Dynamic Characteristics Monitoring of Large Wind Turbine Blades Based on Target-Free DSST Vision Algorithm and UAV
The structural condition of blades is mainly evaluated using manual inspection methods. However, these methods are time-consuming, labor-intensive, and costly, and the detection results significantly depend on the experience of inspectors, often resulting in lower precision. Focusing on the dynamic...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2022-06-01
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| Series: | Remote Sensing |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2072-4292/14/13/3113 |
| _version_ | 1797408219594752000 |
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| author | Wanrun Li Wenhai Zhao Jiaze Gu Boyuan Fan Yongfeng Du |
| author_facet | Wanrun Li Wenhai Zhao Jiaze Gu Boyuan Fan Yongfeng Du |
| author_sort | Wanrun Li |
| collection | DOAJ |
| description | The structural condition of blades is mainly evaluated using manual inspection methods. However, these methods are time-consuming, labor-intensive, and costly, and the detection results significantly depend on the experience of inspectors, often resulting in lower precision. Focusing on the dynamic characteristics (i.e., natural frequencies) of large wind turbine blades, this study proposes a monitoring method based on the target-free DSST (Discriminative Scale Space Tracker) vision algorithm and UAV. First, the displacement drift of UAV during hovering is studied. Accordingly, a displacement compensation method based on high-pass filtering is proposed herein, and the scale factor is adaptive. Then, the machine learning is employed to map the position and scale filters of the DSST algorithm to highlight the features of the target image. Subsequently, a target-free DSST vision algorithm is proposed, in which illumination changes and complex backgrounds are considered. Additionally, the algorithm is verified using traditional computer vision algorithms. Finally, the UAV and the target-free DSST vision algorithm are used to extract the dynamic characteristic of the wind turbine blades under shutdown. Results show that the proposed method can accurately identify the dynamic characteristics of the wind turbine blade. This study can serve as a reference for assessment of the condition of wind turbine blades. |
| first_indexed | 2024-03-09T03:55:15Z |
| format | Article |
| id | doaj.art-16ef5313ab4c448abb2021be67d759f8 |
| institution | Directory Open Access Journal |
| issn | 2072-4292 |
| language | English |
| last_indexed | 2024-03-09T03:55:15Z |
| publishDate | 2022-06-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Remote Sensing |
| spelling | doaj.art-16ef5313ab4c448abb2021be67d759f82023-12-03T14:20:37ZengMDPI AGRemote Sensing2072-42922022-06-011413311310.3390/rs14133113Dynamic Characteristics Monitoring of Large Wind Turbine Blades Based on Target-Free DSST Vision Algorithm and UAVWanrun Li0Wenhai Zhao1Jiaze Gu2Boyuan Fan3Yongfeng Du4Institution of Earthquake Protection and Disaster Mitigation, Lanzhou University of Technology, Lanzhou 733050, ChinaInstitution of Earthquake Protection and Disaster Mitigation, Lanzhou University of Technology, Lanzhou 733050, ChinaSchool of Computer and Communication, Lanzhou University of Technology, Lanzhou 733050, ChinaInstitution of Earthquake Protection and Disaster Mitigation, Lanzhou University of Technology, Lanzhou 733050, ChinaInstitution of Earthquake Protection and Disaster Mitigation, Lanzhou University of Technology, Lanzhou 733050, ChinaThe structural condition of blades is mainly evaluated using manual inspection methods. However, these methods are time-consuming, labor-intensive, and costly, and the detection results significantly depend on the experience of inspectors, often resulting in lower precision. Focusing on the dynamic characteristics (i.e., natural frequencies) of large wind turbine blades, this study proposes a monitoring method based on the target-free DSST (Discriminative Scale Space Tracker) vision algorithm and UAV. First, the displacement drift of UAV during hovering is studied. Accordingly, a displacement compensation method based on high-pass filtering is proposed herein, and the scale factor is adaptive. Then, the machine learning is employed to map the position and scale filters of the DSST algorithm to highlight the features of the target image. Subsequently, a target-free DSST vision algorithm is proposed, in which illumination changes and complex backgrounds are considered. Additionally, the algorithm is verified using traditional computer vision algorithms. Finally, the UAV and the target-free DSST vision algorithm are used to extract the dynamic characteristic of the wind turbine blades under shutdown. Results show that the proposed method can accurately identify the dynamic characteristics of the wind turbine blade. This study can serve as a reference for assessment of the condition of wind turbine blades.https://www.mdpi.com/2072-4292/14/13/3113structural health monitoringlarge wind turbine bladesUAVtarget-freeDSST vision algorithm |
| spellingShingle | Wanrun Li Wenhai Zhao Jiaze Gu Boyuan Fan Yongfeng Du Dynamic Characteristics Monitoring of Large Wind Turbine Blades Based on Target-Free DSST Vision Algorithm and UAV Remote Sensing structural health monitoring large wind turbine blades UAV target-free DSST vision algorithm |
| title | Dynamic Characteristics Monitoring of Large Wind Turbine Blades Based on Target-Free DSST Vision Algorithm and UAV |
| title_full | Dynamic Characteristics Monitoring of Large Wind Turbine Blades Based on Target-Free DSST Vision Algorithm and UAV |
| title_fullStr | Dynamic Characteristics Monitoring of Large Wind Turbine Blades Based on Target-Free DSST Vision Algorithm and UAV |
| title_full_unstemmed | Dynamic Characteristics Monitoring of Large Wind Turbine Blades Based on Target-Free DSST Vision Algorithm and UAV |
| title_short | Dynamic Characteristics Monitoring of Large Wind Turbine Blades Based on Target-Free DSST Vision Algorithm and UAV |
| title_sort | dynamic characteristics monitoring of large wind turbine blades based on target free dsst vision algorithm and uav |
| topic | structural health monitoring large wind turbine blades UAV target-free DSST vision algorithm |
| url | https://www.mdpi.com/2072-4292/14/13/3113 |
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