How image capturing setups influence the quality of SfM reconstructions for wind turbine blade inspection

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Abstract

Increased leading edge roughness (LER) is one of the main causes for wind turbine blade performance degradation. To ensure a consistently high energy output, the surface erosion of wind turbine blades, needs to be monitored regularly, so preventive measurements can be done. Capturing 3D surface data is becoming a more and more popular way to extract and quantify roughness on a micro level. In this paper we want to test the possibility of using Structure from Motion (SfM) 3D reconstructions for extracting surface roughness information from wind turbine blades. We test various capturing scenarios with varying horizontal and vertical image overlap, as well as varying distances to the blade, using a real blade in outdoor conditions. We analyze the quality of the reconstructions and provide a benchmark, as well as guidelines to what are the best possible capturing conditions for ensuring a high quality and noise free 3D surface results. All data from the experiments is made publicly accessible.
Original languageEnglish
Title of host publicationSPIE Future Sensing Technologies
EditorsMasafumi Kimata, Joseph A. Shaw, Christopher R. Valenta
Number of pages15
Volume11525
PublisherSPIE - International Society for Optical Engineering
Publication date8 Nov 2020
Pages368-382
Article number115251P
ISBN (Print)9781510638617
ISBN (Electronic)9781510638624
DOIs
Publication statusPublished - 8 Nov 2020
EventSPIE Future Sensing Technologies - Online, Japan
Duration: 9 Nov 202013 Nov 2020

Conference

ConferenceSPIE Future Sensing Technologies
LocationOnline
CountryJapan
Period09/11/202013/11/2020
SeriesProceedings of SPIE, the International Society for Optical Engineering
Volume11525
ISSN0277-786X

Keywords

  • Structure from Motion (SfM)
  • wind turbine blades
  • 3D reconstruction
  • benchmarking
  • surface analysis
  • surface roughness
  • inspection

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