Requirements and challenges for infusion of SHM systems within Digital Twin platforms

• Published in: Structure and infrastructure engineering Vol. ahead-of-print; no. ahead-of-print; pp. 1 - 17
• Main Authors: Chacón, Rolando, Casas, Joan R., Ramonell, Carlos, Posada, Hector, Stipanovic, Irina, Škarić, Sandra
• Format: Journal Article
• Language: English
• Published: Taylor & Francis 17.06.2023
• Subjects: Computer vision; digital twins; performance indicators; predictive maintenance; remote sensing; sensors; structural health monitoring
• ISSN: 1573-2479; 1744-8980
• DOI: 10.1080/15732479.2023.2225486

The need for measurable data from physical assets to actively feed a living Digital Twin (DT) is paramount. The requirements and needs that the gathered data should fulfill in order to be practically implemented in the stream data pipeline are heterogeneous, some of them general and other case-specific. This article summarizes a set of identified challenges and requirements for a seamless infusion of well-established Structural Health Monitoring (SHM) systems within DT platforms, without the objective of solve all of them. This identification is performed based on a review of traditional SHM systems with a vast array of information sources as well as on the review of techniques for the systematic digitalization of existing assets. On the other hand, ten real demo cases belonging to Ashvin, an H2020 Research and Innovation project, are providing real world testing beds for an active development of SHM infused in DT systems. Multiple information sources are studied in those sites, which also enriches with more realism, the identification of requirements and challenges presented herein. These assets provide a perspective to researchers about practical implications of these needs.