Defect Detection Image Processing for Drone Inspection on Wide-Body Aircraft Surface

• Published in: E3S web of conferences Vol. 477; p. 100
• Main Authors: Mokhtar, Muhammad Izham Mohd, Basri, Adi Azriff, Basri, Ernnie Illyani, Sultan, Mohammed Thariq Hameed
• Format: Journal Article
• Language: English
• Published: EDP Sciences 01-01-2024
• Subjects: camera sensitivity; defect detection system; drone inspection
• ISSN: 2267-1242; 2267-1242
• DOI: 10.1051/e3sconf/202447700100

The dependence on Unmanned Aerial Vehicles (UAVs) has greatly increased in many sectors around the globe. UAVs are in high demand and their technology is developing quickly, due to their ability to handle a variety of issues in a sophisticated manner. UAVs deployment in the aviation industry is still in the trial phase, thus certain adjustments must be made to make sure the UAVs meet safety standards. Safety is the most important factor in the aviation sector since it involves people’s lives. UAVs are required to make the maintenance of an aircraft more efficient. For instance, UAVs are capable of replacing the labor-intensive inspection procedure with conducive and safe regulation. Additional tools or sensors need to be added to the UAVs system to ensure the objective of applying UAVs is achieved. The camera mounted on the drone is able to enhance the functionality and widen the range of applications of UAVs. This thesis presents the UAV system that is able to assist during an aircraft inspection. The camera mounted on the drone is installed with an image processing program to identify the defect caused by a lightning strike.