Damage identification of monopile offshore wind structures using data fusion of acceleration and angular velocity

Abstract

Recently, a significant number of offshore wind structures have been constructed as the renewable energy has been considered to be an essential alternative source of energy for sustainable societies. While these offshore wind structures are exposed to a harsh environment with strong wind and tide, sufficient attention and research effort have not been made to date. This study proposes a damage identification method using data fusion of acceleration and angular velocity responses measured from monopile offshore wind structures. Whereas the traditional damage detection methods utilizing a sole type of measurement such as acceleration or strain, the proposed approach is based on the combination of two different measurements to significantly improve damage detection performance. A damage sensitive index is proposed as a form of energy ratios between acceleration and angular velocity responses at each natural mode. An important advantage of the proposed damage index is that it is independent of temperature changes, which allows the damage detection to be robust in the field testing environment. A numerical simulation is conducted to validate the efficacy of the proposed damage detection algorithm using a monopile offshore wind structure. © 2017 Taylor & Francis Group, London.