钢筋混凝土梁损伤的小波包识别方法

英文篇名：Damage Identification of Reinforced Concrete Beam Based on Wavelet Packet
中文刊名：振动.测试与诊断
英文刊名：Journal of Vibration ; Measurement & Diagnosis
作者：任宜春 ; 张杰峰 ; 刘哲峰
英文作者：Ren Yichun1 ; Zhang Jiefeng2 ; Liu Zhefeng1(1School of Civil Engineering and Architecture ; Changsha University of Science and Technology Changsha ; 410114 ; China)(2Changsha Zhonggui Design of Construction Company Changsha ; 410007 ; China)
中文关键词：损伤识别 ; 小波包分解 ; 特征能量向量 ; 钢筋混凝土梁
英文关键词：damage detection wavelet packet decomposition characteristic component energy reinforced concrete beam
出版日期：2011-10-15
机构：长沙理工大学土建学院;长沙市中规建设设计公司;
年：2011
期：05
出版单位：振动.测试与诊断

摘要

基于小波包能量特征向量的损伤识别是一种对损伤非常敏感的方法。为了更有效地选择特征频带,从频带分解的角度分析了基于小波包分解能量特征向量的结构损伤识别方法。将结构响应信号进行小波包分解,提取各频带的能量。通过分析结构响应频率和小波包分解各频带频率范围,选取信号主要频率所在频带及其相邻频带的能量构成特征向量。当信号频率有微小改变时,特征能量向量的变化远远大于信号频率的变化。当结构出现损伤时,脉冲激励下其动力响应信号的频率有所降低,因此可以通过特征能量向量的变化来识别损伤。通过一根钢筋混凝土梁的试验验证了该方法的有效性。
The method for damage identification based on wavelet packet component energy is sensitive to structural damage.In order to select the characteristic frequency band more efficiently,the method in the point of frequency band decomposition of wavelet packet transform is analyzed.The structure vibration response is transformed by wavelet packet and the component energies are calculated.The frequency of the response and the range of each frequency band are analyzed. The frequency band,in which the main frequency of the signal exists,and the adjacent bands are selected as the characteristic bands.If the frequency of the signal changes,the energies of the characteristic bands change more greatly than the frequency itself.When the structure is damaged,the frequencies of the response on impulse force change and the change of WP-based component energies are used as the indices of the damage.A dynamic test on a reinforeced concrete beam confirms the feasibility of the method.

引文

[1]Doebling S W,Farrar C R,Prime M B.A summaryreview of vibration-based damage identification meth-ods[J].The Shock and Vibration Digest,1998,30(2):91-105.
    [2]宗周红,任伟新,阮毅.土木工程结构损伤诊断研究进展[J].土木工程学报,2003,36(5):105-110.
    [3]Farra C R,Cornwell P J,Doebling S W,et al.Struc-tural health mornitoring studies of the AlamosaCanyon and 1-40 bridge[M].Los Alamos N.M.:LosAlamos National Laboratory,2000.
    [4]Yen G G,Lin K C.Wavelet packet feature extractionfor vibration monitoring[J].IEEE Trans IndustrialElectronics,2000,47(3):650-667.
    [5]丁幼亮,李爱群.基于振动测试与小波包分析的结构损伤预警[J].力学学报,2006,38(5):639-644.
    [6]Sun Z,Chang C C.Structural damage assessmentbased on wavelet packet transform[J].Journal ofStructure Engineering,2002,128(10):1354-1361.
    [7]Sun Z,Chang C C.Statistical wavelet-based methodfor structural health monitoring[J].Journal of Struc-ture Engineering,2004,130(7):1055-1062.
    [8]李宏男,孙鸿敏.基于小波分析和神经网络的框架结构损伤诊断方法[J].地震工程与工程振动,2003,23(5):141-148.
    [9]韩建刚,任伟新,孙中寿.基于小波包变换的梁体损伤识别[J].振动、测试与诊断,2006,26(1):5-10.
    [10]闫维明,张卫东,何浩祥,等.基于小波神经网络的RC梁损伤识别试验研究[J].振动、测试与诊断,2007,27(2):129-132.
    [11]胡昌华,张军波,夏军,等.基于Matlab的系统分析与设计——小波分析[M].西安:西安电子科技大学出版社,1999:217-230.
    [12]杨建国.小波分析及其工程应用[M].北京:机械工业出版社,2005:63-77.