Projects Last Projects
Aircraft Wing Shape Analysis by On-board Cameras and Deep Learning
Alexander Portiankin, Ido Plat
Supervised by Ido Imanuel
The main drivers in today's aircraft design are performance improvements, reduction of fuel consumption, and harmful emission. We can straightforwardly achieve these goals with lightweight, large wingspan designs. However, such configurations are inherently more flexible and susceptible to adverse aeroelastic phenomena, including reduced control authority, increased maneuver loads, excessive response to atmospheric turbulence, and flutter instability. The immediate remedy for aeroelastic problems is stiffening the structure.
In this project, we make an essential step - we implement and test the proposed methodology using synthetic, computational data. We simulate a large dataset of 2D wing images and their corresponding deformation parameters and train a neural network, validating it on many unseen examples. We show promising results in preparation for the experimental phase, where this methodology test empirically under lab conditions.
Please, see project report.
Please, see final presentation.