| Popis: |
This review paper examines the use of Unmanned Aircraft Systems (UAS) for inspecting aircraft structures and aeronautical infrastructure as a supplement to traditional methods. The goal is to evaluate the technical and regulatory viability of automated inspections. A systematic review was conducted via Scopus and Google Scholar using terms like aircraft, airport, inspection, UAS, Remotely Piloted Aircraft System (RPAS), Unmanned Aerial Vehicle (UAV), and drone. Research was filtered by engineering, computer science, materials science, energy, decision science, and environmental science, prioritizing studies published in the last decade. The article explores drones commonly used in Structural Health Monitoring (SHM), emphasizing multirotor drones for aircraft structural inspection. It discusses onboard sensors and cameras required for data acquisition, such as Laser Imaging Detection and Ranging (LiDAR) and Infrared Thermography (IR). Deliverables such as 3D models, orthomosaics, Digital Surface Models (DSM), Digital Elevation Models (DEM), and Digital Terrain Models (DTM) are created to identify structural defects such as cracks, delamination, dents, corrosion, and pores. Image post-processing techniques include algorithms like Convolutional Neural Networks (CNN), OpenCV, and Generative Adversarial Networks (GAN), using software such as MATLAB, PIX4DMapper, Agisoft PhotoScan, and FlirTools. The review concludes that drones and UAS can feasibly and effectively supplement conventional aircraft inspections. However, regulatory and operational challenges limit the full automation of the inspection process. |
