Intelligent segmentation method for blurred cracks and 3D mapping of width nephograms in concrete dams using UAV photogrammetry

被引:8
|
作者
Zhao, Sizeng [1 ]
Kang, Fei [2 ]
Li, Junjie [1 ,2 ]
机构
[1] Hohai Univ, Coll Water Conservancy & Hydropower Engn, Nanjing 210098, Peoples R China
[2] Dalian Univ Technol, Fac Infrastruct Engn, Sch Hydraul Engn, Dalian 116024, Peoples R China
基金
中国国家自然科学基金;
关键词
Computer vision; Concrete dam; Crack; Segmentation; 3D reconstruction; Structural health monitoring; Deep learning; Unmanned aerial vehicle;
D O I
10.1016/j.autcon.2023.105145
中图分类号
TU [建筑科学];
学科分类号
0813 ;
摘要
This study presents an innovative method for precise measurement and mapping of width nephograms for blurred cracks on concrete dams. An intelligent segmentation network called MPViT-Crack is proposed to accurately extract data from blurred crack pixels with complex backgrounds. A refined skeleton-based width nephogram calculation method is designed to quantify the scale of each crack. To convert pixel length into real distance, a technique for calculating spatial projection coordinates of the pixels in a single image using a 3D model is proposed. The proposed method enables intuitive visualization with real positions by mapping the crack width nephogram onto the 3D model. The effectiveness of the proposed method is validated using two experiments and a real concrete dam. The results demonstrate the accurate segmentation and measurement of blurred cracks, precise mapping of width nephograms to relative positions, and comprehensive visualization of crack sizes and distribution on the concrete dam.
引用
收藏
页数:19
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