Articles | Volume 3, issue 2
https://doi.org/10.5194/wes-3-639-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/wes-3-639-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Remote surface damage detection on rotor blades of operating wind turbines by means of infrared thermography
Dominik Traphan
CORRESPONDING AUTHOR
ForWind, Institute of Physics, University of Oldenburg, Oldenburg, Germany
Iván Herráez
Department of Technology, University of Applied Sciences Emden/Leer, Emden, Germany
Peter Meinlschmidt
Fraunhofer Institute for Wood Research, Wilhelm-Klauditz-Institut WKI, Braunschweig, Germany
Friedrich Schlüter
Fraunhofer Institute for Wood Research, Wilhelm-Klauditz-Institut WKI, Braunschweig, Germany
Joachim Peinke
ForWind, Institute of Physics, University of Oldenburg, Oldenburg, Germany
Gerd Gülker
ForWind, Institute of Physics, University of Oldenburg, Oldenburg, Germany
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Cited
14 citations as recorded by crossref.
- Weather-dependent passive thermography and thermal simulation of in-service wind turbine blades S. Chaudhuri et al. 10.1088/1742-6596/2507/1/012025
- Enhanced Non-Destructive Testing of Small Wind Turbine Blades Using Infrared Thermography M. Memari et al. 10.3390/machines13020108
- Flow visualization by means of 3D thermography on yawing wind turbines A. Fischer et al. 10.3389/fenrg.2023.1240183
- An Improved YOLOv7 Model for Surface Damage Detection on Wind Turbine Blades Based on Low-Quality UAV Images Y. Liao et al. 10.3390/drones8090436
- A Comprehensive Review on Signal-Based and Model-Based Condition Monitoring of Wind Turbines: Fault Diagnosis and Lifetime Prognosis H. Badihi et al. 10.1109/JPROC.2022.3171691
- Atmospheric Drivers of Wind Turbine Blade Leading Edge Erosion: Review and Recommendations for Future Research S. Pryor et al. 10.3390/en15228553
- AQUADA PLUS: Automated damage inspection of cyclic-loaded large-scale composite structures using thermal imagery and computer vision X. Chen et al. 10.1016/j.compstruct.2023.117085
- Prioritizing Research for Enhancing the Technology Readiness Level of Wind Turbine Blade Leading-Edge Erosion Solutions S. Pryor et al. 10.3390/en17246285
- Automated Detection of Premature Flow Transitions on Wind Turbine Blades Using Model-Based Algorithms A. Parrey et al. 10.3390/app11188700
- IR thermographic flow visualization for the quantification of boundary layer flow disturbances due to the leading edge condition C. Dollinger et al. 10.1016/j.renene.2019.01.116
- WRF Modeling of Deep Convection and Hail for Wind Power Applications F. Letson et al. 10.1175/JAMC-D-20-0033.1
- Detection of erosion damage on airfoils by means of thermographic flow visualization F. Jensen et al. 10.1016/j.euromechflu.2023.12.004
- Radar-derived precipitation climatology for wind turbine blade leading edge erosion F. Letson et al. 10.5194/wes-5-331-2020
- LiDAR‐based automated UAV inspection of wind turbine rotor blades C. Castelar Wembers et al. 10.1002/rob.22309
14 citations as recorded by crossref.
- Weather-dependent passive thermography and thermal simulation of in-service wind turbine blades S. Chaudhuri et al. 10.1088/1742-6596/2507/1/012025
- Enhanced Non-Destructive Testing of Small Wind Turbine Blades Using Infrared Thermography M. Memari et al. 10.3390/machines13020108
- Flow visualization by means of 3D thermography on yawing wind turbines A. Fischer et al. 10.3389/fenrg.2023.1240183
- An Improved YOLOv7 Model for Surface Damage Detection on Wind Turbine Blades Based on Low-Quality UAV Images Y. Liao et al. 10.3390/drones8090436
- A Comprehensive Review on Signal-Based and Model-Based Condition Monitoring of Wind Turbines: Fault Diagnosis and Lifetime Prognosis H. Badihi et al. 10.1109/JPROC.2022.3171691
- Atmospheric Drivers of Wind Turbine Blade Leading Edge Erosion: Review and Recommendations for Future Research S. Pryor et al. 10.3390/en15228553
- AQUADA PLUS: Automated damage inspection of cyclic-loaded large-scale composite structures using thermal imagery and computer vision X. Chen et al. 10.1016/j.compstruct.2023.117085
- Prioritizing Research for Enhancing the Technology Readiness Level of Wind Turbine Blade Leading-Edge Erosion Solutions S. Pryor et al. 10.3390/en17246285
- Automated Detection of Premature Flow Transitions on Wind Turbine Blades Using Model-Based Algorithms A. Parrey et al. 10.3390/app11188700
- IR thermographic flow visualization for the quantification of boundary layer flow disturbances due to the leading edge condition C. Dollinger et al. 10.1016/j.renene.2019.01.116
- WRF Modeling of Deep Convection and Hail for Wind Power Applications F. Letson et al. 10.1175/JAMC-D-20-0033.1
- Detection of erosion damage on airfoils by means of thermographic flow visualization F. Jensen et al. 10.1016/j.euromechflu.2023.12.004
- Radar-derived precipitation climatology for wind turbine blade leading edge erosion F. Letson et al. 10.5194/wes-5-331-2020
- LiDAR‐based automated UAV inspection of wind turbine rotor blades C. Castelar Wembers et al. 10.1002/rob.22309
Latest update: 09 Mar 2025
Short summary
Wind turbines are exposed to harsh weather, leading to surface defects on rotor blades emerging from the first day of operation. Defects
grow quickly and affect the performance of wind turbines. Thus, there is demand for an easily applicable remote-inspection method that is sensitive to small
surface defects. In this work we show that infrared thermography can meet these requirements by visualizing differences in the surface temperature
of the rotor blades downstream of surface defects.
Wind turbines are exposed to harsh weather, leading to surface defects on rotor blades emerging...
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