Investigation to the nonlinearity evolution of offshore wind turbines using field data: Application to a 4 MW monopile offshore wind turbine

Offshore wind turbines (OWTs) experience persistent nonlinear vibrations due to constantly changing environmental and operational conditions. These nonlinear dynamic responses significantly affect structural safety and introduce uncertainties in predicting fatigue and service life. However, understanding the complex nonlinear characteristics of OWTs is challenging because multiple factors collectively contribute to structural nonlinear vibrations. To quantitatively assess the nonlinear effects on OWT dynamic responses during operation, this paper systematically analyzes long-term monitoring data from a 4 MW monopile OWT site at Rudong Wind Farm in China using a nonlinear effect separation method based on a time-varying kernel function. This method separates the nonlinear components using the measured wave surface elevation and dynamic response data and statistically analyzes the long-term variation of nonlinear effect by combining comprehensive evaluation indicators. The correctness of the method applied to OWTs has been first verified using the shutdown condition data under calm sea conditions. Then, the influence of operating conditions, sensor placement, rotor speed, and other parameters on the nonlinear effects have been investigated through statistical analysis of the real-time evaluation results to reveal the nonlinear evolution process and its contributing factors. An unexpected discovery emerged during the monitoring process: the dynamic response of the OWT during the passage of Typhoon ‘In-FA’ was measured. Consequently, this paper emphasizes the abnormal nonlinear behavior of OWTs under typhoon conditions. The analysis results indicate that under typhoon conditions, the nonlinear effects in the structural response substantially increase, potentially contributing over 20% to the overall response. This finding suggests that current structural designs do not fully consider the nonlinear effects, potentially posing risks to safe operation. The insights from this study will also contribute to the structural design of OWTs, aiding in risk reduction and economic loss mitigation.