| Issue |
E3S Web Conf.
Volume 698, 2026
First International Conference on Research and Advancements in Electronics, Energy, and Environment (ICRAEEE 2025)
|
|
|---|---|---|
| Article Number | 01002 | |
| Number of page(s) | 5 | |
| Section | Electrical and Electronic Engineering | |
| DOI | https://doi.org/10.1051/e3sconf/202669801002 | |
| Published online | 16 March 2026 | |
Intelligent Image-Based Detection of Surface Anomalies in Aircraft Structures
1 Instrumentation and Control Laboratory-Center for Sci-Tech Research in Earth System and Energy – CREATE, Universidade de Évora, Portugal.
2 Cátedra CEiiA de Ciência e Tecnologia Aeroespacial, Universidade de Évora, Portugal.
3 CTI Aeroespacial, Cátedra CEiiA de Ciência e Tecnologia Aeroespacial, Évora, Portugal.
* Corresponding author: This email address is being protected from spambots. You need JavaScript enabled to view it.
Abstract
In the aviation industry, the structural integrity of aircraft is paramount to ensure safety and reliability. The process of regular inspections and maintenance is integral to identifying abnormalities on the surface of the aircraft, which could cause catastrophic failures if left unchecked. Usually, the traditional process of inspections involves the visual assessment of the aircraft surface by a human, who may take a long time, is prone to inaccuracies and requires abundant knowledge. This work presents a discussion on the use of the YOLO image processing technique for the automated detection of abnormalities that exist on the surface of aircraft, including cracks, corrosion, dents, and delamination. The use of image processing for the detection of aircraft surface abnormalities stands to revolutionise the process of maintenance associated with aircraft. A second stage was added to the process, which focuses on including a human in the loop verification, where the inspector will be able to evaluate and validate the results. The technology possesses the potential for ease of scalability for the assessment of numerous aircraft in the fleet. The process leads to beneficial outcomes, including safety, cost reduction, and improved reliability.
© The Authors, published by EDP Sciences, 2026
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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