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Intelligent strain sensing on a smart composite wing using extrinsic Fabry-Perot interferometric sensors and neural networks

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5 Author(s)
Dua, R. ; Appl. Computational Intelligence Lab., Missouri Univ., Rolla, MO, USA ; Eller, V. ; Isaac, K.M. ; Watkins, S.E.
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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 feedforward neural networks trained using a backpropagation training algorithm. This mapping provides a method to predict the stall condition by comparing the strain available in real time and the predicted strain by the trained neural network.

Published in:

Neural Networks, 2003. Proceedings of the International Joint Conference on  (Volume:4 )

Date of Conference:

20-24 July 2003

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