NSMD和LMSST相结合的变转速滚动轴承故障诊断方法

Fault Diagnosis Method of Variable Speed Rolling Bearings Combined with NSMD and LMSST

为了能够准确反映变转速工况下滚动轴承的时变故障特征,本文提出了一种基于非线性稀疏模态分解(NSMD)和局部最大值同步压缩变换(LMSST)的故障诊断方法。首先利用NSMD对含噪振动信号进行分解,基于各分量的频谱最大相关性进行有用分量的选择;然后对其进行LMSST分析,从时频平面中提取时变故障特征,从而实现变转速下轴承故障诊断。

In order to accurately reflect the time-varying fault characteristics of rolling bearings under variable speed conditions, a new fault diagnosis method based on Nonlinear Sparse Mode Decomposition(NSMD) and Local Maximum Synchrosqueezing Transform(LMSST) is proposed in this paper. Firstly, the noisy vibration signal of rolling bearings is decomposed by NSMD, and the useful components are selected based on the maximum spectral correlation of each component;Then these useful components are treated again though LMSST analysis, and the time-varying fault features are extracted from the time-frequency plane, so as to realize the bearing fault diagnosis under variable speed conditions.