Application of Digital Twin in Structural Health Monitoring of Civil Structures: A Systematic Literature Review Based on PRISMA

Abstract

Structural Health Monitoring (SHM) systems are critical for ensuring the safety and longevity of structures. Digital twin technology has emerged as a promising tool to improve the accuracy and efficiency of SHM systems. This paper presents a systematic literature review based on PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) on the applications of digital twin for SHM of civil structures. And this systematic literature review examines the current trends and developments in the application of digital twin technology in SHM systems for structures. The review identified 45 relevant articles published between 2010 and 2023 that covered various applications of digital twin in SHM systems, including buildings, bridges, wind turbines, trains, and gas turbines. Key themes identified from the literature review included the integration of physical models and machine learning algo-rithms, the use of distributed sensor networks, and the importance of real-time data analysis for effective SHM. The findings suggest that digital twin technology has the potential to significantly improve the accuracy and efficiency of SHM systems, but further research is needed to develop more advanced and integrated Digital Twin-Based SHM systems for different types of civil structures.