基于EEMD的振动信号自适应降噪方法

摘 要：应用集合经验模式分解（Ensemble empirical mode decomposition ,EEMD）能有效抑制模态混叠的特性，根据白噪声经经验模式分解（Empirical mode decomposition, EMD）后其固有模式函数（intrinsic mode functions ，IMF）分量的能量密度与其平均周期的乘积为一常量这一特点设计了自动选择IMF分量重构信号的算法，提出了基于EEMD的振动信号自适应降噪方法。对仿真信号和滚动轴承振动信号的降噪结果表明了该降噪方法的可行性和有效性。

Adaptive de-noising method based on ensemble empirical mode decomposition for vibration signal

The ensemble empirical mode decomposition(EEMD) method can effectively suppress the phenomenon of mode mixing.When a white noise signal is decomposed by EMD,the product of the energy density of intrinsic mode function(IMF) component and its corresponding averaged period is a constant.According to these characters,an automatic algorithm of choosing IMF components to reconstruct signal was designed,and an adaptive de-noising method based on EEMD for vibration signal was proposed.A simulation signal and a bearing vibration signal were used for verification and the results show that the EEMD-based noise cancellation method presented here is feasible and valid.