Vui lòng dùng định danh này để trích dẫn hoặc liên kết đến tài liệu này: http://thuvienso.vanlanguni.edu.vn/handle/Vanlang_TV/18611
Toàn bộ biểu ghi siêu dữ liệu
Trường DCGiá trị Ngôn ngữ
dc.contributor.authorLi, Yonglong-
dc.contributor.authorZhang, Hua-
dc.contributor.authorWang, Shuang-
dc.contributor.authorWang, Haoran-
dc.contributor.authorLi, Jialong-
dc.date.accessioned2020-06-01T02:07:50Z-
dc.date.available2020-06-01T02:07:50Z-
dc.date.issued2019-
dc.identifier.issn1687-8086-
dc.identifier.issn1687-8094 (eISSN)-
dc.identifier.otherBBKH1286-
dc.identifier.urihttp://thuvienso.vanlanguni.edu.vn/handle/Vanlang_TV/18611-
dc.description"Hindawi; Advances in Civil Engineering; Volume 2019, Article ID 6924976, 13 pages; https://doi.org/10.1155/2019/6924976"vi
dc.description.abstractThe 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.vi
dc.language.isoenvi
dc.publisherHindawi Limitedvi
dc.subjectMachine learningvi
dc.subjectDeep learningvi
dc.subjectArtificial intelligencevi
dc.subjectConcretevi
dc.subjectAggregatesvi
dc.subjectRobotsvi
dc.subjectUnderwater robotsvi
dc.subjectCracksvi
dc.subjectClusteringvi
dc.subjectSlabsvi
dc.subjectQuantitative analysisvi
dc.subjectAbrasion resistancevi
dc.subjectHydroelectric powervi
dc.subjectInspectionvi
dc.subjectHydroelectric power stationsvi
dc.subjectCivil engineeringvi
dc.subjectNeural networksvi
dc.subjectAlgorithmsvi
dc.subjectImagesvi
dc.subjectAbrasionvi
dc.subjectInfrastructurevi
dc.subjectStilling basinsvi
dc.subjectHydraulicsvi
dc.titleImage-Based Underwater Inspection System for Abrasion of Stilling Basin Slabs of Damvi
dc.typeOthervi
Bộ sưu tập: Bài báo_lưu trữ

Các tập tin trong tài liệu này:
Tập tin Mô tả Kích thước Định dạng  
BBKH1286_TCCN_Image-Based Underwater Inspection.pdf
  Giới hạn truy cập
Image-Based Underwater Inspection System for Abrasion of Stilling Basin Slabs of Dam7.04 MBAdobe PDFXem/Tải về  Yêu cầu tài liệu


Khi sử dụng các tài liệu trong Thư viện số phải tuân thủ Luật bản quyền.