Offshore Wind Turbine Monopile Monitoring Using Guided Ultrasonic Waves

Abstract

Following the rapid expansion of offshore wind farms (OWFs) within the next decade many existing OWFs, typically employing monopile supports, will come to the end of their design life. Life extension offers the potential for continued renewable electricity generation at competitive costs. The viability of continued operation can be quantified using fatigue reliability analysis, enabling risk-based decision-making for the life extension of OWFs. This contribution proposes a novel active learning framework with an ensemble of surrogate models, applied to the numerical model of an offshore wind turbine, to predict fatigue reliability. Guided waves can be employed to inspect and monitor inaccessible, submerged, and embedded sections of the wind turbine support, as they can propagate long distances along thin structures such as monopiles. This could allow for the detection of fatigue cracks and corrosion at critical weld locations below the mudline, providing important information for risk-based life extension. Experiments were conducted on a laboratory scale monopile to assess the guided wave propagation and sensitivity for the detection of critical defects. The guided wave data could be combined with wind and wave data to improve the fatigue reliability analysis based on Structural Health Monitoring (SHM).