Review on Artificial Intelligence-aided Life Extension Assessment of Offshore Wind Support Structures

Abstract

AbstractThe primary objective of the present literature review is to provide a constructive and systematical discussion based on the relevant development, unsolved issues, gaps, and misconceptions in the literature regarding the fields of study that are building blocks of artificial intelligence-aided life extension assessment for offshore wind turbine support structures. The present review aims to set up the needed guidelines to develop a multi-disciplinary framework for life extension management and certification of the support structures for offshore wind turbines using artificial intelligence. The main focus of the literature review centres around the intelligent risk-based life extension management of offshore wind turbine support structures. In this regard, big data analytics, advanced signal processing techniques, supervised and unsupervised machine learning methods are discussed within the structural health monitoring and condition-based maintenance planning, the development of digital twins. Furthermore, the present review discusses the critical failure mechanisms affecting the structural condition, such as high-cycle fatigue, low-cycle fatigue, fracture, ultimate strength, and corrosion, considering deterministic and probabilistic approaches.