The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
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Articles | Volume XLIII-B2-2020
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B2-2020, 1121–1127, 2020
https://doi.org/10.5194/isprs-archives-XLIII-B2-2020-1121-2020
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B2-2020, 1121–1127, 2020
https://doi.org/10.5194/isprs-archives-XLIII-B2-2020-1121-2020

  14 Aug 2020

14 Aug 2020

3D RECONSTRUCTION OF ON-/OFFSHORE WIND TURBINES FOR MANUAL AND COMPUTATIONAL VISUAL INSPECTION

T. Möller1, D. Brün2, D. Langenkämper1, R. van Kevelaer1, and T. W. Nattkemper1 T. Möller et al.
  • 1Bielefeld University, Bielefed, Germany
  • 2saltation GmbH & Co. KG, Bielefeld, Germany

Keywords: 3D Reconstruction, Image Processing, Deep Learning, Computer Graphics, Infrastructure Monitoring, Texture Mapping

Abstract. The expansion of off-/onshore wind farms plays a key role in the transformation of energy production from burning of fossil fuels and nuclear energy to sustainable and safe power generation. However, the wind energy sector is permanently under strong cost pressure and the maintenance of the turbines is currently still carried out quite expensively with human industrial climbers. In this article, we present the results of an interdisciplinary research project on the automation of various image-based inspection steps. Since the use of unmanned aerial vehicles (UAV) is a problem especially offshore, we present here a simple, cost-effective method to obtain a three-dimensional model of a wind energy plant using solely a digital camera equipped with a sensor array to use it for the detection and management of damages and abnormalities. A first approach to detect abnormalities on the surface with deep learning methods achieved an F1-score of about 95%.