基于数学形态变换的转子故障特征提取方法

Fault Feature Extracting Method of Rotating Machinery Based on Mathematical Morphology

基于非线性数学形态变换提出旋转机械故障特征提取的新方法。由数学形态变换构成的形态滤波器可以有效地提取出信号的边缘轮廓以及形状特征,通过选取不同长度的形态结构元素,采用组合形态滤波器将旋转机械故障信号分解到不同频带上,故障信号被分解成基频成分、故障成分及高频噪声三部分,在分解过程中,信号长度没有减少,没有信息的丢失;将分解得到的故障成分单独提取出来进行分析,可以更准确描述故障特征;对实际碰摩故障信号进行形态学分解后,提取出故障成分,采用Hilbert-Huang变换(Hilbert-Huang transform,HHT)对分解前后的信号进行对比分析,验证了方法的有效性,表明基于形态变换的信号特征提取可以更准确刻画故障的非平稳特性,提高了分析效果,并具有计算简单、快速的优点。

The mathematical morphological analysis is a nonlinear method of digital signal processing.To extract fault feature of rotating machinery,a novel method proposed based on mathematical morphology.The morphological filter that constructed by mathematical morphological transform is able to identify the shape feature of the signa1.A combined morphology filter used in fault signal decomposition of rotating machinery,the original vibration signal is decomposed into fundamental component,fault component and noise component via different length of the morphology structure elements,the signal that containing fault information produced by rotor fault is extracted independently.The signal length and information are not lost during the decomposition procedure.A practical rubbing signal decomposed and the fault component extracted by the method,then Hilbert-Huang transform（HHT） adopted in the further comparing analysis,the results show that the fault feature is successfully extracted and non-stationary characteristics of fault described accurately,the effectiveness improved.It is also fast and simple in computational realization.