基于卡尔曼滤波的局部齿轮故障特征提取

Diagnosis Method of Local Gear Fault Based on Kalman Filtering

针对齿轮振动信号具有高噪声的特点,将卡尔曼滤波(Kalman filtering)引进齿轮故障诊断中,提出基于卡尔曼滤波的局部齿轮故障诊断的方法。采用卡尔曼滤波对加速度信号进行降噪处理,再利用局部均值分解将振动信号自适应地分解为若干个单分量信号,从而提取出齿轮故障特征。与只进行局部均值分解获得故障特征的方法对比,采用卡尔曼滤波降噪后提取出的故障特征更具有准确性。

According to the characteristics of gear vibration signals with high noise, the Kalman filter is introduced into gear fault diagnosis. This paper proposes local gear fault diagnosis method based on Kalman filter. De-noise processing of the acceleration signal is conducted by Kalman filter. Local mean decomposition is used to decompose the vibration signal into several single component signals in which the characteristics of gear fault can be extracted. The results show that the extracted fault feature using Kalman filter noise reduction is more accurate than local mean decomposition.Key words： gear; fault diagnosis; Kalman filtering; local mean decomposition