Automatic Detection of Shield Tunnel Leakages Based on Terrestrial Mobile LiDAR Intensity Images Using Deep Learning

Water leakages are very important signals that characterize the serious potential structural damages or flaws in shield tunnels. Automatic, timely, and accurate detection of water leakages is of great significance to the safe operation and maintenance for shield tunnels. However, existing methods (e...

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Veröffentlicht in:	IEEE access 2021, Vol.9, p.55300-55310
Hauptverfasser:	Cheng, Xiaolong, Hu, Xuhang, Tan, Kai, Wang, Lingwen, Yang, Lingjing
Format:	Artikel
Sprache:	eng
Schlagworte:	Cables Confined spaces Convolution Deep learning Flaw detection fully convolutional network Image segmentation intensity images Laser radar Leakage leakage detection Lidar LiDAR intensity correction Luminous intensity Reflectivity Semantics shield tunnels Structural damage Three-dimensional displays Tunnel construction Tunneling shields
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