Research on digital twin technology and its application in intelligent operation and maintenance of high-speed railway infrastructure

Purpose This paper analyzes the application of digital twin technology in the field of intelligent operation and maintenance of high-speed railway infrastructure from the perspective of top-level design. Design/methodology/approach This paper provides a comprehensive overview of the definition, connotations, characteristics and key technologies of digital twin technology. It also conducts a thorough analysis of the current state of digital twin applications, with a particular focus on the overall requirements for intelligent operation and maintenance of high-speed railway infrastructure. Using the Jinan Yellow River Bridge on the Beijing–Shanghai high-speed railway as a case study, the paper details the construction process of the twin system from the perspectives of system architecture, theoretical definition, model construction and platform design. Findings Digital twin technology can play an important role in the whole life cycle management, fault prediction and condition monitoring in the field of high-speed rail operation and maintenance. Digital twin technology is of great significance to improve the intelligent level of high-speed railway operation and management. Originality/value This paper systematically summarizes the main components of digital twin railway. The general framework of the digital twin bridge is given, and its application in the field of intelligent operation and maintenance is prospected.

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Publication Details

Journal
Railway Sciences
Published
2024-11-08
DOI
https://doi.org/10.1108/rs-09-2024-0036
Citations
4
Primary Topic
Advanced Research in Systems and Signal Processing
Type
article
Field-Weighted Citation Impact
1.31
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article

Research on digital twin technology and its application in intelligent operation and maintenance of high-speed railway infrastructure

Yi Liu, Peifen Pan, Qiliang Zhao, Xueying Wang et al.
4 citations
Railway Sciences
Advanced Research in Systems and Signal Processing
1.31
article

Research on digital twin technology and its application in intelligent operation and maintenance of high-speed railway infrastructure

Yi Liu, Peifen Pan, Qiliang Zhao, Xueying Wang, Boqing Feng, Ping Li
article en
4 citations

Abstract

Purpose This paper analyzes the application of digital twin technology in the field of intelligent operation and maintenance of high-speed railway infrastructure from the perspective of top-level design. Design/methodology/approach This paper provides a comprehensive overview of the definition, connotations, characteristics and key technologies of digital twin technology. It also conducts a thorough analysis of the current state of digital twin applications, with a particular focus on the overall requirements for intelligent operation and maintenance of high-speed railway infrastructure. Using the Jinan Yellow River Bridge on the Beijing–Shanghai high-speed railway as a case study, the paper details the construction process of the twin system from the perspectives of system architecture, theoretical definition, model construction and platform design. Findings Digital twin technology can play an important role in the whole life cycle management, fault prediction and condition monitoring in the field of high-speed rail operation and maintenance. Digital twin technology is of great significance to improve the intelligent level of high-speed railway operation and management. Originality/value This paper systematically summarizes the main components of digital twin railway. The general framework of the digital twin bridge is given, and its application in the field of intelligent operation and maintenance is prospected.

Railway SciencesVol. 3(6)
Jilin Jianzhu University (CN), China Academy of Railway Sciences (CN)
Openalex Percentile: Top 19%
Advanced Research in Systems and Signal Processing
1.31
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Research on digital twin technology and its application in intelligent operation and maintenance of high-speed railway infrastructure — Yi Liu, Peifen Pan, et al. · Railway Sciences (2024) | TGRS Research Map | TGRS