Open AccessDeformation monitoring of similar material model based on point cloud feature extraction
Author(s) -
Zhou Baoxing,
Shan Yuhui,
Yao Shoufeng
Publication year - 2019
Publication title -
the journal of engineering
Language(s) - English
Resource type - Journals
ISSN - 2051-3305
DOI - 10.1049/joe.2019.0516
Subject(s) - deformation (meteorology) , extraction (chemistry) , point cloud , cloud computing , computer science , deformation monitoring , feature extraction , feature (linguistics) , point (geometry) , artificial intelligence , materials science , composite material , geometry , chromatography , mathematics , chemistry , operating system , linguistics , philosophy
Three‐dimensional (3D) laser scanning technology can reconstruct target models and analyse structural characteristics, and extract complex geometric contents of target structures. Therefore, it is significant to apply 3D laser scanning technology to construct 3D digital models of the monitored objects and to extract their features to judge their movements. This paper presents deformation monitoring method of 3D point cloud based on image information. First, point cloud was first converted into a two‐dimensional intensity image. Topological relations between each point can be determined clearly through the intensity image. Second, based on the wavelet modulus maxima technology, the characteristics of two‐dimensional intensity images are extracted and the corresponding feature point cloud data are obtained. Finally, According to the feature of the point cloud extracted, the change is calculated to determine the deformation of the point cloud object. An experiment was conducted by using a FOCUS3D laser scanner of FARO. The experiment results further verify that the method yields a good effect of deformation monitoring.