Sun Zhiyan, Jayasinghe Sanduni, Sidiq Amir, Shahrivar Farham, Mahmoodian Mojtaba, Setunge Sujeeva
School of Engineering, RMIT University, 124 La Trobe Street, Melbourne, VIC 3000, Australia.
Sensors (Basel). 2024 Dec 25;25(1):59. doi: 10.3390/s25010059.
Civil infrastructure assets' contribution to countries' economic growth is significantly increasing due to the rapid population growth and demands for public services. These civil infrastructures, including roads, bridges, railways, tunnels, dams, residential complexes, and commercial buildings, experience significant deterioration from the surrounding harsh environment. Traditional methods of visual inspection and non-destructive tests are generally undertaken to monitor and evaluate the structural health of the infrastructure. However, these methods lack reliability due to the need for instrumentation calibration and reliance on subjective visual judgments. Digital twin (DT) technology digitally replicates existing infrastructure, offering significant potential for real-time intelligent monitoring and assessment of structural health. This study reviews the existing applications of DTs across various sectors. It proposes an approach for developing DT applications in civil infrastructure, including using the Internet of Things, data acquisition, and modelling, together with the platform requirements and challenges that may be confronted during DT development. This comprehensive review is a state-of-the-art review of advancements and challenges in DT technology for intelligent monitoring and maintenance of civil infrastructure.
由于人口快速增长和对公共服务的需求，民用基础设施资产对各国经济增长的贡献正在显著增加。这些民用基础设施，包括道路、桥梁、铁路、隧道、水坝、住宅小区和商业建筑，会因周围恶劣环境而出现严重损坏。通常采用传统的目视检查和无损检测方法来监测和评估基础设施的结构健康状况。然而，由于需要仪器校准以及依赖主观的目视判断，这些方法缺乏可靠性。数字孪生（DT）技术以数字方式复制现有基础设施，为结构健康的实时智能监测和评估提供了巨大潜力。本研究回顾了DT在各个领域的现有应用。它提出了一种在民用基础设施中开发DT应用的方法，包括使用物联网、数据采集和建模，以及DT开发过程中可能面临的平台要求和挑战。这一全面综述是对DT技术在民用基础设施智能监测和维护方面的进展与挑战的最新综述。
