中文摘要：

将小波半软阈值法和经验模态分解（EMD）结合，提出了基于小波半软阈值的经验模态分解降噪方法。该方法首先利用小波半软阈值法减少随机噪声干扰，减小经验模态分解的分解层数及边缘效应的影响，然后进行适当的经验模态分解相关度消噪后处理，在有效降噪的同时较好地保存了原信号的有用信息。仿真和实验结果表明，该方法可实现噪声环境下旋转机械故障特征的有效提取，从而实现故障诊断。

英文摘要：

A de-noising method was proposed based on combined semi--soft wavelet threshold and EMD. Firstly,the semi-soft wavelet threshold method was applied to reduce the random noise. At the same time,it could reduce the decomposition layers and end effect of the EMD. Then, EMD was performed properly on de-noising post-processing aiming at de-nosing and preserving useful infor- mation. The simulation and experimental results show that this method can extract fault features of the rotating machinery effectively so as to realize the fault diagnosis.