# Engineering Mechanics

Proceedings Vol. 32 (2026)

ENGINEERING MECHANICS 2026

Copyright © 2026 Institute of Thermomechanics of the Czech Academy of Sciences, Prague

 

Stopel M., Szyca M., Seńko J., Radtke K.
pages 121 - 124, full text

The purpose of this study is to present a methodological framework for wind turbine damage detection using unmanned aerial vehicles supported by artificial intelligence techniques. Traditional inspection procedures are often costly, time-consuming, and contribute significantly to the operational and maintenance share of the Levelized Cost of Energy. The investigation includes an overview of the most common wind turbine structural designs, typical damage mechanisms, and power control strategies required to maintain voltage and frequency stability. Particular attention is given to the role of cyclic condition monitoring as a key factor in ensuring high efficiency and reliability of wind power systems. The proposed approach combines UAV-based visual inspection with AI-assisted damage identification, enabling safer and more effective assessment of turbine technical condition. Safety principles for conducting UAV operations in close proximity to wind turbine infrastructure are also discussed. The results confirm that integrating autonomous aerial inspection with intelligent detection methods may significantly improve maintenance strategies and support the development of more sustainable energy systems.

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All papers were reviewed by members of the scientific committee.