| Issue |
E3S Web Conf.
Volume 118, 2019
2019 4th International Conference on Advances in Energy and Environment Research (ICAEER 2019)
|
|
|---|---|---|
| Article Number | 02041 | |
| Number of page(s) | 4 | |
| Section | Energy Equipment and Application | |
| DOI | https://doi.org/10.1051/e3sconf/201911802041 | |
| Published online | 04 October 2019 | |
Study on wind turbine blade defect detection system based on imaging array
Huadian Electric Power Research Institute Co., Ltd., Hangzhou, China
Currently in the process of wind farm inspection, wind turbine blade appearance inspection mainly adopts the telescope or high-definition cameras, low detection efficiency, labor intensity and the precision is limited, in order to solve this problem, a kind of wind turbine blades defect recognition system based on image array is proposed. Through the joint of array camera and image processing server, the functions of the image acquisition, processing, and defect recognition and detection results output are implemented. The software of artificial intelligence deep learning based on neural network algorithm is used to identify the defects of blade image, and output quality analysis report, to realize automatic detection of wind turbine blade surface defect. The field measurement results show that the system greatly improves the efficiency and accuracy of wind turbine blade defect detection.
© The Authors, published by EDP Sciences, 2019
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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