Development of a modeling method for monitoring tunnel deformation based on active panoramic vision technique

Yiping Tang; Gongping Yuan; Qi Chen; Guodong Han; Kegang Hu

doi:10.3969/j.issn.1003-501X.2017.04.009

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Yiping Tang, Gongping Yuan, Qi Chen, et al. Development of a modeling method for monitoring tunnel deformation based on active panoramic vision technique[J]. Opto-Electronic Engineering, 2017, 44(4): 442-452. doi: 10.3969/j.issn.1003-501X.2017.04.009

Citation:

Yiping Tang, Gongping Yuan, Qi Chen, et al. Development of a modeling method for monitoring tunnel deformation based on active panoramic vision technique[J]. Opto-Electronic Engineering, 2017, 44(4): 442-452. doi: 10.3969/j.issn.1003-501X.2017.04.009

Development of a modeling method for monitoring tunnel deformation based on active panoramic vision technique

Information Engineering College, Zhejiang University of Technology, Hangzhou 310023, China

More Information

Corresponding author: Yiping Tang, E-mail: typ@zjut.edu.cn

Received Date 04 January 2017

Revised Date 24 February 2017

Published Date 15 April 2017

Abstract

Abstract

Aiming at the characteristics of long-distance tunnel, long maintenance intervals, limited repairing time and small changes in the deformation data, this paper presents a detection method of tunnel deformation based on active omni-directional vision tunnel section deformation. Firstly, the active panoramic vision sensor (ASODVS) is installed at the tunnel and detecting device scans the cross section of tunnel to acquire tunnel section panoramic images. Secondly, the sub-pixel center of the panoramic image is extracted by the improved Gauss curve fitting method, and the smooth processing is performed by using the Bezier curves. Thirdly, the system analyzes the geometry information of the tunnel cross-section of the inner wall through calibration results of omnidirectional vision sensor. The tunnel cross section 3D point cloud data are used for 3D reconstruction. Finally, the precision of the tunnel reconstruction model is analyzed. The experimental results show the method has the advantages of high speed acquisition, real-time, comprehensive data and good visualization. It can meet the needs of the rapid qualitative and quantitative analyses.
- tunnel deformation monitoring /
- tunnel cross section /
- tunnel 3D reconstruction /
- active panorama vision /
- sub-pixel

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References

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Overview

Overview

Abstract: The tunnel is a civil engineering structure and the product for the human breaking through the boundaries of the natural environment, to improve the utilization of underground space and the traffic conditions. In 1970, the Organisation for Economic Co-operation and Development held a tunnel meeting that, after synthesizing the various factors, defined the tunnel as follows: "In some applications, under the ground in any way, shape and the size of cross-sectional area is larger than 2 square metres according to regulations".
As tunnel is an important part of the transport facility, it is necessary to inspect and keep the tunnel system in good condition periodically. The main rock mass structure appears varying degrees in different parts of deformation and significantly lower than design life due to the technology limitations and force majeure during the tunnel construction and its operation. The tunnel health problems impact the path transportation security. How to detect the tunnel deformation quickly becomes the urgent problem to be solved. Most of the existing non-machine vision detection methods have the disadvantages of large measurement errors, long time, less-automated and susceptibility to the surrounding environment. There are some shortcomings of machine vision detection method, such as high cost, large number of images acquisition, complicated data processing and poor real-time performance.
Aiming at the above problems and the characteristics of long-distance tunnel, long maintenance intervals, limited repairing time, and small changes in the deformation data, this paper designs and implements the modeling method for monitoring tunnel deformation based on active stereo-omnidirectional vision sensor. Firstly, the active panoramic vision sensor (ASODVS) which is composed of omni-directional vision sensor (ODVS) and circular laser light source is installed at the tunnel detecting device scanning the cross section of tunnel to acquire tunnel section panoramic images. Secondly, the sub-pixel center of the panoramic image is extracted by the improved Gauss curve fitting method, and the smooth processing is performed by using the Bezier curves. Thirdly, the system analyzes the geometry information of the tunnel cross-section of the inner wall through calibration results of omnidirectional vision sensor. The tunnel cross section 3D point cloud data are used for 3D reconstruction. Finally, the precision of the tunnel reconstruction model is analyzed. The experimental results show the method has the advantages of high speed acquisition, real-time, comprehensive data and good visualization. It can meet the needs of the rapid qualitative and quantitative analyses.