A 3D Image Reconstruction Model for Long Tunnel Geological Estimation

• Main Authors: Yongtao Liu, Jie Qiao, Tianyuan Han, Longhui Li, Ting Xu
• Format: Article
• Language: English
• Published: Hindawi-Wiley 2020-01-01
• Series: Journal of Advanced Transportation
• Online Access: http://dx.doi.org/10.1155/2020/8846955

Long tunnels often collapse during the construction period. To ensure personnel safety, the geological characteristics must be predicted before tunnel face excavation. In this study, the ground-penetrating radar (GPR) technique is introduced to obtain information regarding the tunnel excavation face at a certain interval. The amplitude of the radar echo signal is expressed as a function of the position and travel time. A B-scan strategy is selected for the GPR to obtain tunnel information. A frequency-domain (w-k) focusing algorithm, namely, a synthetic aperture radar focusing algorithm, is applied to focus scattered radar signals to obtain focused images. A low-pass filter is designed to remove noises from the original signals. The contours of target objects are extracted from the background information using the edge detection technique. Space coordinate values of the objects are converted to polar coordinates using the Hough transform algorithm for 3D modeling. Visual C++ and AutoCAD are combined to develop a 3D CAD model to help managers in controlling the construction process. The system creates 3D visualization model images and evaluates the geological characteristics of the tunnel excavation faces. The Taigu Tunnel located in the Shanxi Province of China is taken as a case study. A procedure for the geological analysis of this tunnel is introduced in detail, and a 3D image model is built. The results show that the 3D model can help predict rock compositions and locate potential hazards. Moreover, it has better accuracy than conventional models and can be applied to similar transportation construction projects.