A Damage Detection and Location Scheme for Offshore Wind Turbine Jacket Structures Based On Global Modal Properties

Structural failures of offshore wind turbine substructures might be less likely than failures of other equipment of the wind turbine generator but pose a high risk due to the possibility of catastrophic consequences. Significant costs are linked to offshore operations like inspections and maintenance, thus remote monitoring shows promise for cost-efficient structural integrity management. This work is aimed to investigate the feasibility of the two-level detection, in terms of anomaly identification and localisation, in the jacket structure of an offshore wind turbine. A monitoring scheme is developed based on a database of modal properties of the structure for different scenarios. The method identifies the correct anomaly scenario based on three types of modal indicators, namely natural frequency, the modal assurance criterion between mode shapes, and the modal flexibility variation. The supervised Fisher's linear discriminant analysis is applied to transform the modal indicators to maximise the separability of anomaly scenarios. A Fuzzy clustering algorithm is trained to predict the membership of new data to the scenarios in the database. In a case study, extreme scour phenomena and jacket member integrity loss are simulated, together with variations of the structural dynamics for environmental and operating conditions. Cross-validation is used to select the best hyperparameters and the effectiveness of the clustering is validated with slight variations of the environmental conditions. The results prove that it is feasible to detect and localise the simulated scenarios via the global monitoring of an offshore wind jacket structure.