Nowadays, automatic and reliable analysis of laser scanner measurement is important for tunnel structures. In this project, large-scale point cloud data is analyzed in order to monitor the health state of tunnel structures. Comparison is carried out on temporal geometry model and design model, from which the deformation assessment is achieved. In order to monitor the health state of structure, large-scale point cloud data is collected which supplies 3D information of the structure. Because quantitative deformation information is important to assess the safety of the structure, profiles are extracted from the point cloud data and compared. Comprehensive analysis are carried out on the profiles in different time periods and also including initial design model. Considering data gaps and disturbing points makes the task challenging to align profiles, feature points of the profiles are identified automatically for applying iterative closest point registration.