基于EEMD与FastICA的损伤异常识别与定位

PDF(3158 KB)

振动与冲击 ›› 2016, Vol. 35 ›› Issue (1) : 203-209.

论文

姜绍飞，陈志刚，沈清华，吴铭昊，麻胜兰

作者信息 +

Damage detection and location based on the EEMD-FastICA algorithm

Jiang Shao-Fei, Chen Zhi-Gang，Shen Qing-Hua, Wu Ming-Hao,Ma Sheng-Lan

Author information +

文章历史 +

摘要

为了准确地提取结构损伤异常信息，消除小波奇异值分解时存在需要特定的小波基和分解层数以及经验模态分解（EMD）方法存在诸如虚假模态混叠等问题，本文提出了一种基于改进的总体平均经验模态分解（EEMD）与快速独立分量分析（FastICA）相结合的提取结构损伤特征并进行识别与定位的新方法。首先，通过EEMD对结构动力响应信号进行预处理并用 FastICA提取出包含损伤信息的特征分量对结构响应异常进行识别和初步定位；然后，计算归一化的源分布向量(NSDV)的最大值，并根据该最大值精确定位结构损伤。最后，通过框架数值算例和试验进行了所提方法的验证，结果表明该算法能够较好地进行结构损伤异常的识别与定位。

Abstract

It is generally known that the wavelet decomposition requires specific wavelet basis functions and decomposition layers. Meanwhile there exit some problems in the empirical mode decomposition (EMD) such as false modes. To avoid the disadvantages above, this paper presents a method of structural damage detection and location based on the ensemble empirical mode decomposition (EEMD) and fast independent componentan analysis (FastICA) algorithm to accurately extract the structural damage novelty information. At first，the measured structural dynamic responses are preprocessed by EEMD，and then the FastICA algorithm is used to extract the feature components involving the damage information so as to detect the structural response anomalies and preliminary locate damage. After that, the maximum number of the normalized source distribution vector (NSDV) is computed to accurately locate the structural damage. To prove the validity of proposed method, a frame numerical example and a laboratory test are conducted, the results show that the proposed algorithm can successfully detect the instant and location of damage.

导出引用

姜绍飞，陈志刚，沈清华，吴铭昊，麻胜兰. 基于EEMD与FastICA的损伤异常识别与定位[J]. 振动与冲击, 2016, 35(1): 203-209

Jiang Shao-Fei, Chen Zhi-Gang，Shen Qing-Hua, Wu Ming-Hao,Ma Sheng-Lan. Damage detection and location based on the EEMD-FastICA algorithm[J]. Journal of Vibration and Shock, 2016, 35(1): 203-209

参考文献

[1]姜绍飞.结构健康监测-智能信息处理及应用[J].工程力学,2009,26(S2):184-212.
JIANG Shao-fei.Structural health monitoring intelligent information processing and application[J]. Journal of Engineering Mechanics,2009, 26(S2):1-7.
[2]高维成,刘伟,邹经湘.基于结构振动参数变化的损伤探测方法综述[J].振动与冲击, 2004, 23(4):1-7.
GAO Wei-cheng, LIU Wei, ZOU Jing-xiang. Damage detection methods through changes of vibration parameters: a summary review [J]. Journal of Vibration and Shock, 2004, 23(4): 1-7.
[3]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 Analytical method to civil engineering[J]. World Earthquake Engineering, 2003,19(2): 16-22.
[4]刘涛,李爱群,丁幼亮.小波分析在结构损伤识别中的应用[J].地震工程与工程振动,2008, 28(2):29-35.
LIU Tao, LI Ai-qun, DING You-liang. Application of wavelet analysis to structural damage identification[J]. Journal of Earthquake Engineering and Engineeing Vibration, 2008 ,24(2):
29-35.
[5]HUANG N E, SHEN Z, Long S R. A new view of nonlinear water waves: The Hilbert Spectrum1[J]. Annual Review of Fluid Mechanics, 1999, 31(1):417-457.
[6]WU Z H, Huang N E. Ensemble empirical mode decomposition: a noise-assisted data analysis method [J].Advances in Adaptive Data Analysis, 2009, 1: 1―41.
[7]Hyvärinen A and Oja E. Independent component analysis: a tutorial.Neural Networks[J], 2000, 13(45) : 411-430.
[8]Hyvarinen A. Fast and robust fixed-point for independent
component Analysis [J]. IEEE Transactions on Neural Networks, 1999,10(3):626—634.
[9]李富强,刘国华,吴志根.基于双谱和奇异值分解的结构损伤
试验[J].浙江大学学报(工版),2012,46(10):1872-1879.
LI Fu-qiang,LIU Guo-hua,WU Zhi-gen.Experimental study of structural damage based on bispectral analysis and singular value decomposition[J]. Journal of Zhejiang University, 2012, 46 (10): 1872-1879.
[10]郑近德,程军圣,杨宇.改进的 EEMD 算法及其应用研究[J].振动与冲击,2013,32(21) : 21-26.
ZHENG Jin-de,CHENG Jun-sheng,Yang Yu. Modified EEMD algorithm and its applications [J].Journal of Vibration and Shock,2013,32(21) : 21-26.
[11]Wu Z. Huang N E.Ensemble empirical mode decomposition: a noise assiste data analysis method[J]. Advances in Adaptive Data Analysis ,2009,1:1-41．
[12]Shimizu S, Hyvarinen A, Kano Y, et al. Discovery of non-gaussian linear causal models using ICA[J]. arXiv preprint arXiv.1413, 2012,129(3):273-282.
[13]路亮,龙源,钟明寿,谢全民. FastICA算法在低信噪比爆破振动信号信噪分离中的应用研究[J].振动与冲击,2012,31 (17):32-37.
LU Liang,LONG Yuan,ZhONG Ming-shou.Separating noise from ablasting vibration signal based on fastICA[J]. Journal of Vibration and Shock. 2012,31(17):32-37.
[14]Lei Y, He Z, Zi Y. EEMD method and WNN for fault diagnosis of locomotive roller bearings[J].Expert Systems with Applications, 2011, 38(6): 7334-7341.
[15]Jiang S F，Wu S Y and Dong L Q．Structural Damage Detection based on Improved Multi-Particle Swarm Coevolution Optimization Algorithm[J]. Mathematical Problems in Engineering，Vol.2014, Article ID 232763, 1-11