Advanced diagnostics of aircraft structures using automated non-invasive imaging techniques: a comprehensive review

Date published

2025-04-01

Free to read from

2025-04-24

Supervisor/s

Journal Title

Journal ISSN

Volume Title

Publisher

MDPI

Department

Type

Article

ISSN

2076-3417

Format

Citation

Bardis K, Avdelidis NP, Ibarra-Castanedo C, et al., (2025) Advanced diagnostics of aircraft structures using automated non-invasive imaging techniques: a comprehensive review. Applied Sciences, Volume 15, Issue 7, April 2025, Article number 3584

Abstract

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.

Description

Software Description

Software Language

Github

Keywords

4605 Data Management and Data Science, 46 Information and Computing Sciences, 40 Engineering, 4016 Materials Engineering

DOI

Rights

Attribution 4.0 International

Relationships

Relationships

Resources

Funder/s

This research was supported and funded by the British Engineering and Physical Sciences Research Council (EPSRC), grant number EP/T518104/1.