Posters

Abstract

Asset Integrity Management encompasses comprehensive approaches to ensuring the structural integrity, reliability, and longevity of offshore wind turbines and foundations. It involves a systematic framework encompassing monitoring, inspection, maintenance, and risk management protocols. In terms of structural monitoring, the state of the art in the bottom-fixed wind industry generally consists in the use of structural health monitoring (SHM) systems on a limited number of wind turbines of the farm (typically 10%) while the others have little or no instrumentation. SHM systems employ a variety of sensors, such as strain sensors, accelerometers, and inclinometers to collect data on vibrations, deformations and possibly other parameters, which are then analysed continuously or periodically in order to assess the health of the structural components. These practices have two majors limitations. The initial investment and operational costs associated with implementing and maintaining SHM systems can be significant. Also, there is a limited sensors coverage, both in terms of the number of assets monitored within a wind farm and the number of measuring points on a given asset. To overcome these limitations, a method has been developed that couples measurements obtained from a conventional SHM system with advanced digital models. This method uses a limited number of conventional structural sensors, whose measurements are augmented with digital models, in particular physical models of the assets and the farm. The method enables the generation of a large number of structural indicators at any location on the structure and any asset in the farm from a limited number of sensors compared to a conventional SHM system. This method has been applied to an offshore wind farm with bottom fixed wind turbines. This work is a joint development between IFP Energies nouvelles, which developed the methods, and GreenWITS, which tested and validated them on a case study.