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Optimized free-form surface modeling of point clouds from laser-based measurement.

Authors :
Xu, Xiangyang
Yang, Hao
Augello, Riccardo
Carrera, Erasmo
Source :
Mechanics of Advanced Materials & Structures. 2021, Vol. 28 Issue 15, p1570-1578. 9p.
Publication Year :
2021

Abstract

Freeform parameterizations to reproduce structure deformation are increasingly important topics in laser-scanner-based deformation analyses. High-accuracy assurance of free-form surface approximation is extremely critical for reliable deformation analysis. One main challenge in this field is the model selection. Improper model complexity could result in under-fitting the real object shape or overfitting data noises, and thus a failure of deformation analysis. A multi-sensor system could integrate advantages of different sensors and improve the quality of mission completed. This paper combines terrestrial laser scanning (TLS) and laser tracker (LT) technologies, to enhance high-accuracy surface modeling in deformation analysis. A surface-based B-spline approximation and a multi-sensor system are investigated, the latter of which focuses mainly on the combination of TLS and LT technologies. The innovation of this paper is that the surface-based B-spline approximation is validated and optimized with LT corner cube reflectors. Hypothesis testing is adopted to select the best parameter setting by judging most consistency of TLS and LT in various epochs. In the B-spline surface modeling, both instrumental and numerical uncertainties are considered. We use the instrumental uncertainty model based on intensity value, as well as numerical uncertainty based on adjustment theories. A sampling strategy is proposed to avoid data gaps and obtain even distributed data points. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
15376494
Volume :
28
Issue :
15
Database :
Academic Search Index
Journal :
Mechanics of Advanced Materials & Structures
Publication Type :
Academic Journal
Accession number :
151190626
Full Text :
https://doi.org/10.1080/15376494.2019.1688435