[1]杜德润,李爱群,杨玉冬,等.基于神经网络修正的结构有限元模型简化[J].东南大学学报(自然科学版),2003,33(5):635-637.[doi:10.3969/j.issn.1001-0505.2003.05.022]
 Du Derun,Li Aiqun,Yang Yudong,et al.Structural FEA model simplification based on neural network’s modification[J].Journal of Southeast University (Natural Science Edition),2003,33(5):635-637.[doi:10.3969/j.issn.1001-0505.2003.05.022]
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基于神经网络修正的结构有限元模型简化()
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《东南大学学报(自然科学版)》[ISSN:1001-0505/CN:32-1178/N]

卷:
33
期数:
2003年第5期
页码:
635-637
栏目:
土木工程
出版日期:
2003-09-20

文章信息/Info

Title:
Structural FEA model simplification based on neural network’s modification
作者:
杜德润1 李爱群1 杨玉冬2 吉林2 陆宇2 眭峰2
1 东南大学土木工程学院,南京 210096; 2 江苏省长江公路大桥建设指挥部,镇江 212002
Author(s):
Du Derun1 Li Aiqun1 Yang Yudong2 Ji Lin2 Lu Yu2 Sui Feng2
1 College of Civil Engineering, Southeast University, Nanjing 210096, China
2 Jiangsu Provincial Yangtze River Construction Commanding Department, Zhenjiang 212002, China
关键词:
神经网络 有限元模型 动力修正 改进BP神经网络
Keywords:
neural network FEA model dynamic modification improved BP
分类号:
TU311.41
DOI:
10.3969/j.issn.1001-0505.2003.05.022
摘要:
介绍了神经网络修正技术在结构有限元模型简化中的应用,并根据实际工程润扬大桥桥塔的现场实测模态数据对所建的有限元模型进行修正简化.建立了结构物理参数与结构自振频率之间复杂非线性关系的BP神经网络模型,反演仿真数据代入的有限元计算结果与实测结果较为吻合,证实了该方法的有效性.
Abstract:
The application of a neural network’s modification in a structural FEA(finite element analysis)model simplification is introduced. The FEA model of the Runyang Bridge tower is simplified according to measurement data and the complex nonlinear mapping relation is established between structural physical parameters and structural vibration frequency through an improved BP neural network. The computing results of FEA based on simulating data are very close to the test data, which demonstrates the method is effective.

参考文献/References:

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备注/Memo

备注/Memo:
基金项目: 国家重点工程科研项目“润扬长江公路大桥结构安全健康监测评估系统研究”资助项目.
作者简介: 杜德润(1976—), 男,博士生; 李爱群(联系人),男,博士,教授,博士生导师, aiqunli@public1.ptt.js.cn.
更新日期/Last Update: 2003-09-20