Prediction of the business jet Global 7500 wing deformed shape using fiber Bragg gratings and neural network
T. Klotz, R. Pothier, Denis Walch, T. Colombo
Abstract
To develop a common deflection and twist measuring method applicable for both ground and flight tests, the left wing of a Global 7500 business jet was instrumented with fiber Bragg gratings and underwent durability and damage tolerance certification testing. This fiber optical sensing system allows distributed strain measurements on the wing. Fatigue and static tests were monitored. It was shown that the front and rear spar deflections could be analytically calculated with an acceptable accuracy. However, the twist could not be successfully calculated. A neural network was then used to address this issue. Even though the deflection predictions were less accurate than those analytically calculated, the wing twist was successfully predicted. This study shows the potential of using fiber Bragg grating as a shared ground and flight tests strain measuring method allowing to calculate the aircraft wing deflection and to determine the wing twist angle using a neural network.