Research on digital twin monitoring system during milling of large parts

被引:0
作者
Lu, Yao [1 ]
Yue, Caixu [1 ]
Liu, Xianli [1 ]
Wang, Lihui [2 ]
Liang, Steven Y. [3 ]
Xia, Wei [1 ]
Dou, Xueping [1 ]
机构
[1] Harbin Univ Sci & Technol, Key Lab Adv Mfg & Intelligent Technol, Minist Educ, Harbin 150080, Peoples R China
[2] KTH Royal Inst Technol, S-25175 Stockholm, Sweden
[3] Georgia Inst Technol, George W Woodruff Sch Mech Engn, Atlanta, GA 30332 USA
基金
中国国家自然科学基金;
关键词
Digital twin; Milling stability; Adaptive thresholds; On-line monitoring; SEMI-DISCRETIZATION METHOD;
D O I
10.1016/j.jmsy.2024.10.027
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
In the milling process of large-scale critical parts of energy equipment, the rigidity of the tool can be lower than that of workpieces, which makes it easy to trigger tool chatter. When the vibration is large, the tool cannot act on the workpiece and cannot effectively remove the material. In severe cases, the tool will be embedded inside the workpiece, resulting in the tool and the workpiece being scrapped at the same time. At the same time, in the event of programming errors, the tool or shank could interfere or collide with workpieces or worktable, which may damage the machine parts and reduce the machining accuracy of machine tool, leading to economic losses and even casualties. In response to the problems of tool chatter and tool collision in the milling process, this paper has done four steps as follows to improve the monitoring, modeling, and control of the machining dynamics integrity. First of all, the study constructs a digital twin monitoring system framework for the milling process of large parts, utilizes Unity 3D to build the digital twin virtual system, designs and develops the relevant functions of the virtual machine tool. Secondly, this study establishes a dynamic cutting thickness model for high-feed milling cutter and a milling dynamics model for rigid parts, and builds the stability lobe diagram (SLD) based on the modal parameters and milling force coefficients. In turn, the study obtains the chatter adaptive threshold of the digital twin monitoring system with the guidance of the stabilizing leaf petal diagram. Thirdly, this study also utilizes OPC UA protocol and LabVIEW to acquire the signals of spindle position, speed, acceleration, etc., and process them. Based on the digital twin front-end technology, it will realize user interaction, machine tool collision prevention, and cutting parameters calculation; then based on the digital twin back-end technology, it will obtain the theoretical guidance for chatter monitoring, suppression, and prediction. Finally, it proposes a driver update database based on the MySQL, and utilizes it to update the back-end model of the digital twin monitoring system. According to the experimental test of the digital twin monitoring system under realistic machining process conditions, the results show that the system has a certain improvement in processing safety and processing quality, which has carries practical value and guiding significance.
引用
收藏
页码:834 / 847
页数:14
相关论文
共 42 条
  • [1] Machine monitoring system: a decade in review
    Ahmad, Maznah Iliyas
    Yusof, Yusri
    Daud, Md Elias
    Latiff, Kamran
    Kadir, Aini Zuhra Abdul
    Sair, Yazid
    [J]. INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY, 2020, 108 (11-12) : 3645 - 3659
  • [2] Hybrid Edge Cloud: A Pragmatic Approach for Decentralized Cloud Computing
    Alamouti, Siavash M.
    Arjomandi, Fay
    Burger, Michel
    [J]. IEEE COMMUNICATIONS MAGAZINE, 2022, 60 (09) : 16 - 29
  • [3] Digital twins for cutting processes
    Bergs, T.
    Biermann, D.
    Erkorkmaz, K.
    M'Saoubi, R.
    [J]. CIRP ANNALS-MANUFACTURING TECHNOLOGY, 2023, 72 (02) : 541 - 567
  • [4] Development of a novel online chatter monitoring system for flexible milling process
    Chen, Ding
    Zhang, Xiaojian
    Zhao, Huan
    Ding, Han
    [J]. MECHANICAL SYSTEMS AND SIGNAL PROCESSING, 2021, 159
  • [5] Numerical Integration Method for Prediction of Milling Stability
    Ding, Ye
    Zhu, LiMin
    Zhang, XiaoJian
    Ding, Han
    [J]. JOURNAL OF MANUFACTURING SCIENCE AND ENGINEERING-TRANSACTIONS OF THE ASME, 2011, 133 (03):
  • [6] Second-order full-discretization method for milling stability prediction
    Ding, Ye
    Zhu, LiMin
    Zhang, XiaoJian
    Ding, Han
    [J]. INTERNATIONAL JOURNAL OF MACHINE TOOLS & MANUFACTURE, 2010, 50 (10) : 926 - 932
  • [7] A full-discretization method for prediction of milling stability
    Ding, Ye
    Zhu, LiMin
    Zhang, XiaoJian
    Ding, Han
    [J]. INTERNATIONAL JOURNAL OF MACHINE TOOLS & MANUFACTURE, 2010, 50 (05) : 502 - 509
  • [8] Chatter suppression for milling of thin-walled workpieces based on active modal control
    Du, Jianan
    Long, Xinhua
    [J]. JOURNAL OF MANUFACTURING PROCESSES, 2022, 84 : 1042 - 1053
  • [9] Developing sensor signal-based digital twins for intelligent machine tools
    Ghosh, Angkush Kumar
    Ullah, A. M. M. Sharif
    Teti, Roberto
    Kubo, Akihiko
    [J]. JOURNAL OF INDUSTRIAL INFORMATION INTEGRATION, 2021, 24
  • [10] Grieves M, 2017, T DISCIPLINARY PERSP, P85, DOI 10.1007/978-3-319-38756-7_4