No abstract

In recent years, 3D laser scanning technology has been applied to tunnel engineering. Although more intelligent than traditional measurement technology, it is still challenging to estimate the real-time deformation of NATM tunnel excavation from laser detection and ranging point clouds. To further improve the measurement accuracy of 3D laser scanning technology in the tunnel construction process, this paper proposes an improved Kriging filtering algorithm. Considering the spatial correlation of the described object, the optimization method of point cloud grid filtering is studied. By analyzing the full-space deformation field of the tunnel lining, the deformation information of the measuring points on the surface of the tunnel lining is extracted. Based on the actual project, through the on-site monitoring comparison test, the three-dimensional laser point cloud data are grid processed and analyzed, and the deformation data obtained from the test are compared with the data measured by traditional methods. The experimental results show that the Kriging filtering algorithm can not only efficiently identify and extract the tunnel profile visualization data but also efficiently and accurately obtain the tunnel deformation. The measurement results obtained by using the proposed technology are in good agreement with those obtained by using traditional monitoring methods. Therefore, tunnel deformation monitoring based on 3D laser scanning technology can better reflect the evolution of the tunnel full-space deformation field under certain environmental conditions and can provide an effective safety warning for tunnel construction.

No abstract

The concrete thickness of the tunnel lining structure and cover depth is insufficient. Such condition seriously affects the safety and stability of the lining structure. The lining structure thickness is difficult to identify using radar profile horizon tracing method because of the strong interference of steel bars to electromagnetic wave propagation. To explore the reflection characteristics of electromagnetic wave signals at the interface between deep concrete and surrounding rock, a time-energy density analysis based on wavelet transform (TEDAWT) was proposed in this study. Ground-penetrating radar (GPR) forward modelling of the lining structure with different thicknesses of plain and reinforced concrete was carried out by using different central frequencies, namely, 1600 and 900 MHz, respectively. On this basis, the GPR detection signals for the plain and reinforced concrete lining structures were analyzed by employing the TEDAWT method. The feasibility of the TEDAWT method in GPR quantitative identification was verified using physical experiment. Results demonstrate that the identification accuracy of different thicknesses of plain and reinforced concrete structure is high regardless of the method used in either forward modelling or physical experiment, and the relative error is less than 5%. In the identification of concrete cover depth, the resolution of a 1600 MHz antenna is higher than that of a 900 MHz antenna, and the relative error is also less than 5%. The results indicate the application potential of the proposed method for quantitative identification of tunnel lining thickness by non-destructive testing. The proposed method provides not only the thickness distribution of the plain concrete structure but also the distribution of the reinforced concrete structure and concrete cover depth compared with traditional radar profile horizon tracing method.