Corrosion Prognostics for Offshore Wind- Turbine Structures Using Bayesian Filtering with Bi-Modal and Linear Degradation Models

Abstract

New offshore wind farms are often operating far from the shore and under challenging operating conditions, making manual on-site inspections expensive. Therefore, there is a growing need for remote condition monitoring and prognostics systems for such offshore wind farms. In this paper, we focus on corrosion prognosis since corrosion is a major failure mode of offshore wind turbine structures. In particular, we propose two algorithms for corrosion prognosis by employing Bayesian filtering techniques, one is based on linear degradation and another is based on a bi-modal corrosion model. Due to distinct characteristics of the two degradation models, different Bayesian filtering implementations are therefore required. Although the degradation model of the latter method more accurately reflects the ground truth, we find that the former prognosis method is computationally more efficient and likely more robust against various noise sources.