Tunnel Crack and Seepage Detection in Multi-scale Space

被引：0
|
作者：
Jia D. [1 ]
Zhang W. [1 ]
Liu Y. [2 ]
机构：
[1] College of Civil Engineering, Tongji University, Shanghai
[2] Tongji Zhejiang College, Jiaxing
来源：
Tongji Daxue Xuebao/Journal of Tongji University | 2019年 / 47卷 / 12期
关键词：
Crack detection; Multi-scale space; Point cloud image; Seepage area;
D O I：
10.11908/j.issn.0253-374x.2019.12.019
中图分类号：
学科分类号：
摘要：
Based on the image of point cloud, a detection algorithm for cracks and water seepage area identification in multi-scale space is proposed. According to the physical features of tunnel cracks in different scale, meanwhile, with the definition of scale space, a fusion image detection operator is developed to maintain the stability of ribbon like cracks detection, at the same time, to restore the sensitivity to the small cracks in high gray value for obtaining more edge pixels. Therefore, the identification and detection of multi-scale cracks and seepage are achieved with the application of proposed algorithm. It is proved by an example that the algorithm can effectively eliminate the interference of fake cracks, and accurately identify and locate cracks in different scales. © 2019, Editorial Department of Journal of Tongji University. All right reserved.
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页码：1825 / 1830
页数：5
相关论文
共 15 条
  • [1] Xiao S., New developing direction of tunnel survey technology-application of tunnel scanning technology in completion survey of Nuremberg-Ingostadt high speed railway in germany, International Technical Exchange Conference on China High Speed Railway Tunnel, pp. 653-657, (2006)
  • [2] Tie X., Tunnel lining inspection vhicle in Japan, Modern Urban Rail Transit, 3, 2, (2012)
  • [3] Siriphan J., Development of a new digital pavement image processing algorithm for unified crack index computation, (1997)
  • [4] Muduli P.R., Pati U.C., A novel technique for wall crack detection using image fusion, International Conference on Computer Communication and Liformtics (ICCCI), pp. 1-6, (2013)
  • [5] Sunil K., Paul W., Automated detection of cracks in buried concrete pipe images, Automation in Construction, 15, 1, (2006)
  • [6] Hatada T., Saitoh R., Crack detection method for drain by using directional smoothing, IEEE Trans.EIS, 127, 2, (2007)
  • [7] Kovesi P., Phase congruency: a low level image invariant, Psychological Research, 2, 64, (2000)
  • [8] Wang P., Huang H., Xue Y., Automatic recognition of cracks in tunnel lining based on characteristics of local grids in images, Chinese Journal of Rock Mechanics and Engineering, 31, 5, (2012)
  • [9] Shen Y., Image detection of tunnel cracks based on NSCT, Urban Roads Bridges & Flood Control, 10, 10, (2013)
  • [10] Ding R., Liu H., Application of distributed optical fiber sensing technique to detection of cracks in concrete, Journal of Southwest Jiaotong University(Natural Science), 38, 6, (2003)
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