Research progress of machine vision based disease detecting techniques for the tunnel lining surface

被引:0
|
作者
Huang, Hongwei [1 ,2 ]
Sun, Yan [1 ]
Xue, Yadong [1 ,2 ]
机构
[1] Department of Geotechnical Engineering, Tongji University, Shanghai, China
[2] Key Laboratory of Geotechnical Engineering, Tongji University, Shanghai, China
关键词
Computer vision - Surface analysis - Crack detection - Laser applications - Tunnel linings;
D O I
10.13807/j.cnki.mtt.2014.S1.003
中图分类号
学科分类号
摘要
Maintenances for the completed tunnels have been increasingly become an important part of tunnels' safe operation, and its key point is the surface detection of tunnel lining in the stage of maintenance, including the detection of crack and water leakage. This paper presents a detailed discussion on two detection techniques based on machine vision, i. e. the tunnel detection techniques separately based on the camera technique and the laser scanning. According to the progress in tunnel detecting techniques in various countries, it is presented that the key points of disease detection for the surface of tunnel lining are the applicability of detecting method, detecting speed, detection precision and the post processing method etc. By comparison of the advantages and disadvantages and the distinction of both methods used for tunnel detection, it is found that each of them has its own features in detection of tunnel lining surface; therefore, it is essential to select the appropriate detection method in specific detecting environment and optimize both methods in practice. ©, 2015, Editorial Office of Modern Tunnelling Technology. All right reserved.
引用
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页码:19 / 31
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