海上风力发电
风力发电
计算机科学
涡轮机
可视化
反演(地质)
可再生能源
系统工程
工程类
数据挖掘
机械工程
古生物学
电气工程
构造盆地
生物
作者
Yi Liu,Jianmin Zhang,Yan-Tao Min,Yantao Yu,Chao Lin,Zhen‐Zhong Hu
标识
DOI:10.1016/j.oceaneng.2023.115009
摘要
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.
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