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Romotioncam, BAM & Latoda: Innovating Wind Turbine Inspections

At Romotioncam, we’re excited to share a breakthrough achievement in collaboration with LATODA and the experts at Bundesanstalt für Materialforschung und -prüfung (BAM), specifically the Thermographic Methods team.

Our joint effort aimed to seamlessly integrate two distinct camera systems, a ground-based inspection camera by Romotioncam and a custom Pitch-Traversal-Unit triggering an Infratec Image IR 8880 thermal camera by BAM. The challenge? Harmonizing the capture of both optical and thermographic turbine blade images simultaneously and precisely.

After meticulous coordination and adjustments, our innovative ground-based inspection camera, capturing dynamic blade sequences, worked in tandem with BAM’s thermal camera triggered by the Pitch-Traversal-Unit. The result? A comprehensive dataset combining thermographic and optic turbine blade images, providing precise inputs for advanced analysis.

The Ren-AI system by LATODA played a crucial role, utilizing two algorithms to analyze the datasets effectively. The images were strategically taken at the 3, 6, and 9 o’clock positions from both the front and back, with special attention to the 7 o’clock backside position to avoid pylon/mast interference.

Despite the challenges of installation and coordination, the team persevered, capturing up to eight images per blade and amassing an impressive sample size of around 280 images. The weather played its part, transitioning from good to ideal conditions, minimizing wind direction changes during turbine operation and optimizing lighting for both optical and thermographic analysis.

The Storkow field test not only marked a successful collaboration but also provided valuable insights into refining our combined imaging process. This initial dataset serves as a foundation for testing and enhancing our AI system, unlocking a deeper understanding of the synergies between thermal and regular inspection images.

Looking ahead, our focus is on establishing a consistent method for matching different image types and further optimizing the setup of both camera systems. This endeavor is pivotal in advancing the overall surveillance of wind turbines, paving the way for increased electricity generation through AI-based rotor blade inspections.

Stay tuned as we continue to push the boundaries of innovation in renewable energy!

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