桥梁动力测试信号的自适应分解与重构
详细信息 本馆镜像全文    |  推荐本文 | | 获取馆网全文
摘要
针对桥梁结构动力测试信号噪声水平高、难以分离结构有效信号的特点,在总体平均经验模态分解方法和主成分分析的基础上,建立了自适应分解与重构方法。对经验模态分解结果的模态混叠现象进行深入分析,利用白噪声概率密度函数的均匀性对模态混叠模式一进行了改进,基于相关性分析改进了模态混叠模式二,改进后的分解方法在计算效率和分解精度上均有较大提升;随后对所有分解获得的固有模态函数进行多尺度主成分分析,实现降噪和选择并重构测试信号。分别用模拟信号和实际桥梁测试信号对所提方法的有效性进行了验证。结果表明:改进后的信号自适应分解和重构方法能在降噪的同时,有效地提取桥梁结构信息,可用于实际桥梁结构的动力测试分析中。
In order to extract structural information from bridge structural dynamic signals with high noise level,a novel adaptive decomposition and reconstruction method was proposed by combining the ensemble empirical mode decomposition( EEMD) method and the principal component analysis( PCA) method for the specific characteristics of bridge structural dynamic signals. Based on the in-depth analysis of mode mixing in results of empirical mode decomposition,the uniformity of probability density function of white noise was adopted to improve the pattern I of mode mixing,and the correlation analysis was used to ameliorate the pattern II of mode mixing,then the calculation efficiency and decomposition accuracy were upgraded greatly for the improved EEMD. The multi-scale principal components analysis was implemented for all of the intrinsic mode functions( IMFs) obtained with the improved EEMD to reduce noise and select IMFs. Moreover,the dynamic signals were reconstructed. The effectiveness of the proposed method was verified with both the simulated signals and testing signals from real bridge structures. The results showed that the proposed method can be used to decompose adaptively and denoise effectively the bridge dynamic signals with high noise,and extract accurately the structural information from the testing signals,furthermore,it is applicable for the dynamic testing analysis of real bridge structures.
引文
[1]Huang N,Attoh-Okine N O.The Hilbert-Huang transform in engineering[M].Boca Raton,USA:CRC Prese,2005.
    [2]Feldman M.Hilbert transform applications in mechanical vibration[M].John Wiley&Sons,Ltd.,2011.
    [3]Huang N E,Shen Z,Long S R.A new view of nonlinear water waves:the Hilbert spectrum[J].Annual Review of Fluid Mechanics,1999,31:417-457.
    [4]谭善文,秦树人,汤宝平.Hilbert-Huang变换的滤波特性及其应用[J].重庆大学学报,2004.27(2):9-12TAN Shan-wen,QIN Shu-ren,TANG Bao-ping.The filtering character of Hilbert-Huang transform and Its application[J].Journal of Chongqing University,2004.27(2):9-12.
    [5]Flandrin P,Rilling G,Gonclaves P.Empirical mode decomposition as a filter bank[J].IEEESig.Pros,2004(11):112-114.
    [6]Gledhill R J.Methods for investigating conformational change in bimolecular simulations[D].University of Southampton,2004:201.
    [7]Wu Zhao-hua,Huang N E.Ensemble empirical mode decomposition:a noise assisted data analysis method[J].Advances in Adaptive Data Analysis,2009,1(1):1-41.
    [8]陈仁祥,汤宝平,马婧华.基于EEMD的振动信号自适应降噪方法[J].振动与冲击,2012,31(15):82-86.CHEN Ren-xiang,TANG Bao-ping,MA Jing-hua.Adaptive de-noising method based on ensemble empirical mode decomposition for vibration signal[J].Journal of Vibration and Shock,2012,31(15):82-86.
    [9]陈隽,李想.运用总体经验模态分解的疲劳信号降噪方法[J].振动、测试与诊断,2011,31(1):15-20.CHEN Jun,LI Xiang.Application of ensemble empirical mode decomposition to noise reduction of fatigue signal[J].Journal of Vibrat ion,Measurement&Diagnosis,2011,31(1):15-20.
    [10]Terrien J,Marque C,Karlsson B.Automatic detection of mode mixing in empirical mode decomposition using nonstationarity detection:application to selecting IMFs of interest and denoising[J].EURASIP Journal on Advances in Signal Processing,2011,2011:37,doi:10.1186/1687-6180-2011-37.
    [11]单德山,李乔,付春雨,等.桥梁健康监测与损伤评估[M].北京:人民交通出版社,2011:25-78.
    [12]朱建平.应用多元统计分析[M].北京:科学出版社,2006:93-100.
    [13]Flandrin P,Gonalvés P,Rilling G.Detrending and denosing with empirical mode decompositions[C].Proceedings of the European Signal Processing Conference(EUSIPCO'04),Aalborg,Denmark,2004.
    [14]Aminghafari M,Cheze N,Poggi J M.Multivariate de-noising using wavelets and principal component analysis[J].Computational Statistics&Data Analysis,2006(50)2381-2398.
    [15]侯遵泽,杨文采.小波多尺度分析应用[M].北京:科学出版社,2012.
    [16]单德山,徐敏.数据驱动随机子空间算法的桥梁运营模态分析[J].桥梁建设,2011(06):16-21.SHAN Des-han,XU Min.Operational modal analysis of bridge structure based on data-driven stochastic subspace algorithm[J].Bridge Construction,2011(06):16-21.
    [17]陈文元.考虑桩土水耦合的大跨度斜拉桥地震响应与可靠度研究[D].成都:西南交通大学,2013:30-39.

版权所有:© 2023 中国地质图书馆 中国地质调查局地学文献中心