Abstract

For offshore structures such as offshore wind turbines (OWT), typhoon is usually considered one of the most critical threats to structural safety performances and service life due to its heavy wind, wave, and even coexisted storm surge. Meanwhile, it is challenging to obtain the systematic data from the environmental conditions, structural dynamic vibrations and the SCADA record, when typhoon passes by the offshore wind farm. Taking into account these situations, a real-time multi-source monitoring system enabling the investigation of the typhoon impact on the performances of OWT, has been firstly established and implemented to a 4.0 MW mono-pile OWT in Rudong, Jiangsu, China. One of the major contributions in this work is to develop the monitoring system using a unique environment of real-world data that has been synchronously obtained from waves, winds, vibrational accelerations, inclinations of towers and SCADA data during the typhoon “In-fa” passing by the wind farm, and provide the scientific community with the underlying standards and technical recommendations. To investigate the influence caused by “In-fa”, comparison results of the measured data in the range of June to August have been analysed. It is worth noting that two conclusions have been obtained: (1) the region near the nacelle is not always the most critical vibrational area. Actually, the change of the maximum structural response in the position under different external loads should be applied to effectively evaluate the structural safety; (2) the measured accelerations exhibit an obvious decay process in the presence of the turbine rotor-stop, but not the yaw rigid-body motion. This observation promotes the accurate identification of modal parameters for the long-term monitoring. Consequently, these valuable findings to facilitate the assessment of structural operational conditions have been developed into two guide-lines. All the data and analyses presented in this paper provide a valuable insight into the design, energy efficiency, safety monitoring and damage diagnosis of OWT structures.

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