Comparison of chaos optimization functions for performance improvement of fitting of non-linear geometries

Fitting algorithms play an important role in the whole measuring cycle in order to derive a measurement result. They involve associating substitute geometry to a point cloud obtained by an instrument. This situation is more difficult in the case of non-linear geometry fitting since iterative method...

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Main Authors: Moroni, Giovanni, Syam, Wahyudin P., Petrò, Stefano
Format: Article
Published: Elsevier 2016
Subjects:
Online Access:https://eprints.nottingham.ac.uk/34194/
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author Moroni, Giovanni
Syam, Wahyudin P.
Petrò, Stefano
author_facet Moroni, Giovanni
Syam, Wahyudin P.
Petrò, Stefano
author_sort Moroni, Giovanni
building Nottingham Research Data Repository
collection Online Access
description Fitting algorithms play an important role in the whole measuring cycle in order to derive a measurement result. They involve associating substitute geometry to a point cloud obtained by an instrument. This situation is more difficult in the case of non-linear geometry fitting since iterative method should be used. This article addresses this problem. Three geometries are selected as relevant case studies: circle, sphere and cylinder. This selection is based on their frequent use in real applications; for example, cylinder is a relevant geometry of an assembly feature such as pin-hole relationship, and spherical geometry is often found as reference geometry in high precision artifacts and mechanisms. In this article, the use of Chaos optimization (CO) to improve the initial solution to feed the iterative Levenberg–Marquardt (LM) algorithm to fit non-linear geometries is considered. A previous paper has shown the performance of this combination in improving the fitting of both complete and incomplete geometries. This article focuses on the comparison of the efficiency of different one-dimensional maps of CO. This study shows that, in general, logistic-map function provides the best solution compared to other types of one-dimensional functions. Finally, case studies on hemispheres and industrial cylinders fitting are presented.
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spelling nottingham-341942020-05-04T17:43:49Z https://eprints.nottingham.ac.uk/34194/ Comparison of chaos optimization functions for performance improvement of fitting of non-linear geometries Moroni, Giovanni Syam, Wahyudin P. Petrò, Stefano Fitting algorithms play an important role in the whole measuring cycle in order to derive a measurement result. They involve associating substitute geometry to a point cloud obtained by an instrument. This situation is more difficult in the case of non-linear geometry fitting since iterative method should be used. This article addresses this problem. Three geometries are selected as relevant case studies: circle, sphere and cylinder. This selection is based on their frequent use in real applications; for example, cylinder is a relevant geometry of an assembly feature such as pin-hole relationship, and spherical geometry is often found as reference geometry in high precision artifacts and mechanisms. In this article, the use of Chaos optimization (CO) to improve the initial solution to feed the iterative Levenberg–Marquardt (LM) algorithm to fit non-linear geometries is considered. A previous paper has shown the performance of this combination in improving the fitting of both complete and incomplete geometries. This article focuses on the comparison of the efficiency of different one-dimensional maps of CO. This study shows that, in general, logistic-map function provides the best solution compared to other types of one-dimensional functions. Finally, case studies on hemispheres and industrial cylinders fitting are presented. Elsevier 2016-05-01 Article PeerReviewed Moroni, Giovanni, Syam, Wahyudin P. and Petrò, Stefano (2016) Comparison of chaos optimization functions for performance improvement of fitting of non-linear geometries. Measurement, 86 . pp. 79-92. ISSN 0263-2241 least-square fitting non-linear optimization chaos optimization one dimensional map http://www.sciencedirect.com/science/article/pii/S0263224116001226 doi:10.1016/j.measurement.2016.02.045 doi:10.1016/j.measurement.2016.02.045
spellingShingle least-square fitting
non-linear optimization
chaos optimization
one dimensional map
Moroni, Giovanni
Syam, Wahyudin P.
Petrò, Stefano
Comparison of chaos optimization functions for performance improvement of fitting of non-linear geometries
title Comparison of chaos optimization functions for performance improvement of fitting of non-linear geometries
title_full Comparison of chaos optimization functions for performance improvement of fitting of non-linear geometries
title_fullStr Comparison of chaos optimization functions for performance improvement of fitting of non-linear geometries
title_full_unstemmed Comparison of chaos optimization functions for performance improvement of fitting of non-linear geometries
title_short Comparison of chaos optimization functions for performance improvement of fitting of non-linear geometries
title_sort comparison of chaos optimization functions for performance improvement of fitting of non-linear geometries
topic least-square fitting
non-linear optimization
chaos optimization
one dimensional map
url https://eprints.nottingham.ac.uk/34194/
https://eprints.nottingham.ac.uk/34194/
https://eprints.nottingham.ac.uk/34194/