Automatic Sensing and Detection for Subway Tunnel Pathologies
作者机构：School of Geomatics and Urban Spatial InformaticsBeijing University of Civil Engineering and ArchitectureBeijing 102616China
出 版 物：《Journal of World Architecture》 (世界建筑（百图）)
年 卷 期：2024年第8卷第1期
页 面：54-62页
学科分类：08[工学] 0812[工学-计算机科学与技术（可授工学、理学学位）]
主 题：Visual detection Neural network Health monitoring Image segmentation Water leakage Subway tunnel.
摘 要：Subway tunnels often suffer from surface pathologies such as cracks,corrosion,fractures,peeling,water and sand infiltration,and sudden hazards caused by foreign object *** a mobile visual pathology sensing system at the front end of operating trains is a critical measure to ensure subway *** leakage as the typical pathology,a tunnel pathology automatic visual detection method based on Deeplabv3+(ASTPDS)was proposed to achieve automatic and high-precision detection and pixel-level morphology extraction of *** with similar methods,this approach showed significant advantages and achieved a detection accuracy of 93.12%,surpassing FCN and ***,it also exceeded the recall rates for detecting leaks of FCN and U-Net by 8.33%and 8.19%,respectively.
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