ON THE DEVELOPMENT OF THE STRUCTURAL DIGITAL TWIN OF AN UNMANNED AERIAL VEHICLE

Structural fatigue poses a significant concern for flight safety, particularly during the later stages of service. The Airframe Digital Twin plays a pivotal role in facilitating structural damage diagnosis and prognosis by establishing a multiphysics, multiscale, and probabilistic virtual model of an as-built system. This paper presents a comprehensive and integrated framework for constructing the digital twin of an Unmanned Aerial Vehicle, incorporating load tracking, multi-level structural analysis, and probabilistic diagnosis and prognosis. Flight tests of the UAV are utilized to validate the proposed method. Results demonstrate that the digital twin can effectively predict fatigue crack growth in real-time using flight parameters as input. Furthermore, with inspection data available, the digital twin model can be updated to provide a more accurate prediction of future damage evolution. These insights offer valuable guidance for optimizing aircraft fleet maintenance strategies, thereby enhancing safety and cost-effectiveness.