A digital twin platform for structural health monitoring

Engineering structures such as bridges and wind turbines need to have a long useful lifetime. As a result, different approaches for lifetime extension are currently being explored, with one particularly prevalent approach being vibration-based Structural Health Monitoring (SHM) using Digital Twin (DT) technology. However, there are some challenges with this approach, especially in integrating sensing across physical twins, creating representative models, and applying SHM methods. This paper addresses the challenges by presenting a DT workflow for constructing DTs from sensing data, finite-element models, and SHM methods, and subsequently using them for SHM purposes. The workflow is implemented on a new DT platform, namely, the Digital Twin as a Service (DTaaS), which facilitates the task of building, using, and sharing DTs in a collaborative environment. The workflow and its platform implementation are demonstrated in the context of an experimental case study with a beam in different structural configurations.