Automated UAV-based Wind Turbine Blade Inspection: Blade Stop Angle Estimation and Blade Detail Prioritized Exposure Adjustment
Fuente:
arXiv
Guardado en:
| Autores principales: | , , , , , , , |
|---|---|
| Formato: | Preprint |
| Publicado: |
2025
|
| Materias: | |
| Acceso en línea: | |
| Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
| _version_ | 1866916867803709440 |
|---|---|
| author | Shi, Yichuan Liu, Hao Zheng, Haowen Yu, Haowen Liang, Xianqi Li, Jie Ma, Minmin Lyu, Ximin |
| author_facet | Shi, Yichuan Liu, Hao Zheng, Haowen Yu, Haowen Liang, Xianqi Li, Jie Ma, Minmin Lyu, Ximin |
| contents | Unmanned aerial vehicles (UAVs) are critical in the automated inspection of wind turbine blades. Nevertheless, several issues persist in this domain. Firstly, existing inspection platforms encounter challenges in meeting the demands of automated inspection tasks and scenarios. Moreover, current blade stop angle estimation methods are vulnerable to environmental factors, restricting their robustness. Additionally, there is an absence of real-time blade detail prioritized exposure adjustment during capture, where lost details cannot be restored through post-optimization. To address these challenges, we introduce a platform and two approaches. Initially, a UAV inspection platform is presented to meet the automated inspection requirements. Subsequently, a Fermat point based blade stop angle estimation approach is introduced, achieving higher precision and success rates. Finally, we propose a blade detail prioritized exposure adjustment approach to ensure appropriate brightness and preserve details during image capture. Extensive tests, comprising over 120 flights across 10 wind turbine models in 5 operational wind farms, validate the effectiveness of the proposed approaches in enhancing inspection autonomy. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2507_04922 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Automated UAV-based Wind Turbine Blade Inspection: Blade Stop Angle Estimation and Blade Detail Prioritized Exposure Adjustment Shi, Yichuan Liu, Hao Zheng, Haowen Yu, Haowen Liang, Xianqi Li, Jie Ma, Minmin Lyu, Ximin Robotics Unmanned aerial vehicles (UAVs) are critical in the automated inspection of wind turbine blades. Nevertheless, several issues persist in this domain. Firstly, existing inspection platforms encounter challenges in meeting the demands of automated inspection tasks and scenarios. Moreover, current blade stop angle estimation methods are vulnerable to environmental factors, restricting their robustness. Additionally, there is an absence of real-time blade detail prioritized exposure adjustment during capture, where lost details cannot be restored through post-optimization. To address these challenges, we introduce a platform and two approaches. Initially, a UAV inspection platform is presented to meet the automated inspection requirements. Subsequently, a Fermat point based blade stop angle estimation approach is introduced, achieving higher precision and success rates. Finally, we propose a blade detail prioritized exposure adjustment approach to ensure appropriate brightness and preserve details during image capture. Extensive tests, comprising over 120 flights across 10 wind turbine models in 5 operational wind farms, validate the effectiveness of the proposed approaches in enhancing inspection autonomy. |
| title | Automated UAV-based Wind Turbine Blade Inspection: Blade Stop Angle Estimation and Blade Detail Prioritized Exposure Adjustment |
| topic | Robotics |
| url | https://arxiv.org/abs/2507.04922 |