real systems. Meanwhile, relevant professional knowledge in the field is triggered by real-time behavioral data to assist decision making. The establishment process of the whole digital twin model takes into account the cost and effect, which will greatly improve the operation security and intelligence degree of the mining hoisting system.

  • [1]
    李腾宇,寇子明,吴 娟,等. 超千米深井提升机可视化监测系统应用[J]. 煤炭学报,2020,45(S2):1069−1078. doi: 10.13225/j.cnki.jccs.zn20.0324

    LI Tengyu,KOU Ziming,WU Juan,et al. Monitoring system of the hoist in the over kilometer deep shaft[J]. Journal of China Coal Society,2020,45(S2):1069−1078. doi: 10.13225/j.cnki.jccs.zn20.0324
    [2]
    何满潮. 深井提升动力学研究[J]. 力学进展, 2021, 51(3): 702−728.

    HE Manchao. Research on deep shaft hoisting dynamics [J] Advances in Mechanics, 2021, 51(3): 702−728
    [3]
    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.
    [4]
    发展改革委, 能源局, 应急管理部, 等. 关于加快煤矿智能化发展的指导意见[EB/OL]. http://www.gov.cn/zhengce/zhengceku/2020-03/05/content_54 87081.htm, 2020-02-25

    Development and Reform Co- mmission, Energy Bureau, emergency department, et al. Guiding opinionson acce- lerating intelligent development of coal mine[EB/OL]. [2020-02-25] http://www.gov.cn/zhengce/Zhengce-ku/2020-03/05/content_5487081.htm.
    [5]
    BEATE B,VERA H. Digital twin as enabler for an innovative digital shopfloor management system in the ESB logistics learning factory at Reutlingen-University[J]. Procedia Manufacturing,2017,9:198−205.
    [6]
    SEONGJIN Y, JUN H P, WON T K. Data-centricmiddleware based digital twin platform for dependable cyber-physical systems [C]//Ninth International Conference on Ubiquitous and Future Networks(ICUFN), 2017: 922−926.
    [7]
    宋学官, 何西旺, 李昆鹏, 等. 人体骨骼数字孪生的构建方法及应用[J]. 机械工程学报, 2022, 58(18): 218−228.

    SONG Xuegan, HE Xiwang, LI Kunpeng, et al. Construction method and application of digital twin of human skeleton [J]. Journal of Mechanical Engineering, 2022, 58(18): 218−228.
    [8]
    王兴志,翟海保,严亚勤,等. 基于数字孪生和深度学习的 新一代 调控系统预调度方法[J]. 上海交通大学学报,2021,55(S2):37−41.

    WANG Xingzhi,ZHAI Haibao,YAN Yaqin,et al. Pre-dispatching method of new generation dispatching and control system based on digital twin and deep learning[J]. Journal of Shanghai Jiao Tong University,2021,55(S2):37−41.
    [9]
    Dassault Systemes. Meet virtual Singapore, the city's 3D digital twin [EB/OL]. (2018-01-29)[2022-09-20]. https://govinsider.asia/digital-gov/meet-virtual-singapore-citys-3d-digital-twin/.
    [10]
    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. doi: 10.13196/j.cims.2019.06.007

    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. doi: 10.13196/j.cims.2019.06.007
    [11]
    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. doi: 10.13196/j.cims.2021.02.012

    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. doi: 10.13196/j.cims.2021.02.012
    [12]
    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. doi: 10.13199/j.cnki.cst.2021.10.021

    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. doi: 10.13199/j.cnki.cst.2021.10.021
    [13]
    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, ZHANG 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.
    [14]
    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):1−13.

    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):1−13.
    [15]
    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研究[J]. 煤炭学报, 2022, 47(S1): 384-398.

    WANG Yan, ZHANG Xuhui, CAO Xiangang, et al. Research on digital Twin construction and parallel intelligent control method of Driving face[J]. Journal of China Coal Society, 2022, 47(S1): 384-398.
    [16]
    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(S1):506−513. doi: 10.13225/j.cnki.jccs.2019.1453

    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. doi: 10.13225/j.cnki.jccs.2019.1453
    [17]
    龚晓燕,雷可凡,吴群英,等. 数字孪生驱动的掘进工作面出风口风流智能调控系统[J]. 煤炭学报,2021,46(4):1331−1340. doi: 10.13225/j.cnki.jccs.2020.0963

    GONG Xiaoyan,LEI Kefan,WU Qunying,et al. Digital twin driven airflow intelligent control system for the air outlet of heading face[J]. Journal of China Coal Society,2021,46(4):1331−1340. doi: 10.13225/j.cnki.jccs.2020.0963
    [18]
    张 超,张旭辉,毛清华,等. 煤矿智能掘进机器人数字孪生系统研究 及应用[J]. 西安科技大学学报,2020,40(5):813−822.

    ZHANG Chao,ZHANG Xuhui,MAO Qinghua,et al. Research and application of digital twin system for intelligent tunneling equipment in coal mine[J]. Journal of Xi'An University of Science And Technology,2020,40(5):813−822.
    [19]
    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.
    [20]
    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):311−320. doi: 10.13225/j.cnki.jccs.yg20.1904

    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):311−320. doi: 10.13225/j.cnki.jccs.yg20.1904
    [21]
    仇晓黎, 朱 睿, 幸 研, 等. 螺线管装配生产线数字孪生建模技术[J]. 计算机集成制造系统, 2022, 28(6): 1696−1703.

    QIU Xiaoli, ZHU Rui, XING Yan, et al. Digital twin modeling technology for the solenoid assembly production line[J]. Computer Integrated Manufacturing Systems, 2022, 28(6): 1696−1703.
    [22]
    DIGNE J, FRANCHIS C D. The Bilateral Filter for Point Clouds[J]. Computer Science,2017, 7: 278−287.
    [23]
    HARMANY Z T, MARCIA R F, WILLETT R M. Sparse Poisson intensity reconstruction algorithms[C]//Statistical Signal Processing, 2009. SSP09. IEEE/SP 15th Workshop on, 2009: 634−637.
    [24]
    ROSHNARA N P P, JABBAR S. Efficient 3D visual hull reconstruction b- sed on marching cube algorithm[C]//Intermational Conference on Innovations in Information, Coimbatore: 2015.

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