Abstract
This study presents a foundational step in a broader initiative aimed at leveraging thermal imaging technology to enhance wind turbine maintenance, particularly focusing on the challenges of detecting defects and object localization in small wind turbine blades. Serving as a preliminary experiment, this research project tested methodologies and technologies on a smaller scale before advancing to more complex applications involving large, operational wind turbines using drone-mounted cameras. Utilizing thermal cameras suitable for both handheld and drone use, alongside advanced image processing applications, we navigated the significant challenge of acquiring high-quality thermal images to detect small defects. This required a concentrated analysis of a select subset of data and a methodological shift towards object detection and localization using the You Only Look Once (YOLO) model versions 8 and 9. This effort not only paves the way for applying these techniques to larger-scale turbines but also contributes to the ongoing development of an integrated maintenance strategy in the wind energy sector. Highlighting the critical impact of environmental conditions on thermal imaging, our research underscores the importance of continued exploration in this field, especially in enhancing object localization techniques for the future drone-based maintenance of operational wind turbine blades (WTBs).
Published Version
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