Intelligent Strain Sensing on a Smart Composite Wing Using Extrinsic Fabry-Perot Interferometric Sensors and Neural Networks
Strain prediction at various locations on a smart composite wing can provide useful information on its aerodynamic condition. The smart wing consisted of a glass/epoxy composite beam with three Extrinsic Fabry-Perot Interferometric (EFPI) sensors mounted at three different locations near the wing root. Strain acting on the three sensors at different air speeds and angles-of-attack were experimentally obtained in a closed circuit wind tunnel under normal conditions of operation. A function mapping the angle of attack and air speed to the strains on the three sensors was simulated using feed-forward neural networks trained using back-propagation training algorithm. This mapping provides a method to predict stall condition by comparing the strain available in real time and the predicted strain by the trained neural network.
Dua, Rohit, Vicki Eller, Kakkattukuzhy M. Isaac, Steve E. Watkins, and Donald C. Wunsch. "Intelligent strain sensing on a smart composite wing using extrinsic Fabry-Perot interferometric sensors and neural networks." In Proceedings of the International Joint Conference on Neural Networks, 2003., vol. 4, pp. 2667-2672. IEEE, 2003.
Proceedings of the International Joint Conference on Neural Networks