EconPapers    
Economics at your fingertips  
 

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

Jian-Guo Duan, Tian-Yu Ma (), Qing-Lei Zhang, Zhen Liu and Ji-Yun Qin
Additional contact information
Jian-Guo Duan: Shanghai Maritime University
Tian-Yu Ma: Shanghai Maritime University
Qing-Lei Zhang: Shanghai Maritime University
Zhen Liu: Shanghai Maritime University
Ji-Yun Qin: Shanghai Maritime University

Journal of Intelligent Manufacturing, 2023, vol. 34, issue 2, No 20, 753-769

Abstract: Abstract 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.

Keywords: System design; Digital twin; Data collection; Virtual reality interaction (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://link.springer.com/10.1007/s10845-021-01824-w Abstract (text/html)
Access to the full text of the articles in this series is restricted.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:joinma:v:34:y:2023:i:2:d:10.1007_s10845-021-01824-w

Ordering information: This journal article can be ordered from
http://www.springer.com/journal/10845

DOI: 10.1007/s10845-021-01824-w

Access Statistics for this article

Journal of Intelligent Manufacturing is currently edited by Andrew Kusiak

More articles in Journal of Intelligent Manufacturing from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().

 
Page updated 2025-03-20
Handle: RePEc:spr:joinma:v:34:y:2023:i:2:d:10.1007_s10845-021-01824-w