基于EMD和HT时频分析方法的滚动轴承故障诊断

针对滚动轴承故障信号的非线性非平稳特征,提出一种基于EMD和HT的时频分析方法。首先对滚动轴承振动信号进行经验模态分解,然后对分解后的固有模态函数分量作希尔波特变换,得到各分量的时频图,清晰直观地显示出信号的时频分布,从而比较方便地从混有背景信号和噪声的振动信号中提取轴承故障信息。通过现场应用,证明了该方法的有效性。

Study of fault diagnosis of rolling bearings based on empirical mode decomposition and Hilbert transformation time-frequency analysis method

According to the non-stationary and non-linear characteristic of the fault signal of rolling bearing,a time-frequency analysis method based on empirical mode decomposition and Hilbert transformation is put forward in this paper.First of all,the original signals are decomposed into a finite number of stationary intrinsic mode functions(IMFs),which are then applied to Hilbert transformation.The result of the method is the time-frequency spectrum of every IMF.The time-frequency distributing characteristic can be clearly shown and the fault characteristic information can be easily extracted from the vibration signals mixed with background signal and noise.The field application proves the effectiveness of the method.