Estimation of Wind Turbine Blade Icing Volume Based on Binocular Vision
Icing on wind turbine blades in cold and humid weather has become a detrimental factor limiting their efficient operation, and traditional methods for detecting blade icing have various limitations. Therefore, this paper proposes a non-contact ice volume estimation method based on binocular vision a...
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| Format: | Article |
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MDPI AG
2024-12-01
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| Series: | Applied Sciences |
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| Online Access: | https://www.mdpi.com/2076-3417/15/1/114 |
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| author | Fangzheng Wei Zhiyong Guo Qiaoli Han Wenkai Qi |
| author_facet | Fangzheng Wei Zhiyong Guo Qiaoli Han Wenkai Qi |
| author_sort | Fangzheng Wei |
| collection | DOAJ |
| description | Icing on wind turbine blades in cold and humid weather has become a detrimental factor limiting their efficient operation, and traditional methods for detecting blade icing have various limitations. Therefore, this paper proposes a non-contact ice volume estimation method based on binocular vision and improved image processing algorithms. The method employs a stereo matching algorithm that combines dynamic windows, multi-feature fusion, and reordering, integrating gradient, color, and other information to generate matching costs. It utilizes a cross-based support region for cost aggregation and generates the final disparity map through a Winner-Take-All (WTA) strategy and multi-step optimization. Subsequently, combining image processing techniques and three-dimensional reconstruction methods, the geometric shape of the ice is modeled, and its volume is estimated using numerical integration methods. Experimental results on volume estimation show that for ice blocks with regular shapes, the errors between the measured and actual volumes are 5.28%, 8.35%, and 4.85%, respectively; for simulated icing on wind turbine blades, the errors are 5.06%, 6.45%, and 9.54%, respectively. The results indicate that the volume measurement errors under various conditions are all within 10%, meeting the experimental accuracy requirements for measuring the volume of ice accumulation on wind turbine blades. This method provides an accurate and efficient solution for detecting blade icing without the need to modify the blades, making it suitable for wind turbines already in operation. However, in practical applications, it may be necessary to consider the impact of illumination and environmental changes on visual measurements. |
| format | Article |
| id | doaj-art-ae61fc04bf5e404a980c26bf10d0850b |
| institution | Kabale University |
| issn | 2076-3417 |
| language | English |
| publishDate | 2024-12-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Applied Sciences |
| spelling | doaj-art-ae61fc04bf5e404a980c26bf10d0850b2025-01-10T13:14:29ZengMDPI AGApplied Sciences2076-34172024-12-0115111410.3390/app15010114Estimation of Wind Turbine Blade Icing Volume Based on Binocular VisionFangzheng Wei0Zhiyong Guo1Qiaoli Han2Wenkai Qi3College of Mechanical and Electrical Engineering, Inner Mongolia Agricultural University, Hohhot 010018, ChinaCollege of Mechanical and Electrical Engineering, Inner Mongolia Agricultural University, Hohhot 010018, ChinaCollege of Energy and Traffic Engineering, Inner Mongolia Agricultural University, Hohhot 010018, ChinaCollege of Mechanical and Electrical Engineering, Inner Mongolia Agricultural University, Hohhot 010018, ChinaIcing on wind turbine blades in cold and humid weather has become a detrimental factor limiting their efficient operation, and traditional methods for detecting blade icing have various limitations. Therefore, this paper proposes a non-contact ice volume estimation method based on binocular vision and improved image processing algorithms. The method employs a stereo matching algorithm that combines dynamic windows, multi-feature fusion, and reordering, integrating gradient, color, and other information to generate matching costs. It utilizes a cross-based support region for cost aggregation and generates the final disparity map through a Winner-Take-All (WTA) strategy and multi-step optimization. Subsequently, combining image processing techniques and three-dimensional reconstruction methods, the geometric shape of the ice is modeled, and its volume is estimated using numerical integration methods. Experimental results on volume estimation show that for ice blocks with regular shapes, the errors between the measured and actual volumes are 5.28%, 8.35%, and 4.85%, respectively; for simulated icing on wind turbine blades, the errors are 5.06%, 6.45%, and 9.54%, respectively. The results indicate that the volume measurement errors under various conditions are all within 10%, meeting the experimental accuracy requirements for measuring the volume of ice accumulation on wind turbine blades. This method provides an accurate and efficient solution for detecting blade icing without the need to modify the blades, making it suitable for wind turbines already in operation. However, in practical applications, it may be necessary to consider the impact of illumination and environmental changes on visual measurements.https://www.mdpi.com/2076-3417/15/1/114wind turbineblade icingbinocular visionstereo matchingvolume estimation |
| spellingShingle | Fangzheng Wei Zhiyong Guo Qiaoli Han Wenkai Qi Estimation of Wind Turbine Blade Icing Volume Based on Binocular Vision Applied Sciences wind turbine blade icing binocular vision stereo matching volume estimation |
| title | Estimation of Wind Turbine Blade Icing Volume Based on Binocular Vision |
| title_full | Estimation of Wind Turbine Blade Icing Volume Based on Binocular Vision |
| title_fullStr | Estimation of Wind Turbine Blade Icing Volume Based on Binocular Vision |
| title_full_unstemmed | Estimation of Wind Turbine Blade Icing Volume Based on Binocular Vision |
| title_short | Estimation of Wind Turbine Blade Icing Volume Based on Binocular Vision |
| title_sort | estimation of wind turbine blade icing volume based on binocular vision |
| topic | wind turbine blade icing binocular vision stereo matching volume estimation |
| url | https://www.mdpi.com/2076-3417/15/1/114 |
| work_keys_str_mv | AT fangzhengwei estimationofwindturbinebladeicingvolumebasedonbinocularvision AT zhiyongguo estimationofwindturbinebladeicingvolumebasedonbinocularvision AT qiaolihan estimationofwindturbinebladeicingvolumebasedonbinocularvision AT wenkaiqi estimationofwindturbinebladeicingvolumebasedonbinocularvision |