采用EEMD和WPT的结构损伤特征提取方法

为了解决传统小波或小波包变换方法对结构损伤振动信号频率分辨率不高、易受邻近谐波交叠影响的问题,提出了一种基于聚类经验模式分解(EEMD)和小波包变换(WPT)的结构损伤特征提取方法.首先对原始信号进行EEMD分解,提取包含结构损伤信息的固有模式分量(IMF),再对其进行正交小波包分解,并计算小波包相对能量分布.该方法用于美国土木工程师学会(ASCE)提出的钢结构框架的损伤特征提取,结果表明:EEMD方法具有白噪声的剔除特性,可避免模式混叠的发生；不同检测节点处不同损伤工况的IMF小波包相对能量分布有显著的差异,可以作为一种理想指标表征结构损伤特征.

Structure Damage Feature Extraction Based on EEMD and WPT

To overcome the limitations of low frequency resolution and interference of aliasing distortion of neighboring harmonic in the structure vibration signal analysis using wavelet transform(WT) or wavelet packet transform(WPT),a new damage feature extraction method is developed based on Ensemble Empirical mode decomposition(EEMD) and WPT.The response signals of the ASCE benchmark structure are processed by using EEMD,the intrinsic mode function(IMF) containing structural damage information are selected.Then,the selected IMF is decomposed by orthogonal WPT,and wavelet package energy(WPE) on decomposition frequency bands is calculated to represent the structure condition.The method is used to extract damage feature of the steel frame presented by the American Society of Civil Engineers(ASCE).The main results are summarized as follows: EEMD methods by using the eliminating characteristics of white noise can avoid the occurrence of mode mixing.For different kinds of damage,their WPE distributions are different with each other,and for a special damage,the distributions of WPE are different at the different detection nodes,thus it can be used as an ideal target for structural damage characteristics.