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Nhan đề: Image-Based Underwater Inspection System for Abrasion of Stilling Basin Slabs of Dam
Tác giả: Li, Yonglong
Zhang, Hua
Wang, Shuang
Wang, Haoran
Li, Jialong
Từ khoá: Machine learning
Deep learning
Artificial intelligence
Underwater robots
Quantitative analysis
Abrasion resistance
Hydroelectric power
Hydroelectric power stations
Civil engineering
Neural networks
Stilling basins
Năm xuất bản: 2019
Nhà xuất bản: Hindawi Limited
Tóm tắt: The abrasion of stilling basin slabs which is caused by waterborne particles is one of the main surface damages in the operation of hydropower station. For determining whether to repair the stilling basin slabs, periodic inspections of erosion condition of stilling basin slabs are required. The practical problem is how to get the underwater image without unwatering and how to analyse the abrasion though the images. This paper developed a novel underwater inspection system named UIS-1 which consists of a customized underwater robot and special quantitative analysis method for this situation. Firstly, the integrated component was designed for the underwater robot that partially removes the siltation and obtains the image of the concrete surface of stilling basin slabs in the desired position. Secondly, the paper proposed an image algorithm to obtain aggregate exposure ratio for quantitative abrasion analysis. This image algorithm used SLIC superpixel and the SVM machine learning method to detect the coarse aggregate exposure automatically. Then, the aggregate exposure ratio was calculated to analyse the degree of abrasion. Finally, the UIS-1 system was evaluated in the field experiments of a dam in Sichuan, China, and its performance was discussed by comparison.
Mô tả: "Hindawi; Advances in Civil Engineering; Volume 2019, Article ID 6924976, 13 pages;"
Định danh:
ISSN: 1687-8086
1687-8094 (eISSN)
Bộ sưu tập: Bài báo_lưu trữ

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