Inspection of Aircraft Wing Panels Using Unmanned Aerial Vehicles
Инспекция панелей крыла воздушных судов с использованием беспилотных летательных аппаратов
2019-04-17
SCID: 54.1/shu2fbzy
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aircraft wing panel inspectionautomated defect detectionpath followingultraviolet imaging inspectionunmanned aerial vehicles
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Abstract (AI)
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.
Key Findings
1
A small off-the-shelf multirotor UAV was developed for automated, non-destructive inspection of aircraft wing panels.
2
The UAV combines a wide-field-of-view camera and ultraviolet torch, while streaming inspection video to a ground station for real-time defect detection.
3
The complete inspection mission was automated, and the platform’s path-following behavior was mathematically modeled in MATLAB/SIMULINK.
4
Two defect-detection algorithms were tested on images collected at Airbus facilities and identified all defect-containing images in the current dataset.
Research Object
Aircraft wing panels inspected by an unmanned aerial vehicle
Research Subject
Automated non-destructive aerial inspection and defect detection in wing panels, including UAV path-following and real-time image analysis
Publication Details
Publication Date
2019-04-17
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