High-Resolution Structure-from-Motion for Quantitative Measurement of Leading-Edge Roughness

Mikkel Schou Nielsen, Ivan Adriyanov Nikolov, Emil Krog Kruse, Jørgen Garnæs, Claus B. Madsen

Research output: Contribution to journalJournal articleResearchpeer-review

3 Citations (Scopus)
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Abstract

Over time, erosion of the leading edge of wind turbine blades increases the leading-edge roughness (LER). This may reduce the aerodynamic performance of the blade and hence the annual energy production of the wind turbine. As early detection is key for cost-effective maintenance, inspection methods are needed to quantify the LER of the blade. The aim of this proof-of-principle study is to determine whether high-resolution Structure-from-Motion (SfM) has the sufficient resolution and accuracy for quantitative inspection of LER. SfM provides 3D reconstruction of an object geometry using overlapping images of the object acquired with an RGB camera. Using information of the camera positions and orientations, absolute scale of the reconstruction can be achieved. Combined with a UAV platform, SfM has the potential for remote blade inspections with a reduced downtime. The tip of a decommissioned blade with an artificially enhanced erosion was used for the measurements. For validation, replica molding was used to transfer areas-of-interest to the lab for reference measurements using confocal microscopy. The SfM reconstruction resulted in a spatial resolution of 1 mm as well as a sub-mm accuracy in both the RMS surface roughness and the size of topographic features. In conclusion, high-resolution SfM demonstrated a successful quantitative reconstruction of LER.
Original languageEnglish
Article number3916
JournalEnergies
Volume13
Issue number15
ISSN1996-1073
DOIs
Publication statusPublished - 2020

Keywords

  • Structure from Motion (SfM)
  • 3D reconstruction
  • Microscopy
  • Wind Turbine Blades
  • Benchmark
  • Quantitative 3D reconstruction
  • Structure from motion
  • Blade inspection
  • Leading-edge roughness
  • Surface analysis
  • Photogrammetry

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