Research on inspection of wind turbine blade inner cavity by unmanned aerial vehicle based on binocular stereovision

Quan Li; Qin Xu; Shihu Zhou; Yong Huang; Fuxue Gong

doi:10.1117/12.3031003

19 July 2024 Research on inspection of wind turbine blade inner cavity by unmanned aerial vehicle based on binocular stereovision

Quan Li, Qin Xu, Shihu Zhou, Yong Huang, Fuxue Gong

Author Affiliations +

Proceedings Volume 13181, Third International Conference on Electronic Information Engineering, Big Data, and Computer Technology (EIBDCT 2024); 131813G (2024) https://doi.org/10.1117/12.3031003
Event: Third International Conference on Electronic Information Engineering, Big Data, and Computer Technology (EIBDCT 2024), 2024, Beijing, China

Abstract

Wind turbine generators, which convert wind energy into electricity, require particularly crucial inspection of their internal blade cavities. To achieve precise inspection of the internal blade cavities, a quadcopter drone was designed with collision prevention capabilities and equipped with dual-camera stereo vision to obtain 3D point cloud reconstruction and achieve three-dimensional defect coordinate localization. The application of this advanced technology significantly enhances the efficiency of internal blade cavity inspections. During on-site testing, the drone effectively navigated a 32-meter-long blade cavity, reducing safety risks and providing precise defect location information for subsequent maintenance. This study not only keeps inspection personnel away from hazardous areas but also enables inspections to cover regions inaccessible to individuals, thereby ensuring the safe and stable operation of wind power generation.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Quan Li, Qin Xu, Shihu Zhou, Yong Huang, and Fuxue Gong "Research on inspection of wind turbine blade inner cavity by unmanned aerial vehicle based on binocular stereovision", Proc. SPIE 13181, Third International Conference on Electronic Information Engineering, Big Data, and Computer Technology (EIBDCT 2024), 131813G (19 July 2024); https://doi.org/10.1117/12.3031003

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