小波包和频响函数随机-模糊统计的斜拉桥损伤识别
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摘要
针对单点损伤识别方法的缺点,提出了基于频响函数和小波包能量谱的斜拉桥多点损伤识别指标。对结构损伤前后的频响函数值进行了随机-模糊均值处理,将处理的频响函数作为基进行小波包能量谱分析,提取能量累积变异值进行损伤识别,并进行了独塔斜拉桥模型的试验研究和连续梁与简支梁的数值仿真。分析结果表明:桥梁上有1处和2处损伤时都可被识别和定位;损伤指标随着损伤程度的增加而变化,损伤初期呈线性变化,损伤程度在40%~50%时,指标变化趋缓,损伤超过50%后,指标值又会急剧变化;采用锤击激励比环境激励的损伤识别结果更好,锤击激励力大小对损伤识别效果无影响。
In view of the defects of single-location damage identifying method,the multi-location damage identifying index of cable-stayed bridge in combination with wavelet packet energy spectrum and frequency response function(FRF) was proposed.The random-fuzzy mean was processed with the FRFs of undamaged and damaged structures.Wavelet packet energy spectrum was analyzed with the processed FRFs as wavelet base functions,and the value of accumulated energy variation was extracted to recognize damages.The experiment of a single tower cable-stayed bridge model and the numerical simulations of continuous and simple-supported beams were carried out.Analysis result shows that 1 or 2-loacation damage of bridge model can be identified and located.With the increasing of damage severity,the initial damage index increases linearly,and it will change gently or dramatically when the damage severity approaches 40%-50% or exceeds 50% respectively.The damage identifying result of hammering excitation is better than that of environmental excitation,and the value of hammering exciting load has no effect on identifying precision.1 tab,8 figs,15 refs.
In view of the defects of single-location damage identifying method,the multi-location damage identifying index of cable-stayed bridge in combination with wavelet packet energy spectrum and frequency response function(FRF) was proposed.The random-fuzzy mean was processed with the FRFs of undamaged and damaged structures.Wavelet packet energy spectrum was analyzed with the processed FRFs as wavelet base functions,and the value of accumulated energy variation was extracted to recognize damages.The experiment of a single tower cable-stayed bridge model and the numerical simulations of continuous and simple-supported beams were carried out.Analysis result shows that 1 or 2-loacation damage of bridge model can be identified and located.With the increasing of damage severity,the initial damage index increases linearly,and it will change gently or dramatically when the damage severity approaches 40%-50% or exceeds 50% respectively.The damage identifying result of hammering excitation is better than that of environmental excitation,and the value of hammering exciting load has no effect on identifying precision.1 tab,8 figs,15 refs.
引文
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[13]王振林,聂国华.曲率模态和小波包变换在结构损伤识别中的应用[J].振动与冲击,2008,27(1):124-126.WANG Zhen-lin,NIE Guo-hua.A method for structuredamage detection based on curvature mode and wavelet packettransformation[J].Journal of Vibration and Shock,2008,27(1):124-126.(in Chinese)
[14]李胡生.地基土工实验数据的随机-模糊统计原理及方法[J].四川建筑科学研究,2006,32(5):88-92.LI Hu-sheng.The random-fuzzy principle and calculationmethod for the statistics of experi mental data of foundationgeotechnical test[J].Sichuan Building Science,2006,32(5):88-92.(in Chinese)
[15]YEN G G,LI N K C.Wavelet packet feature extraction forvibration monitoring[J].IEEE Transactions on IndustrialElectronics,2000,47(3):650-667.
[2]郑明刚,刘天雄,陈兆能.基于频响函数的结构损伤检测[J].机械科学与技术,2001,20(3):479-480.ZHENG Ming-gang,LI U Tian-xiong,CHEN Zhao-neng.Structural damage assessment based on frequency responsefunction[J].Mechanical Science and Technology,2001,20(3):479-480.(in Chinese)
[3]曾神昌,麦汉超.结构健康监测系统中的频率响应方法[J].强度与环境,2004,31(1):29-34.ZENG Shen-chang,MAI Han-chao.Frequency response methodin structure health monitoring system[J].Structure andEnvironment Engineering,2004,31(1):29-34.(in Chinese)
[4]李友荣,曾法力,吕勇,等.小波包分析在齿轮故障诊断中的应用[J].振动与冲击,2005,24(5):101-103.LI You-rong,ZENG Fa-li,LU Yong,et al.Application ofwavelet packet analysis to gear fault diagnosis[J].Journal ofVibration and Shock,2005,24(5):101-103.(in Chinese)
[5]刘宗页,方开翔,林玮.小波分析在齿轮故障诊断中的应用研究[J].噪声与振动控制,2009,29(4):58-59,119.LI U Zong-ye,FANG Kai-xiang,LIN Wei.Application studyof wavelet analysisin the fault diagnosis of gears[J].Noise andVibration Control,2009,29(4):58-59,119.(in Chinese)
[6]李宏男,孙鸿敏.小波分析在土木工程领域中的应用[J].世界地震工程,2003,19(2):16-22.LI Hong-nan,SUN Hong-min.Application of wavelet ana-lytical method to civil engineering[J].World EarthquakeEngineering,2003,19(2):16-22.(in Chinese)
[7]李洪泉,董亮,吕西林.基于小波变换的结构损伤识别与试验分析[J].土木工程学报,2003,36(5):52-57,75.LI Hong-quan,DONG Liang,LU Xi-lin.Identification ofstructural damage and test study based on wavelet transform[J].China Civil Engineering Journal,2003,36(5):52-57,75.(in Chinese)
[8]孙增寿,林友勤,任伟新.基于小波能量分布向量的结构损伤识别[J].地震工程与工程振动,2007,27(5):103-109.SUN Zeng-shou,LI N You-qin,REN Wei-xin.Structuraldamage identification based on wavelet energy distributionvectors[J].Journal of Earthquake Engineering and EngineeringVibration,2007,27(5):103-109.(in Chinese)
[9]SUN Zhi,CHANG C C.Statistical wavelet-based methodforstructural health monitoring[J].Journal of StructuralEngineering,2004,130(7):1055-1062.
[10]丁幼亮,李爱群,缪长青,等.基于小波包能量谱的大跨桥梁结构损伤预警指标[J].中国公路学报,2006,19(5):34-40.DI NG You-liang,LI Ai-qun,MI AO Chang-qing,et al.Structural damage alarming indices for long-span bridgesbased on wavelet packet energy spectrum[J].China Journalof Highway and Transport,2006,19(5):34-40.(inChinese)
[11]HAN Jian-gang,REN Wei-xin,SUN Zeng-shou.Waveletpacket based damage identification of beam structures[J].International Journal of Solids and Structures,2005,42(26):6610-6627.
[12]韩建刚,任伟新,孙增寿.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.HAN Jian-gang,REN Wei-xin,SUN Zeng-shou.Damagedetection of beams based on wavelet packet analysis[J].Journal of Vibration,Measurement&Diagnosis,2006,26(1):5-10.(in Chinese)
[13]王振林,聂国华.曲率模态和小波包变换在结构损伤识别中的应用[J].振动与冲击,2008,27(1):124-126.WANG Zhen-lin,NIE Guo-hua.A method for structuredamage detection based on curvature mode and wavelet packettransformation[J].Journal of Vibration and Shock,2008,27(1):124-126.(in Chinese)
[14]李胡生.地基土工实验数据的随机-模糊统计原理及方法[J].四川建筑科学研究,2006,32(5):88-92.LI Hu-sheng.The random-fuzzy principle and calculationmethod for the statistics of experi mental data of foundationgeotechnical test[J].Sichuan Building Science,2006,32(5):88-92.(in Chinese)
[15]YEN G G,LI N K C.Wavelet packet feature extraction forvibration monitoring[J].IEEE Transactions on IndustrialElectronics,2000,47(3):650-667.
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