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| 苏通大桥结构健康状态评估技术研究与应用(1):拉索损伤识别 | |
| 引用本文： | 杨杰,李爱群,丁幼亮,姚蓓,杨军,张维苏.苏通大桥结构健康状态评估技术研究与应用(1):拉索损伤识别[J].防灾减灾工程学报,2010,30(3):325-329. |
| 作者姓名： | 杨杰 李爱群 丁幼亮 姚蓓 杨军 张维苏 |
| 作者单位： | 1. 东南大学混凝土与预应力混凝土结构教育部重点实验室,南京,210096;南京航空航天大学土木工程系,南京,210016 2. 东南大学混凝土与预应力混凝土结构教育部重点实验室,南京,210096 3. 江苏省苏通大桥建设指挥部,南京,210006 |
| 基金项目： | 国家杰出青年科学基金项目，国家"十一五"科技支撑计划项目，国家航空科学基金项目 |
| 摘 要： | 采用改进的RBF神经网络建立了苏通大桥拉索损伤识别方法。2个不同阶固有频率之比是仅与损伤位置有关的结构振动参数,据此定义了用于损伤定位的损伤特征指标,并用其来训练神经网络;提出了基于R2+准则与Jackknife校验的改进RBF算法,以有效地控制RBF网络的过拟合现象。算例结果表明,所提出的方法可以较好地对苏通大桥斜拉索进行损伤识别。 |
| 关 键 词： | 斜拉桥 结构损伤识别 神经网络 斜拉索 |
Technology and Application of Structural Health Condition Assessment for Sutong Bridge(1):Damage Identification of Stay Cable |
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| YANG Jie,LI Ai-qun,DING You-liang,YAO Bei,YANG Jun,ZHANG Wei-su.Technology and Application of Structural Health Condition Assessment for Sutong Bridge(1):Damage Identification of Stay Cable[J].Journal of Disaster Prevent and Mitigation Eng,2010,30(3):325-329. | |
| Authors: | YANG Jie LI Ai-qun DING You-liang YAO Bei YANG Jun ZHANG Wei-su |
| Abstract: | In this paper the damage identification method for stay cable of Sutong Bridge is established using the modified RBF neural networks.The ratio of two different frequencies of the main girder is a vibration character which varies only with the damage location.It is selected as damage analysis index to train the neural networks.And in order to control the over-fitting of RBF neural networks,a new modified algorithm is presented based on R2+ rule and Jackknife validation.The analysis results show that the presented method can effectively locate the cable damage of Sutong Bridge. |
| Keywords: | cable-stayed bridge structural damage identification neural network stay cable |
| 本文献已被 CNKI 维普 万方数据 等数据库收录！ | |