Advanced Diagnostics of Aircraft Structures Using Automated Non-Invasive Imaging Techniques: A Comprehensive Review
The aviation industry currently faces several challenges in inspecting and diagnosing aircraft structures. Current aircraft inspection methods still need to be fully automated, making early detection and precise sizing of defects difficult. Researchers have expressed concerns about current aircraft...
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MDPI AG
2025-03-01
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| author | Kostas Bardis Nicolas P. Avdelidis Clemente Ibarra-Castanedo Xavier P. V. Maldague Henrique Fernandes |
| author_facet | Kostas Bardis Nicolas P. Avdelidis Clemente Ibarra-Castanedo Xavier P. V. Maldague Henrique Fernandes |
| author_sort | Kostas Bardis |
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| description | The aviation industry currently faces several challenges in inspecting and diagnosing aircraft structures. Current aircraft inspection methods still need to be fully automated, making early detection and precise sizing of defects difficult. Researchers have expressed concerns about current aircraft inspections, citing safety, maintenance costs, and reliability issues. The next generation of aircraft inspection leverages semi-autonomous and fully autonomous systems integrating robotic technologies with advanced Non-Destructive Testing (NDT) methods. Active Thermography (AT) is an example of an NDT method widely used for non-invasive aircraft inspection to detect surface and near-surface defects, such as delamination, debonding, corrosion, impact damage, and cracks. It is suitable for both metallic and non-metallic materials and does not require a coupling agent or direct contact with the test piece, minimising contamination. Visual inspection using an RGB camera is another well-known non-contact NDT method capable of detecting surface defects. A newer option for NDT in aircraft maintenance is 3D scanning, which uses laser or LiDAR (Light Detection and Ranging) technologies. This method offers several advantages, including non-contact operation, high accuracy, and rapid data collection. It is effective across various materials and shapes, enabling the creation of detailed 3D models. An alternative approach to laser and LiDAR technologies is photogrammetry. Photogrammetry is cost-effective in comparison with laser and LiDAR technologies. It can acquire high-resolution texture and colour information, which is especially important in the field of maintenance inspection. In this proposed approach, an automated vision-based damage evaluation system will be developed capable of detecting and characterising defects in metallic and composite aircraft specimens by analysing 3D data acquired using an RGB camera and a IRT camera through photogrammetry. Such a combined approach is expected to improve defect detection accuracy, reduce aircraft downtime and operational costs, improve reliability and safety and minimise human error. |
| format | Article |
| id | doaj-art-e60f00ab3e064e0790ecf1dc72bba04d |
| institution | OA Journals |
| issn | 2076-3417 |
| language | English |
| publishDate | 2025-03-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Applied Sciences |
| spelling | doaj-art-e60f00ab3e064e0790ecf1dc72bba04d2025-08-20T02:17:00ZengMDPI AGApplied Sciences2076-34172025-03-01157358410.3390/app15073584Advanced Diagnostics of Aircraft Structures Using Automated Non-Invasive Imaging Techniques: A Comprehensive ReviewKostas Bardis0Nicolas P. Avdelidis1Clemente Ibarra-Castanedo2Xavier P. V. Maldague3Henrique Fernandes4Integrated Vehicle Health Management Centre, Faculty of Engineering and Applied Sciences, Cranfield University, Bedford MK43 0AL, UKComputer Vision & Systems Laboratory, Department of Electrical & Computer Engineering, Laval University, Quebec City, QC G1V 0A6, CanadaComputer Vision & Systems Laboratory, Department of Electrical & Computer Engineering, Laval University, Quebec City, QC G1V 0A6, CanadaComputer Vision & Systems Laboratory, Department of Electrical & Computer Engineering, Laval University, Quebec City, QC G1V 0A6, CanadaIntegrated Vehicle Health Management Centre, Faculty of Engineering and Applied Sciences, Cranfield University, Bedford MK43 0AL, UKThe aviation industry currently faces several challenges in inspecting and diagnosing aircraft structures. Current aircraft inspection methods still need to be fully automated, making early detection and precise sizing of defects difficult. Researchers have expressed concerns about current aircraft inspections, citing safety, maintenance costs, and reliability issues. The next generation of aircraft inspection leverages semi-autonomous and fully autonomous systems integrating robotic technologies with advanced Non-Destructive Testing (NDT) methods. Active Thermography (AT) is an example of an NDT method widely used for non-invasive aircraft inspection to detect surface and near-surface defects, such as delamination, debonding, corrosion, impact damage, and cracks. It is suitable for both metallic and non-metallic materials and does not require a coupling agent or direct contact with the test piece, minimising contamination. Visual inspection using an RGB camera is another well-known non-contact NDT method capable of detecting surface defects. A newer option for NDT in aircraft maintenance is 3D scanning, which uses laser or LiDAR (Light Detection and Ranging) technologies. This method offers several advantages, including non-contact operation, high accuracy, and rapid data collection. It is effective across various materials and shapes, enabling the creation of detailed 3D models. An alternative approach to laser and LiDAR technologies is photogrammetry. Photogrammetry is cost-effective in comparison with laser and LiDAR technologies. It can acquire high-resolution texture and colour information, which is especially important in the field of maintenance inspection. In this proposed approach, an automated vision-based damage evaluation system will be developed capable of detecting and characterising defects in metallic and composite aircraft specimens by analysing 3D data acquired using an RGB camera and a IRT camera through photogrammetry. Such a combined approach is expected to improve defect detection accuracy, reduce aircraft downtime and operational costs, improve reliability and safety and minimise human error.https://www.mdpi.com/2076-3417/15/7/3584aircraft inspectiondefect detectionthermographyvisual inspectiondefect estimationphotogrammetry |
| spellingShingle | Kostas Bardis Nicolas P. Avdelidis Clemente Ibarra-Castanedo Xavier P. V. Maldague Henrique Fernandes Advanced Diagnostics of Aircraft Structures Using Automated Non-Invasive Imaging Techniques: A Comprehensive Review Applied Sciences aircraft inspection defect detection thermography visual inspection defect estimation photogrammetry |
| title | Advanced Diagnostics of Aircraft Structures Using Automated Non-Invasive Imaging Techniques: A Comprehensive Review |
| title_full | Advanced Diagnostics of Aircraft Structures Using Automated Non-Invasive Imaging Techniques: A Comprehensive Review |
| title_fullStr | Advanced Diagnostics of Aircraft Structures Using Automated Non-Invasive Imaging Techniques: A Comprehensive Review |
| title_full_unstemmed | Advanced Diagnostics of Aircraft Structures Using Automated Non-Invasive Imaging Techniques: A Comprehensive Review |
| title_short | Advanced Diagnostics of Aircraft Structures Using Automated Non-Invasive Imaging Techniques: A Comprehensive Review |
| title_sort | advanced diagnostics of aircraft structures using automated non invasive imaging techniques a comprehensive review |
| topic | aircraft inspection defect detection thermography visual inspection defect estimation photogrammetry |
| url | https://www.mdpi.com/2076-3417/15/7/3584 |
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