Abstract In this paper, we propose a blade loading sensing system for model tests of floating wind turbines (FWTs) in the wave basin. The sensing system is based on Fiber Bragg Grating (FBG) sensors and a Fiber Optical Rotary Joint (FORJ). Systematical model tests are conducted for the novel SJTU-S4 FWT in the wave basin to reveal the characteristics of FWT blade loads under different environmental conditions. Results show that the developed FBG-FORJ system performs well to capture the FWT blade loads while not smearing other FWT dynamics. The FWT blade loading is determined by gravity, centrifugal force, aerodynamic loads, as well as wave and current excitations. The driving wind takes the lead in the FWT blade loads. An increased driving wind corresponds to increased blade loads in magnitude and fluctuation, as well as increased nP (n times per revolution) harmonics. The incident wave generates considerable responses at the wave frequency and introduces more loading fluctuations. The current tends to eliminate the floater inclination generated by the driving wind and subsequently mitigates the unsteady blade loading, despite the increased floater sway and roll fluctuations. This work extends the knowledge of FWT aerodynamics and helps to investigate advanced FWT control strategies.

中文翻译：

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波浪盆模型试验中浮式风机叶片加载性能

摘要 在本文中，我们提出了一种叶片载荷传感系统，用于波浪盆中浮动风力涡轮机 (FWT) 的模型测试。传感系统基于光纤布拉格光栅 (FBG) 传感器和光纤旋转接头 (FORJ)。对新型 SJTU-S4 FWT 在波浪盆中进行了系统模型测试，以揭示不同环境条件下 FWT 叶片载荷的特征。结果表明，开发的 FBG-FORJ 系统在捕获 FWT 叶片负载方面表现良好，同时不会影响其他 FWT 动力学。FWT 叶片载荷由重力、离心力、空气动力载荷以及波浪和电流激励决定。驱动风在 FWT 叶片负载中占主导地位。增加的驱动风对应于增加的叶片载荷的大小和波动，以及增加的 nP（每转 n 次）谐波。入射波在波频率下产生相当大的响应并引入更多的负载波动。尽管漂浮物摇摆和滚动波动增加，但水流往往会消除由驱动风产生的漂浮物倾斜度，并随后减轻不稳定的叶片载荷。这项工作扩展了 FWT 空气动力学的知识，并有助于研究先进的 FWT 控制策略。