针对滚动轴承原始振动信号信噪比小,以及传统共振解调中带通滤波器参数选择难以确定,且依赖于人的主观经验的问题,提出一种基于局部均值分解和共振解调相结合的方法;该方法首先利用局部均值分解算法将振动信号分解成多个分量,再通过希尔伯特(Hilbert)变换获得各个分量的时频图,然后利用快速谱峭图算法自动确定带通滤波器的中心频率和带宽,最后对信号进行带通滤波和包络解调分析完成故障诊断.数字仿真信号和滚动轴承实验证明了该方法的有效性.%Aiming at the problem that the signal-to-noise ratio of the original vibration signal of rolling bearing was low and the parameter selection of band-pass filter in traditional resonance demodulation was difficult to determine and depend-ed on the subjective experience of human,a new method based on local mean decomposition and resonance demodulation was proposed. The vibration signal was decomposed into multiple components by local mean decomposition algorithm, then the time-frequency diagram of each component was obtained by Hilbert transform,then the center frequency and bandwidth of the band-pass filter were automatically determined by spectral spectrum algorithm. Filtering and envelope de-modulation were conducted for fault diagnosis. The digital simulation of the signal and rolling bearing experiments show the effectiveness of the method.
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