Revamping structural health monitoring of advanced rail transit systems: A paradigmatic shift from digital shadows to digital twins
Mujib Olamide Adeagbo, Su-Mei Wang, Yi‐Qing Ni
Abstract
Advanced rail transit systems (ARTS), including high-speed rail and maglev trains, provide enhanced transportation options to meet the growing demand for efficient transportation systems. However, they present unique challenges in maintaining the safety and performance of their infrastructures. Structural health monitoring (SHM) has emerged as an essential practice to forestall the potential consequences of structural defects in ARTS. Recently, digital twins and digital shadows have been successfully employed in various industries to monitor the state of physical systems. However, their application for structural health monitoring in ARTS remains largely unexplored. Hence, this article explores the potential of digital twins and digital shadows, in improving structural health monitoring in ARTS. Due to the digital twins’ ability to bi-directional communication between a real system and its virtual replica, this article presents a comprehensive literature survey on their enablers and capabilities. Meanwhile, a framework for digital twins-based monitoring in ARTS is also proposed. The key distinctions and benefits of digital twins over other Industry 4.0 digital representation concepts, such as real-time monitoring, optimization, prediction, simulation, and decision-making, are identified. The paper highlights the significant opportunities that digital twins, especially, can offer to improve health monitoring. Similarly, limitations and bottlenecks that must be tackled in future research for implementations are also acknowledged. Finally, harnessing the power of digital twins can catalyze a transformative shift in ARTS, leading to more effective monitoring, enhanced safety, and improved performance.