Project
Wind turbine blade degradation is a serious problem of the wind energy industry. Regular inspections are necessary to ensure the correct and safe work state of wind turbine blades. This project looks at a novel way of extracting and quantifying the roughness of wind turbine blade surfaces – through the use of Structure from Motion. It is used to reconstruct the 3D model of the surface of the blade, using a number of images from different view angles. Some challenges with SfM 3D reconstruction are the smooth, featureless and mono-colored blade surfaces, as well as the reflections from the sun when performed outdoors. The project also focuses on the creation of an autonomous drone for capturing the required images, as well as the different processes required to post-process the 3D data – scaling, removal of noise, quality verification, classification.
Scientific Work
Calculating Absolute Scale and Scale Uncertainty for SfM Using Distance Sensor Measurements: A Lightweight and Flexible Approach
Nikolov, I. A. & Madsen, C. B., 2020, Recent Advances in 3D Imaging, Modeling and Reconstruction.IGI global, p. 168-192 25 p.
High-Resolution Structure-from-Motion for Quantitative Measurement of Leading-Edge Roughness
Schou Nielsen, M., Nikolov, I. A., Kruse, E. K., Garnæs, J. & Madsen, C. B., 2020, In : Energies. 13, 15, 3916.
How image capturing setups influence the quality of SfM reconstructions for wind turbine blade inspection
Nikolov, I., Kruse, E. K. & Madsen, C., 8 Nov 2020, SPIE Future Sensing Technologies. Kimata, M., Shaw, J. A. & Valenta, C. R. (eds.). SPIE – International Society for Optical Engineering, Vol. 11525. p. 368-382 15 p. 115251P. (Proceedings of SPIE, the International Society for Optical Engineering, Vol. 11525).
Preliminary Study on the Influence of Visual Cues, Transitional Environments and Tactile Augmentation on the Perception of Scale in VR
Jensen, T. D., Kasprzak, F., Szekely, H-G., Nikolov, I. A., Høngaard, J. S. & Madsen, C. B., 2020, 22nd International Conference on Human-Computer Interaction HCII 2020.Springer, Vol. Lecture Notes in Computer Science. 7 p.
Rough or Noisy? Metrics for Noise Estimation in SfM Reconstructions
Nikolov, I. A. & Madsen, C. B., 8 Oct 2020, In : Sensors. 20, 19, p. 1-23 23 p., 5725.
Interactive Environment for Testing SfM Image Capture Configurations
Nikolov, I. A. & Madsen, C. B., 27 Feb 2019, VISIGRAPP 2019 – Proceedings of the 14th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications. Kerren, A., Hurter, C. & Braz, J. (eds.). SCITEPRESS Digital Library, p. 317-322 6 p.
Performance Characterization of Absolute Scale Computation for 3D Structure from Motion Reconstruction
Nikolov, I. A. & Madsen, C. B., 27 Feb 2019, VISIGRAPP 2019 – Proceedings of the 14th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications. Kerren, A., Hurter, C. & Braz, J. (eds.). SCITEPRESS Digital Library, Vol. 5. p. 884-891 8 p.
LiDAR-based 2D Localization and Mapping System using Elliptical Distance Correction Models for UAV Wind Turbine Blade Inspection
Nikolov, I. A. & Madsen, C. B., 2017, Proceedings of the 12th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications.SCITEPRESS Digital Library
Benchmarking Close-range Structure from Motion 3D Reconstruction Software under Varying Capturing Conditions
Nikolov, I. A. & Madsen, C. B., 31 Oct 2016, 6th International Euro-Mediterranean Conference (EuroMed 2016).Springer, Vol. 10058 2016.
Datasets
GGG-BenchmarkSfM: Dataset for Benchmarking Close-range SfM Software Performance under Varying Capturing Condition
Nikolov, I. A. (Creator) & Madsen, C. B. (Creator), Mendeley Data, 12 Aug 2020
DOI: doi: 10.17632/bzxk2n78s9.4
GGG-BenchmarkSfM- Secondary: Secondary Dataset for Benchmarking Close-range SfM Software Performance Captured with Different Cameras
Nikolov, I. A. (Creator), Mendeley Data, 10 Aug 2020
DOI: 10.17632/t4d8mv3fxt.2
GGG-PositioningSfMScale: Dataset for Testing Scaling and Uncertainty Propagation Through Camera Positioning Data
Nikolov, I. A. (Creator) & Madsen, C. B. (Creator), Mendeley Data, 12 Aug 2020
DOI: 10.17632/24vt4rbpyx.3
Sandpaper Wind Turbine Blade Benchmark Dataset
Nikolov, I. A. (Creator), Schou Nielsen, M. (Creator), Kruse, E. K. (Creator), Garnæs, J. (Creator) & Madsen, C. B. (Creator), Mendeley Data, 10 Aug 2020
DOI: 10.17632/hcgcnm269w.2
Wind Turbine Blade Surfaces Dataset
Nikolov, I. A. (Creator), Schou Nielsen, M. (Contributor), Garnæs, J. (Supervisor) & Madsen, C. B. (Creator), Mendeley Data, 12 Aug 2020
DOI: 10.17632/jrmm82m4mv.2
GGG – Rough or Noisy? Metrics for Noise Detection in SfM Reconstructions
Nikolov, I. A. (Creator) & Madsen, C. B. (Creator), Mendeley Data, 6 Aug 2020
DOI: 10.17632/xtv5y29xvz.1
Wind Turbine Blade SfM Image Capturing Setups
Nikolov, I. A. (Creator) & Madsen, C. B. (Creator), Mendeley Data, 1 Sep 2020
DOI: 10.17632/fptxw8cynv.1
Funding
This project is funded by the Danish National EUDP programme.
Contact
PhD-Fellow: Ivan Adriyanov Nikolov
Mail: iani@create.aau.dk
Supervisor: Claus B. Madsen
Mail: cbm@create.aau.dk
