Research on Deformation Analysis of Time-Varying Point Cloud

Abstract

For large-scale object or scene which needs high requirements of deformation detection, a comprehensive deformation analysis method is proposed based on the time-varying point cloud to perform continuous detection, to comprehensively analyze the deformation and to research its characteristics and rules. In order to improve computing efficiency, a BSP parallel algorithm based on deformation analysis of time-varying point cloud is designed according to BSP parallel computing technology, and the deformational data are handled by a HAMA computing cluster which is composed of common personal computers. Several computing results from both simulations and real cases have proved the feasibility and effectiveness of analyzing method and BSP analyzing algorithm of deformation of time-varying point cloud.

Full‐field deformation measurement by videogrammetry using self‐adaptive window matching

“…In the distributed parallel computing, GPU‐based image matching will also be considered to accelerate the processing speed (Zhi et al., ). Furthermore, more attention will be paid to the time‐series analysis of the sequential point clouds (Liu et al., ).…”

“…In the research field of non-contact deformation monitoring, some scholars have carried out research into the use of DIC in arithmetic improvement, accuracy assessment and application extension (Pan et al, 2009b;Liu et al, 2014;Zhang et al, 2015). In proposing the Newton-Raphson (NR) method of partial differential correction to determine displacements and gradients, Bruck et al (1989) laid the groundwork for optical measurement in the field of mechanics.…”