Wind turbine blade erosion is typically assessed in situ using visual inspection, which is a rudimentary qualitative assessment of the condition of the blade coating system. On coated test specimens in laboratory test conditions, mass loss can provide a better understanding of the stage of erosion, but cannot be extended to real world applications. In this work, by using analysis of photographs, microscopy images, mass data, and gloss data together, it was found that gloss measurements can effectively quantify changes in coating microstructure as a result of rain erosion. This was achieved by correlating and comparing mass loss measurements over time with surface gloss and verifying the erosion stages with photographs and microscopy images. As such, gloss was shown to represent the erosion stages with greater accuracy than the current industry methods. This novel technique has been shown to identify the incubation period, that is the onset of erosion damage, by detecting microstructure changes which are not visible to the naked eye, nor is determinable by mass loss. The quantitative output from the gloss methodology thus allows wind turbine owners and operators to assess, manage, and plan more efficiently for costly erosion repairs and future inspections. The system is presently being used in a laboratory setting, though it has the potential to be combined with drones or climber robots to be remotely used within the wind farm.
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