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Inspection of Aircraft Wing Panels Using Unmanned Aerial Vehicles †
In large civil aircraft manufacturing, a time-consuming post-production process is the non-destructive inspection of wing panels. This work aims to address this challenge and improve the defects’ detection by performing automated aerial inspection using a small off-the-shelf multirotor. The UAV is e...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6514946/ https://www.ncbi.nlm.nih.gov/pubmed/30999568 http://dx.doi.org/10.3390/s19081824 |
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author | Tzitzilonis, Vasileios Malandrakis, Konstantinos Zanotti Fragonara, Luca Gonzalez Domingo, Jose Angel Avdelidis, Nicolas P. Tsourdos, Antonios Forster, Kevin |
author_facet | Tzitzilonis, Vasileios Malandrakis, Konstantinos Zanotti Fragonara, Luca Gonzalez Domingo, Jose Angel Avdelidis, Nicolas P. Tsourdos, Antonios Forster, Kevin |
author_sort | Tzitzilonis, Vasileios |
collection | PubMed |
description | In large civil aircraft manufacturing, a time-consuming post-production process is the non-destructive inspection of wing panels. This work aims to address this challenge and improve the defects’ detection by performing automated aerial inspection using a small off-the-shelf multirotor. The UAV is equipped with a wide field-of-view camera and an ultraviolet torch for implementing non-invasive imaging inspection. In particular, the UAV is programmed to perform the complete mission and stream video, in real-time, to the ground control station where the defects’ detection algorithm is executed. The proposed platform was mathematically modelled in MATLAB/SIMULINK in order to assess the behaviour of the system using a path following method during the aircraft wing inspection. In addition, two defect detection algorithms were implemented and tested on a dataset containing images obtained during inspection at Airbus facilities. The results show that for the current dataset the proposed methods can identify all the images containing defects. |
format | Online Article Text |
id | pubmed-6514946 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-65149462019-05-30 Inspection of Aircraft Wing Panels Using Unmanned Aerial Vehicles † Tzitzilonis, Vasileios Malandrakis, Konstantinos Zanotti Fragonara, Luca Gonzalez Domingo, Jose Angel Avdelidis, Nicolas P. Tsourdos, Antonios Forster, Kevin Sensors (Basel) Article In large civil aircraft manufacturing, a time-consuming post-production process is the non-destructive inspection of wing panels. This work aims to address this challenge and improve the defects’ detection by performing automated aerial inspection using a small off-the-shelf multirotor. The UAV is equipped with a wide field-of-view camera and an ultraviolet torch for implementing non-invasive imaging inspection. In particular, the UAV is programmed to perform the complete mission and stream video, in real-time, to the ground control station where the defects’ detection algorithm is executed. The proposed platform was mathematically modelled in MATLAB/SIMULINK in order to assess the behaviour of the system using a path following method during the aircraft wing inspection. In addition, two defect detection algorithms were implemented and tested on a dataset containing images obtained during inspection at Airbus facilities. The results show that for the current dataset the proposed methods can identify all the images containing defects. MDPI 2019-04-17 /pmc/articles/PMC6514946/ /pubmed/30999568 http://dx.doi.org/10.3390/s19081824 Text en © 2019 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 Tzitzilonis, Vasileios Malandrakis, Konstantinos Zanotti Fragonara, Luca Gonzalez Domingo, Jose Angel Avdelidis, Nicolas P. Tsourdos, Antonios Forster, Kevin Inspection of Aircraft Wing Panels Using Unmanned Aerial Vehicles † |
title | Inspection of Aircraft Wing Panels Using Unmanned Aerial Vehicles † |
title_full | Inspection of Aircraft Wing Panels Using Unmanned Aerial Vehicles † |
title_fullStr | Inspection of Aircraft Wing Panels Using Unmanned Aerial Vehicles † |
title_full_unstemmed | Inspection of Aircraft Wing Panels Using Unmanned Aerial Vehicles † |
title_short | Inspection of Aircraft Wing Panels Using Unmanned Aerial Vehicles † |
title_sort | inspection of aircraft wing panels using unmanned aerial vehicles † |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6514946/ https://www.ncbi.nlm.nih.gov/pubmed/30999568 http://dx.doi.org/10.3390/s19081824 |
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