基于EEMD与FastICA的损伤异常识别与定位

姜绍飞,陈志刚,沈清华,吴铭昊,麻胜兰

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

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PDF(3158 KB)
振动与冲击 ›› 2016, Vol. 35 ›› Issue (1) : 203-209.
论文

基于EEMD与FastICA的损伤异常识别与定位

  • 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
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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.
 

关键词

总体平均经验模态分解 / 快速独立分量分析 / 损伤定位 / 源分布向量

Key words

EEMD / FastICA / Damage location / NSDV

引用本文

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

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