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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
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 Prevention and Mitigation Engineering, 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
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