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Establishment of the Complete Closed Mesh Model of Rail-Surface Scratch Data for Online Repair
Rail surface scratching occurs with increasing frequency, seriously threatening the safety of vehicles and humans. Online repair of rail-surface scratches on damaged rails with scratch depths >1 mm is of increased importance, because direct rail-replacement has the disadvantages of long operation...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7506854/ https://www.ncbi.nlm.nih.gov/pubmed/32825753 http://dx.doi.org/10.3390/s20174736 |
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author | Guo, Yanbin Huang, Lulu Liu, Yingbin Liu, Jun Wang, Guoping |
author_facet | Guo, Yanbin Huang, Lulu Liu, Yingbin Liu, Jun Wang, Guoping |
author_sort | Guo, Yanbin |
collection | PubMed |
description | Rail surface scratching occurs with increasing frequency, seriously threatening the safety of vehicles and humans. Online repair of rail-surface scratches on damaged rails with scratch depths >1 mm is of increased importance, because direct rail-replacement has the disadvantages of long operation time, high manpower and high material costs. Advanced online repair of rail-surface scratch using three-dimensional (3D) metal printing technology such as laser cladding has become an increasing trend, desperately demanding a solution for the fast and precise establishment of a complete closed mesh model of rail-surface scratch data. However, there have only been limited studies on the topic so far. In this paper, the complete closed mesh model is well established based on a novel triangulation algorithm relying on the topological features of the point-cloud model (PCM) of scratch-data, which is obtained by implementing a scratch-data-computation process following a rail-geometric-feature-fused algorithm of random sample consensus (RANSAC) performed on the full rail-surface PCM constructed by 3D laser vision. The proposed method is universal for all types of normal-speed rails in China. Experimental results show that the proposed method can accurately acquire the complete closed mesh models of scratch data of one meter of 50 Kg/m-rails within 1 min. |
format | Online Article Text |
id | pubmed-7506854 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-75068542020-09-26 Establishment of the Complete Closed Mesh Model of Rail-Surface Scratch Data for Online Repair Guo, Yanbin Huang, Lulu Liu, Yingbin Liu, Jun Wang, Guoping Sensors (Basel) Article Rail surface scratching occurs with increasing frequency, seriously threatening the safety of vehicles and humans. Online repair of rail-surface scratches on damaged rails with scratch depths >1 mm is of increased importance, because direct rail-replacement has the disadvantages of long operation time, high manpower and high material costs. Advanced online repair of rail-surface scratch using three-dimensional (3D) metal printing technology such as laser cladding has become an increasing trend, desperately demanding a solution for the fast and precise establishment of a complete closed mesh model of rail-surface scratch data. However, there have only been limited studies on the topic so far. In this paper, the complete closed mesh model is well established based on a novel triangulation algorithm relying on the topological features of the point-cloud model (PCM) of scratch-data, which is obtained by implementing a scratch-data-computation process following a rail-geometric-feature-fused algorithm of random sample consensus (RANSAC) performed on the full rail-surface PCM constructed by 3D laser vision. The proposed method is universal for all types of normal-speed rails in China. Experimental results show that the proposed method can accurately acquire the complete closed mesh models of scratch data of one meter of 50 Kg/m-rails within 1 min. MDPI 2020-08-21 /pmc/articles/PMC7506854/ /pubmed/32825753 http://dx.doi.org/10.3390/s20174736 Text en © 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Guo, Yanbin Huang, Lulu Liu, Yingbin Liu, Jun Wang, Guoping Establishment of the Complete Closed Mesh Model of Rail-Surface Scratch Data for Online Repair |
title | Establishment of the Complete Closed Mesh Model of Rail-Surface Scratch Data for Online Repair |
title_full | Establishment of the Complete Closed Mesh Model of Rail-Surface Scratch Data for Online Repair |
title_fullStr | Establishment of the Complete Closed Mesh Model of Rail-Surface Scratch Data for Online Repair |
title_full_unstemmed | Establishment of the Complete Closed Mesh Model of Rail-Surface Scratch Data for Online Repair |
title_short | Establishment of the Complete Closed Mesh Model of Rail-Surface Scratch Data for Online Repair |
title_sort | establishment of the complete closed mesh model of rail-surface scratch data for online repair |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7506854/ https://www.ncbi.nlm.nih.gov/pubmed/32825753 http://dx.doi.org/10.3390/s20174736 |
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