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矮塔斜拉桥施工状态下结构损伤识别研究
作者姓名:张寅涛  唐雪松  陈星烨
作者单位:长沙理工大学土木与建筑学院
基金项目:湖南省科技厅科技计划项目(2011FJ3235)
摘    要:以广东省江肇高速公路西江特大桥为工程背景,选取最大双悬臂施工状态,采用MIDAS软件获取损伤状态下的各阶模态,将模态信号导入MATLAB中进行了Hilbert-Huang变换和小波变换,对结构损伤状况进行了识别判断,并对比了两种识别方法的识别效果.研究结果表明:Hilbert-Huang变换方法损伤识别效果良好,抗噪性强,但存在端点效应问题;小波变换方法损伤识别效果与所选小波基有关,不利于基准的选取,且小波识别需要消噪,消噪可能会导致损伤漏检.

关 键 词:矮塔斜拉桥  损伤识别  施工状态  Hilbert-Huang变换  小波变换

Damage identification of cable-stayed bridge with low towers under construction state
Authors:ZHANG Yin-tao  TANG Xue-song  CHEN Xing-ye
Institution:(School of Civil Engineering and Architecture,Changsha University of Science & Technology,Changsha 410004,China)
Abstract:Xijiang Large Bridge on the highway from Jiangmen to Zhaoqing in Guangdong province is taken as an example.The longest double cantilever beam state during the construction period is considered.The FEM model is established by the software MIDAS.Then,the modal singles under undamaged and damaged states are obtained from the FEM modal analysis.The modal signals are input into MATLAB to perform the Hilbert-Huang and wavelet transformation in order to estimate the structure damage location and degree.The results show that the HHT method is effective and has a stronger anti-noise feature.The limitation is the end effect.On the other hand,the accuracy of wavelet method is related to the choice of wavelet basis which is disadvantageous to set up the standard of damage identification.Moreover,the wavelet method needs denoising and this may result in the failure of damage detection.
Keywords:cable-stayed bridge with low towers  damage identification  construction state  Hilbert-Huang transformation  wavelet transformation
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