应用EMD分解下的Volterra模型提取机械故障特征

将混沌时间序列的Volterra模型引入到机械故障诊断中,提出了采用EMD与Volterra模型相结合的方法提取机械故障特征。该方法较传统的特征提取方法,具有提取特征明显,计算简单等优点。仿真实验表明,此法能够有效地提取特征参数。将其应用于机械转子故障特征提取中,取得了较为满意的结果。

Applying EMD decomposition of the Volterra model to extract mechanical fault feature

Will be chaotic time series prediction of Volterra into machinery fault diagnosis, made use of EMD and Volterra forecast parameters combination of singular value decomposition method to extract the characteristics of mechanical failure. This method is different from the traditional feature extraction methods, with the extraction of the characteristics of obvious advantages of simple calculation. The simulation signals and the actual signal test, the method can effectively extract the characteristics of mechanical failure.