Lidar-based Tunnel Wet Spray State Perception Method

In the construction of tunnel lining,the wet spraying machine is mainly operated by workers with remote control,but there are disadvantages such as high labor intensity,low efficiency,and difficulty in guaranteeing the quality of wet spraying.In order to promote the intelligent of wet spraying operation and improve the wet spraying quality,it is very important to realize the state perception of the wet spray process.Lidar can accurately obtain the three-dimensional spatial information of the target,which can be used for three-dimensional reconstruction.A Li DAR-based tunnel wet spray state perception method is proposed in this thesis,which completes the fast and effective surface reconstruction of the wet spray operation area,accurately analyzes the wet spray state of the area to be measured,and solves the following problems in the process of wet spray intelligent operation:(1)Aiming at the problem that it is difficult to accurately describe the outline of the tunnel in the wet spray process,a feature point extraction method based on data standardization is proposed.Combined with Mestimator sample consensus algorithm and piecewise cubic Hermite interpolating polynomial algorithm,an adaptive point cloud data standardization processing method is proposed to solve the problem of different attitudes and missing data of tunnel point cloud.Based on GaussNewton iterative algorithm,segmental Lame curve fitting is performed on the inner contour of the tunnel,and the tunnel feature points are extracted to mark the key positions of the tunnel.(2)Aiming at the problem of large space surface reconstruction in wet spray process,a 3D reconstruction algorithm of tunnel area based on feature points growing algorithm is proposed.The iterative closest point algorithm is improved with the tunnel feature points to better the registration of multi-frame point clouds and solve the problem of insufficient data of single-frame point clouds.According to the characteristics of tunnel wet spray,an improved region growing algorithm is used to divide the tunnel into eight uniform regions for 3D reconstruction.Experiments show that the proposed algorithm achieves high-quality modeling of the wet spray area of the tunnel,whose triangular mesh model performs better than the traditional Delaunay algorithm in various indicators.(3)Aiming at the problem of the real-time monitoring in wet spraying process,quality evaluation indicators such as the concave-convex and the roughness of the tunnel surface are introduced.The area to be wet sprayed is identified by comparing the surface concave-convex between the regional triangular mesh models,and a triangular prism is used to approximate the amount of concrete to be wet sprayed in this area.When evaluating the quality of tunnel wet spray,a cylindrical projection and expansion method is proposed to evaluate the surface roughness of the tunnel wall.Experiments show that the quality assessment conclusion obtained by the proposed tunnel wet spray quality assessment method in this paper is consistent with that obtained by manual work.