| 基于神经网络的斜拉索损伤识别研究 |
| |
| 引用本文： | 郑婷婷,虞庐松.基于神经网络的斜拉索损伤识别研究[J].兰州铁道学院学报,2006,25(4):32-34,38. |
| |
| 作者姓名： | 郑婷婷 虞庐松 |
| |
| 作者单位： | 兰州交通大学土木工程学院 甘肃兰州730070 |
| |
| 摘 要： | 以一模型桥为背景,探讨了斜拉索损伤定位以及损伤程度确定的方法.基于ANSYS有限元模型,采用RBF网络,模拟了斜拉索的损伤情况.以不同损伤程度下自振频率和局部模态作为神经网络的训练与测试输入样本,由神经网络的输出来指示损伤位置和损伤程度,并与BP神经网络的识别效果进行比较.
|
| 关 键 词： | 斜拉索 损伤位置及程度识别 神经网络 |
| 文章编号： | 1001-4373（2006）04-0032-03 |
| 收稿时间： | 2006-04-11 |
| 修稿时间： | 2006-04-11 |
Study of Cable-stayed Cable Damage Identification Based on Neural Network |
| |
| Zheng Tingting,Yu Lusong.Study of Cable-stayed Cable Damage Identification Based on Neural Network[J].Journal of Lanzhou Railway University,2006,25(4):32-34,38. |
| |
| Authors: | Zheng Tingting Yu Lusong |
| |
| Institution: | School of Engineering, Lanzhou Jiaotong University, Lanzhou 730070,China |
| |
| Abstract: | Orientation method for cable-stayed cable damage and the degree of cable-stayed cable damage based on a model bridge is probed.And damage situation of cable-stayed cable is simulated by using RBF network based on finite element model in ANSYS.Taking natural frequency and local mode as input stylebook for neural network training and neural network testing,the output of neural network denotes the position and degree of damage.Then the identification effect is compared with the identification effect of BP network. |
| |
| Keywords: | cable-stayed cable identification of damage position and damage degree neural network |
| 本文献已被 CNKI 维普 万方数据 等数据库收录！ |
