一种基于EMD的共振解调改进方法

An Improved EMD-Algorithm-Based Resonance Demodulation Method

针对传统共振解调方法中共振频带需要人为确定和故障轴承振动信号信噪比低的缺陷,提出了一种基于EMD算法的共振解调改进方法。该方法首先对轴承振动信号进行EMD分解,然后自适应地筛选出高频固有振动频率附近的基本模式分量(IMF),并对单分量进行滤波处理,最后重构选取滤波后的基本模式分量,并对重构信号进行包络解调分析,得到故障特征频率和故障类型。滚动轴承故障诊断表明,改进方法不仅能够自适应地确定共振频带,而且可以有效地提取故障特征,识别故障类型。

Aiming at overcoming the defects of the traditional resonance-demodulating method in manually determining the resonance frequency band and the lower ratio of signal to noise in the course of the fault diagnosis of the bearing,proposed in the paper is a new improved,EMD-algorithm-based resonance-demodulating method,where the original vibration signal is first decomposed into the Intrinsic Mode Function in the light of EMD.Then,the IMF containing natural vibration frequencies are adaptively selected and these IMF are filtered.Finally,the processed IMF are reconstructed,enveloping-demodulation analyzed and the characteristic frequency and the defect type are obtained.Practice of the Fault Diagnosis of the rolling bearing shows that the improved method can not only adaptively determine the resonance frequency band,but also identify the type of the fault and extract fault features effectively.