Application of artificial neural network to predict static loads on an aircraft rib

被引：0

作者：

Amali, Ramin ^{[1
]}

Cooper, Samson ^{[1
]}

Noroozi, Siamak ^{[2
]}

机构：

[1] University of the West of England, Bristol

来源：

IFIP Advances in Information and Communication Technology | 2014年 / 436卷

关键词：

Aircraft rib; Artificial neural network; Finite Element Analysis; MATLAB; Static load;

D O I：

10.1007/978-3-662-44654-6_57

中图分类号：

学科分类号：

摘要：

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%. © IFIP International Federation for Information Processing 2014.

引用

页码：576 / 584

页数：8

共 6 条

[1] Liu S., Tong F., Fuzzy pattern recognition of impact acoustic signals for non-destructive, Sensors and Actuators: Physical, 167, pp. 588-593, (2011)
[2] Reed S., Cole D., Development of a Parametric Aircraft Fatigue Monitoring System using Artificial Neural Networks, Proceedings of the 22Nd Symposium of the International Committee on Aeronautical Fatigue, (2003)
[3] Polanco F., Estimation of Structural Component Loads in Helicopters: A Review of Current Methodologies, (1999)
[4] Mitchell T.M., Machine Learning, pp. 85-100, (1997)
[5] Bishop C.M., Pattern Recognition and Machine Learning, pp. 226-290, (2006)
[6] Neural Network Toolbox User Guide, (2012)

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