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It is currently a prevailing trend to adopt clean energies instead of traditional ones due to the global climate change caused by carbon emissions. Offshore wind farms, in particular, have emerged as a crucial source of renewable energy, owing to their benefits such as no land occupation and abundant resources. However, the design, installation, operation, and maintenance (O&M) of floating wind turbines (FWTs) involve multiple sources of heterogeneous data, which pose challenges to data integration and management, as well as to the simulation and analysis of FWTs. To address this issue, this study proposes a unified framework based on digital twin (DT) to acquire and integrate diverse types of information used throughout the entire life cycle of FWTs. A digital 3D model serves as a medium to enable real-time synchronization and inversion of sensor data, facilitating the simulation and analysis of the global state of FWTs. The proposed framework is evaluated through a case study of a twin-barge float-over project, which includes process simulation, mechanical analysis, and anomaly identification. The results demonstrate that DT can facilitate timely monitoring and analysis of FWTs, and enable visualization of construction plans, early warning of structural abnormalities, and accurate recognition of FWT posture and marine environment. The case study validates the efficacy of the proposed framework in ensuring personnel and equipment safety, optimizing project plans, and improving construction efficiency.
Liu et al. (Mon,) studied this question.