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PROCESSING OF POINT CLOUD DATA RETRIEVED FROM TERRESTRIAL LASER SCANNING FOR STRUCTURAL MODELING BY FINITE ELEMENT METHOD

Patryk Ziolkowski

First published: 2017-06-20https://doi.org/10.5593/sgem2017/23/s10.026View metrics

Abstract

Finite Element Method is one most popular contemporary method of strength analysis. The method is an advanced method for solving differential equations, based on discretization, which means that area is divided into finite elements. Each finite element has a solution of the equation approximated by specific functions and performing the actual calculations only for nodes of this division. Finite Element Method is widely used in structural strength simulations, in which features such as deformations, displacements, stresses might be examined. It might also be used with success in the dynamics and kinematics simulations. In presented paper, the author would like to raise an issue of reverse engineering and stress analysis of the existing structure. Strength analysis of existing structures requires tedious acquiring of dimensions and modeling, which sometimes (e.g., in the case of large objects) may be impossible, or extremely time-consuming and expensive. Light is the most accessible medium of collecting data about the environment, which use almost all living organisms. The author believes that the future of reverse engineering lies in optical methods, such as Terrestrial Laser Scanning. In the following paper, the author considers and try to answer the question, how to process point cloud data, in such a way, that it will be possible, in a relatively easy way to build up the finite elements mesh directly on the point cloud, which allows carrying out strength analysis.

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Publication details

Title
PROCESSING OF POINT CLOUD DATA RETRIEVED FROM TERRESTRIAL LASER SCANNING FOR STRUCTURAL MODELING BY FINITE ELEMENT METHOD
Authors
Patryk Ziolkowski
Proceedings
SGEM International Multidisciplinary Scientific GeoConference EXPO Proceedings; 17th International Multidisciplinary Scientific GeoConference SGEM2017, Informatics, Geoinformatics and Remote Sensing
Publisher
STEF92 Technology
Year
2017
Pages
211-218
SWS Citekey
Ziolkowski201710211218
ISSN
1314-2704
ISBN
978-619-7408-03-4
Language
en
Publication type
Conference Paper
Keywords
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Number of times cited according to Crossref: 1

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