3D RECONSTRUCTION OF ON-/OFFSHORE WIND TURBINES FOR MANUAL AND COMPUTATIONAL VISUAL INSPECTION
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...
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Format: | Article |
Language: | English |
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Copernicus Publications
2020-08-01
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Series: | The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences |
Online Access: | https://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XLIII-B2-2020/1121/2020/isprs-archives-XLIII-B2-2020-1121-2020.pdf |
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author | T. Möller D. Brün D. Langenkämper R. van Kevelaer T. W. Nattkemper |
author_facet | T. Möller D. Brün D. Langenkämper R. van Kevelaer T. W. Nattkemper |
author_sort | T. Möller |
collection | DOAJ |
description | 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%. |
first_indexed | 2024-12-14T22:42:04Z |
format | Article |
id | doaj.art-8bb7322360ad479a8ec1af3d38925e85 |
institution | Directory Open Access Journal |
issn | 1682-1750 2194-9034 |
language | English |
last_indexed | 2024-12-14T22:42:04Z |
publishDate | 2020-08-01 |
publisher | Copernicus Publications |
record_format | Article |
series | The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences |
spelling | doaj.art-8bb7322360ad479a8ec1af3d38925e852022-12-21T22:44:57ZengCopernicus PublicationsThe International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences1682-17502194-90342020-08-01XLIII-B2-20201121112710.5194/isprs-archives-XLIII-B2-2020-1121-20203D RECONSTRUCTION OF ON-/OFFSHORE WIND TURBINES FOR MANUAL AND COMPUTATIONAL VISUAL INSPECTIONT. Möller0D. Brün1D. Langenkämper2R. van Kevelaer3T. W. Nattkemper4Bielefeld University, Bielefed, Germanysaltation GmbH & Co. KG, Bielefeld, GermanyBielefeld University, Bielefed, GermanyBielefeld University, Bielefed, GermanyBielefeld University, Bielefed, GermanyThe 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%.https://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XLIII-B2-2020/1121/2020/isprs-archives-XLIII-B2-2020-1121-2020.pdf |
spellingShingle | T. Möller D. Brün D. Langenkämper R. van Kevelaer T. W. Nattkemper 3D RECONSTRUCTION OF ON-/OFFSHORE WIND TURBINES FOR MANUAL AND COMPUTATIONAL VISUAL INSPECTION The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences |
title | 3D RECONSTRUCTION OF ON-/OFFSHORE WIND TURBINES FOR MANUAL AND COMPUTATIONAL VISUAL INSPECTION |
title_full | 3D RECONSTRUCTION OF ON-/OFFSHORE WIND TURBINES FOR MANUAL AND COMPUTATIONAL VISUAL INSPECTION |
title_fullStr | 3D RECONSTRUCTION OF ON-/OFFSHORE WIND TURBINES FOR MANUAL AND COMPUTATIONAL VISUAL INSPECTION |
title_full_unstemmed | 3D RECONSTRUCTION OF ON-/OFFSHORE WIND TURBINES FOR MANUAL AND COMPUTATIONAL VISUAL INSPECTION |
title_short | 3D RECONSTRUCTION OF ON-/OFFSHORE WIND TURBINES FOR MANUAL AND COMPUTATIONAL VISUAL INSPECTION |
title_sort | 3d reconstruction of on offshore wind turbines for manual and computational visual inspection |
url | https://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XLIII-B2-2020/1121/2020/isprs-archives-XLIII-B2-2020-1121-2020.pdf |
work_keys_str_mv | AT tmoller 3dreconstructionofonoffshorewindturbinesformanualandcomputationalvisualinspection AT dbrun 3dreconstructionofonoffshorewindturbinesformanualandcomputationalvisualinspection AT dlangenkamper 3dreconstructionofonoffshorewindturbinesformanualandcomputationalvisualinspection AT rvankevelaer 3dreconstructionofonoffshorewindturbinesformanualandcomputationalvisualinspection AT twnattkemper 3dreconstructionofonoffshorewindturbinesformanualandcomputationalvisualinspection |