Application of Artificial Neural Network to Predict Static Loads on an Aircraft Rib

Abstract : Aircraft wing structures are subjected to different types of loads such as static and dynamic loads throughout their life span. A methodology was developed to predict the static load applied on a wing rib without load cells using Artificial Neural Network (ANN). In conjunction with the finite element modelling of the rib, a classic two layer feed-forward networks were created and trained on MATLAB using the back-propagation algorithm. The strain values obtained from the static loading experiment was used as the input data for the network training and the applied load was set as the output. The results obtained from the ANN showed that this method can be used to predict the static load applied on the wing rib to an accuracy of 92%.
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Lazaros Iliadis; Ilias Maglogiannis; Harris Papadopoulos. 10th IFIP International Conference on Artificial Intelligence Applications and Innovations (AIAI), Sep 2014, Rhodes, Greece. Springer, IFIP Advances in Information and Communication Technology, AICT-436, pp.576-584, 2014, Artificial Intelligence Applications and Innovations. 〈10.1007/978-3-662-44654-6_57〉
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Ramin Amali, Samson Cooper, Siamak Noroozi. Application of Artificial Neural Network to Predict Static Loads on an Aircraft Rib. Lazaros Iliadis; Ilias Maglogiannis; Harris Papadopoulos. 10th IFIP International Conference on Artificial Intelligence Applications and Innovations (AIAI), Sep 2014, Rhodes, Greece. Springer, IFIP Advances in Information and Communication Technology, AICT-436, pp.576-584, 2014, Artificial Intelligence Applications and Innovations. 〈10.1007/978-3-662-44654-6_57〉. 〈hal-01391362〉

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