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Patrick Rizk, UQAR: Flaw Diagnosis on Wind Turbine Blade via Hyperspectral Imaging
During the wind turbine's lifetime, its major components, the blades, are susceptible to deterioration and normal wear and tear that limit their efficiency, increase their maintenance costs, and enlarge their downtime periods. Although many faults' detection methods were used, remote inspection techniques such as hyperspectral imaging are recently widely used. In this study, the potential of this non-destructive and fast monitoring technique in the classification and detection of blade surface defects and icing incident in their early stages of occurrence is demonstrated. Specifically, it lists the types, causes and detection techniques of these damage.