Model Updating of A Steel Truss Based on Artificial Neural Networks

被引：3
|
作者：
Zhang, Shilei [5 ,1 ]
Chen, Shaofeng [2 ]
Wang, Huanding [1 ]
Wang, Wei [1 ]
机构：
[1] Harbin Inst Technol, Sch Civil Engn, Harbin 150090, Peoples R China
[2] Harbin Inst Technol, Sch Transportat Sci & Engn, Harbin 150090, Peoples R China
来源：
FRONTIERS OF MANUFACTURING AND DESIGN SCIENCE II, PTS 1-6 | 2012年 / 121-126卷
关键词：
model updating; neural network; back propagation; sample; truss; DERIVATIVES; MATRIX;
D O I：
10.4028/www.scientific.net/AMM.121-126.1363
中图分类号：
T [工业技术];
学科分类号：
08 ;
摘要：
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.
引用
收藏
页码：1363 / +
页数：2
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