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针对传统小波阈值去噪所产生的Pseudo-Gibbs现象,已发展出各种改进的小波去噪方法,基于相关原则优化阈值方法就是其中的一种。介绍了该方法的原理,证明其优于传统阈值去噪的特性。与以往的对阈值进行改进不同,将形态小波用于信号处理当中,对轴承早期故障特征进行提取,并经过数据仿真和故障轴承实例分析,将该方法的去噪效果和基于相关原则优化阈值方法进行对比,验证了该方法的有效性和先进性。
Aiming at the Pseudo-Gibbs phenomenon caused by the traditional wavelet threshold denoising, various improved wavelet denoising methods have been developed. One of the methods is to optimize the threshold based on the correlation principle. The principle of the method is introduced, which proves its superiority to the traditional threshold denoising. Different from the previous improvement on the threshold, the morphological wavelet is used in the signal processing to extract the early fault features of the bearing. After data simulation and fault bearing example analysis, the de-noising effect and the threshold method based on the correlation principle are optimized The comparison shows that the method is effective and advanced.