环境激励下基于经验模式分解的结构模态参数识别方法
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摘要
识别结构模态参数是结构健康监测和振动控制等研究及工程实践中的一个重要环节,同时也是前提和难点所在。提出基于经验模式分解(EMD)的环境激励结构模态参数识别的STD法、复指数法与ARMA法。3种方法采用EMD将结构环境振动响应原始信号分解成若干个基本模式分量(IMF),使每一个基本模式分量仅为结构的某一阶固有模态,采用相关系数法结合频谱分析挑选出真实IMF,进而分别用STD法、复指数法与ARMA法进行模态参数识别。四层钢框架模型环境振动试验分析结果表明,3种方法能有效地避免结构各阶模态之间的相互影响,能够更清晰更方便得到结构模态参数。采用基于奇异值差分谱进行去噪处理,使得识别结果更加准确。
The system modal parameters identification under ambient excitation becomes the focus of the structural health monitoring.Empricalmode decomposition(EMD) based STD method,complex index method and ARMA method were presented to extract the modal parameters of the structure induced by ambient vibration.The measured signals were first decomposed into several intrinsic mode functions(IMF) and each IMF represents a modal response where a natural frequency is dominated.The decomposed data were then used as the input of STD method,complex index method and ARMA method to identify the modal parameters.A case study of a four-story steel frame model ambient vibration experiment had demonstrated that the proposed methods could overcome the difficulty of mode mixing and reduce the noise effect.The methods make the system modal parameters identification more clear and easier.
The system modal parameters identification under ambient excitation becomes the focus of the structural health monitoring.Empricalmode decomposition(EMD) based STD method,complex index method and ARMA method were presented to extract the modal parameters of the structure induced by ambient vibration.The measured signals were first decomposed into several intrinsic mode functions(IMF) and each IMF represents a modal response where a natural frequency is dominated.The decomposed data were then used as the input of STD method,complex index method and ARMA method to identify the modal parameters.A case study of a four-story steel frame model ambient vibration experiment had demonstrated that the proposed methods could overcome the difficulty of mode mixing and reduce the noise effect.The methods make the system modal parameters identification more clear and easier.
引文
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[7]徐晓霞,任伟新,韩建刚.基于响应协方差小波变换和SVD的结构工作模态参数识别[J].振动工程学报,2010,23(2):194-199(Xu Xiaoxia,Ren Weixin,HanJiangang.Operational modal parameter identification basedon covariancedriven wavelet transform and singular valuedecomposition[J].Journal of Vibration Engineering,2010,23(2):194-199(in Chinese))
[2]Huang C S,Hung S L,Wen C M,et al.A neural networkappoach for structural identification and diagnosis of abuilding from seismic response data[J].EarthquakeEngineering and Structural Dynamics,2003,32(2):187-206
[3]陈隽,徐幼麟,李杰.经验模分解及小波分析在结构损伤识别中的应用:试验研究[J].地震工程与工程振动,2007,27(1):110-116(Chen Jun,Xu Youlin,Li Jie.Structural damage detection using empirical modedecomposition and wavelet analysis:experimentalinvestigation[J].Journal of Earthquake Engineering andEngineering Vibration,2007,27(1):110-116(inChinese))
[4]Ren W X,Zong ZH.Output-only modal parameteridentification of civil engineering structures[J].StructuralEngineering and Mechanics,2004,17(3/4):429-444
[5]李海龙.环境激励下结构模态参数识别方法研究[D].重庆:重庆大学,2012(Li Hailong.Research on methodsof structural modal parameter identification under ambientexcitation[D].Chongqing:Chongqing University,2012(in Chinese))
[6]韩建平,李达文,王飞行.基于Hilbert-Huang变换和随机子空间识别的模态参数识别[J].地震工程与工程振动,2010,30(1):53-59(Han Jianping,Li Dawen,WangFeixing.Modal parameter identification based on Hilbert-Huang transform and stochastic subspace identification[J].Journal of Earthquake Engineering and EngineeringVibration,2010,30(1):53-59(in Chinese))
[7]徐晓霞,任伟新,韩建刚.基于响应协方差小波变换和SVD的结构工作模态参数识别[J].振动工程学报,2010,23(2):194-199(Xu Xiaoxia,Ren Weixin,HanJiangang.Operational modal parameter identification basedon covariancedriven wavelet transform and singular valuedecomposition[J].Journal of Vibration Engineering,2010,23(2):194-199(in Chinese))
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