Model Updating of a Steel Truss Based on Artificial Neural Networks

Abstract:

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Based on the artificial neural network, the parameters of a steel truss are identified. And the finite element model of truss is corrected. In order to improve the efficiency of model updating by artificial neural networks, the momentum is introduced into the back propagation algorithm. Based on the theory of probability and mathematical statistics, the expectation confidence interval of the measured deflections and strains is obtained. In this way, the samples to train the neural network are optimized. The numerical results show that the back propagation neural network proposed on this paper is able to correct the finite element model of the truss effectively.

Info:

Periodical:

Edited by:

Dongye Sun, Wen-Pei Sung and Ran Chen

Pages:

1363-1366

DOI:

10.4028/www.scientific.net/AMM.121-126.1363

Citation:

S. L. Zhang et al., "Model Updating of a Steel Truss Based on Artificial Neural Networks", Applied Mechanics and Materials, Vols. 121-126, pp. 1363-1366, 2012

Online since:

October 2011

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Price:

$35.00

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