Design and application of digital twin system for the blade-rotor test rig

被引:30
作者
Duan, Jian-Guo [1 ]
Ma, Tian-Yu [1 ]
Zhang, Qing-Lei [1 ]
Liu, Zhen [1 ]
Qin, Ji-Yun [1 ]
机构
[1] Shanghai Maritime Univ, Shanghai 201306, Peoples R China
基金
中国国家自然科学基金;
关键词
System design; Digital twin; Data collection; Virtual reality interaction;
D O I
10.1007/s10845-021-01824-w
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Digital twin technology is a key technology to realize cyber-physical system. Owing to the problems of low visual monitoring of the blade-rotor test rig and poor equipment monitoring capabilities, this paper proposes a framework based on the digital twin technology. The digital-twin based architecture and major function implementation have been carried out form five dimensions, i.e. Physical layer, Virtual layer, Data layer, Application layer and User layer. Three key technologies utilized to create the system including underlying equipment real-time communication, virtual space building and virtual reality interaction have been demonstrated in this paper. Based on RS-485 and other communication protocols, the data acquisition of the underlying devices have been successfully implemented, and then the real-time data reading has been achieved. Finally, the rationality of the system has been validated by taking the blade-rotor test rig as the application object, which provides a reference for the monitoring and evaluation of equipment involved in manufacturing and experiment.
引用
收藏
页码:753 / 769
页数:17
相关论文
共 27 条
  • [1] Digital twin-driven supervised machine learning for the development of artificial intelligence applications in manufacturing
    Alexopoulos, Kosmas
    Nikolakis, Nikolaos
    Chryssolouris, George
    [J]. INTERNATIONAL JOURNAL OF COMPUTER INTEGRATED MANUFACTURING, 2020, 33 (05) : 429 - 439
  • [2] Embedded Digital Twins in future energy management systems: paving the way for automated grid control
    Brosinsky, Christoph
    Krebs, Rainer
    Westermann, Dirk
    [J]. AT-AUTOMATISIERUNGSTECHNIK, 2020, 68 (09) : 750 - 764
  • [3] Chen Xuejun, 2012, Process Automation Instrumentation, V33, P66
  • [4] Web service QoS prediction: when collaborative filtering meets data fluctuating in big-range
    Chen, Zhen
    Shen, Limin
    Li, Feng
    You, Dianlong
    Mapetu, Jean Pepe Buanga
    [J]. WORLD WIDE WEB-INTERNET AND WEB INFORMATION SYSTEMS, 2020, 23 (03): : 1715 - 1740
  • [5] Cheng LY., 2012, ADV MAT RES, V588, P1390, DOI [10.4028/www.scientific.net/AMR.588-589.1390, DOI 10.4028/WWW.SCIENTIFIC.NET/AMR.588-589.1390]
  • [6] Chi C, 2019, ED TEACHING FORUM, V47, P273
  • [7] Ding Kai, 2019, Computer Integrated Manufacturing Systems, V25, P1491, DOI 10.13196/j.cims.2019.06.017
  • [8] Digital twin and virtual reality: a co-simulation environment for design and assessment of industrial workstations
    Havard, Vincent
    Jeanne, Benoit
    Lacomblez, Marc
    Baudry, David
    [J]. PRODUCTION AND MANUFACTURING RESEARCH-AN OPEN ACCESS JOURNAL, 2019, 7 (01): : 472 - 489
  • [9] Jian G, 2019, AEROSPACE POWER, V04, P65
  • [10] Jianguo D, 2015, MAGAZINE EQUIPMENT M, V03, P1