A digital-twin model-pattern matching-based structural health monitoring system for gravity-based aquaculture platforms

To meet the long-term safety demands of gravity-based platforms in marine ranching, this paper develops a structural health monitoring system based on digital-twin model pattern matching (DT-PM-SHM@GRP). The system is built around a four-closed-loop architecture of “sensing–twinning–matching–decision”. First, an integrated sensor network combining fiber Bragg gratings, inclinometers and meteorological instruments is deployed on site to establish a multi-source synchronous acquisition and processing system. Second, a 3D adaptive FE twin model is created; by coupling it with all potential anticipated environmental loads, a database set that links environmental parameters–load cases–structural responses is generated. Real-time on-site data features extracted from the sensor network are then used to search the twin model states via pattern matching, enabling reliable tracking of the twin’s condition. On this basis, online assessment of structural deformation, stress distribution and overall platform integrity assessment is carried out, and predictive decision-making suggestions are provided. The developed system offers a transferable and scalable digital-twin monitoring paradigm for intelligent marine-ranch safety and maintenance.