Non-contact strain measurement for laterally loaded steel plate using LiDAR point cloud displacement data

Abstract

Strain measurement in structures provides key information for structural health monitoring (SHM); therefore, researchers have developed various sensing methods for measuring strain in structures. Recently, light detection and ranging (LiDAR) has been studied as a non-contact strain measurement method (NCSMM). LiDAR is a technology for remotely acquiring high precision three-dimensional (3D) coordinate information for a terrain or a structure using a 3D laser scanning system. In recent years, LiDAR applications have expanded to include systems used to monitor structural behavior. Using this technology, structural behavior can be monitored without directly attaching sensors to the surfaces of target structures. It is advantageous to use non-contact 3D laser scanning measuring methods to obtain the 3D coordinates of a specific region or the shape of the target structures. LiDAR technology does not have some of the limitations associated with existing types of measuring sensors used for SHM. Therefore, in this study, we will present a method for estimating deformation and strains for a whole structure by measuring discretized 3D coordinate data of the target structure obtained from the LiDAR. The 3D coordinate data was revised using a regression analysis, and the strain was estimated by developing a finite element model based on the corrected 3D coordinate information. The experimental structural model is a steel plate, which is the primary material used for the outer wall construction of LNG storage tanks. The estimated strains will be compared to the measured values from real strain gauges, and the applicability of the proposed strain measurement method to structural behavior monitoring will be verified.