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基于曲率模态和小波系数差的损伤识别
引用本文:宋子收,周奎,李胡生,葛继平.基于曲率模态和小波系数差的损伤识别[J].公路交通科技,2010,27(11):61-66.
作者姓名:宋子收  周奎  李胡生  葛继平
作者单位:1. 上海理工大学,环境与建筑学院,上海,200093;海应用技术学院,土木建筑与安全工程学院,上海,200235
2. 上海理工大学,环境与建筑学院,上海,200093
3. 海应用技术学院,土木建筑与安全工程学院,上海,200235
基金项目:海市科学技术委员会重点科技攻关项目(072105115);上海市优青科研专项基金资助项目(YYY09007)
摘    要:针对单一方法对结构损伤识别不太敏感的缺陷,提出了结合曲率模态和小波分析的综合损伤识别方法。以损伤前后的曲率模态作为分析信号,进行离散小波变换,提取高阶频率系数。将高阶系数之差作为损伤指标,通过高频系数差值的奇异处可以识别损伤位置。经过对2跨连续梁的数值模拟,不仅能够识别1、2处损伤,还能识别支座附近的损伤。证实了此方法定位准确,易于识别的优点,并对一座2跨连续梁钢桥模型进行试验。

关 键 词:桥梁工程  损伤识别  曲率模态  小波系数差
收稿时间:2009-10-29

Damage Identification Based on Curvature Mode and Difference of Wavelet Coefficients
SONG Zishou,ZHOU Kui,LI Husheng,GE Jiping.Damage Identification Based on Curvature Mode and Difference of Wavelet Coefficients[J].Journal of Highway and Transportation Research and Development,2010,27(11):61-66.
Authors:SONG Zishou  ZHOU Kui  LI Husheng  GE Jiping
Institution:1.School of Environment and Architecture, University of Shanghai for Science and Technology, Shanghai 200093, China; 2. School of Civil Construction and Security Engineering,Shanghai Institute of Technology, Shanghai 200235, China
Abstract:To cope with the insensitivity of single method for structural damage identification, a comprehensive damage identification method in combination with curvature mode and wavelet analysis was proposed. The method takes curvature mode which comes from damaged and undamaged structures as signal, carries on discrete wavelet transform and extracts high-frequency coefficients. Then takes difference between high-frequency coefficients as the damage index, damage location can be identified through the singularity of the difference. Through numerical simulation of a two-span continuous beam, not only one and two damages but also damage located at the supports can be identified. It is confirmed that the method has advantages of accurate positioning and easy identification. A model of two-span steel bridge was tested by the proposed method.
Keywords:bridge engineering  damage identification  curvature mode  difference of wavelet coefficients   
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