| EMD和小波变换在结构模态参数辨识中的应用 |
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| 引用本文： | 徐亚兰,马娟,陈建军,刘珍. EMD和小波变换在结构模态参数辨识中的应用[J]. 西安电子科技大学学报(自然科学版), 2012, 39(2): 186-191. DOI: 10.3969/j.issn.1001-2400.2012.02.031 |
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| 作者姓名： | 徐亚兰 马娟 陈建军 刘珍 |
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| 作者单位： | (西安电子科技大学 机电工程学院，陕西 西安710071) |
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| 基金项目： | 中央高校基本科研业务费专项资金资助项目(JY10000904012);国家863高技术研究发展计划资助项目(2006AA04Z402) |
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| 摘 要： | 针对希尔伯特-黄变换方法在振动信号处理中不能有效地进行模态解耦的缺点，提出一种将经验模式分解和小波变换相结合的结构模态参数辨识方法．首先利用经验模式分解方法对结构响应信号进行分解，获得多个本征模函数以完成结构模态的筛选过程，并根据模态筛选得到的本征模函数进行信号重构；然后对重构信号进行Morlet小波变换和模态解耦，获得信号小波变换系数的瞬时幅值和瞬时相位拟合曲线，并在此基础上计算出结构的各阶模态频率、阻尼和振型．结果表明，利用小波变换对本征模函数的叠加信号进行参数辨识代替对单个本征模函数进行希尔伯特变换，更能有效地进行模态解耦，从而获得更为准确的结构模态参数信息．
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| 关 键 词： | 模态参数辨识 经验模式分解 小波变换 模态解耦 |
| 收稿时间： | 2010-12-29 |
Application of empirical mode decomposition and wavelet transform in structural modal parameter identification |
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| XU Yalan,MA Juan,CHEN Jianjun,LIU Zhen. Application of empirical mode decomposition and wavelet transform in structural modal parameter identification[J]. Journal of Xidian University, 2012, 39(2): 186-191. DOI: 10.3969/j.issn.1001-2400.2012.02.031 |
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| Authors: | XU Yalan MA Juan CHEN Jianjun LIU Zhen |
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| Affiliation: | (School of Mechano-electronic Engineering, Xidian Univ., Xi'an 710071， China) |
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| Abstract: | To overcome the limitation of hilbert-huang transform in decoupling the structural modes in vibration signal processing,a novel structural modal parameter identification method is proposed by combining empirical mode decomposition(EMD) with Morlet wavelet transform.First,the dynamical response signal is decomposed by using the EMD method to achieve intrinsic mode functions and implement the sifting processing of modes,on the basis of which the signal is reconstructed.Then,the variation of the transient amplitude and phase of wavelet transform coefficients with time is given by using the Morlet wavelet and the least squares fit,on the basis of which corresponding modal frequencies and modal damping ratios and mode shapes are achieved.Simulation results show that the method is effective in modal decoupling and accurate in modal parameter identification,which can not be implemented effectively by using the Hilbert transform of the individual intrinsic mode function due to modal mixture. |
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| Keywords: | modal parameters empirical mode decomposition wavelet transform modal decoupling |
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