形态学滤波方法改进及其在滚动轴承故障特征提取中的应用

滚动轴承是旋转机械设备的重要部件,对滚动轴承的故障诊断研究具有重要的意义。滚动轴承故障会导致振动信号中出现冲击响应成分,可通过对冲击响应成分的周期的检测与提取,进行局部故障诊断。在分析形态学滤波方法的基础上,提出机构结构元素(SE)选择方法,并用于振动信号中冲击响应特征的提取。通过对仿真信号的处理验证了该方法的有效性,并将该方法用于轴承外圈、内圈局部故障状态下的特征的检测,结果表明该方法能有效提取周期性脉冲成分并抑制噪声。

An improved morphological filtering method and its application in bearing fault feature extraction

Rolling element bearings are one of the most important components in rotary machines and the fault diagnosis of bearing is of great significance.Localized defects in bearings tend to arouse periodical impulsive vibration,and the diagnosis of the bearing can be realized by detecting and extracting the impulsive components.Based on the structural characteristics of the signals,an improved morphological filtering method is proposed for periodical impulsive signal feature extraction..The performance of the proposed method is validated by both simulated impulsive signal and vibration signals of defective rolling bearing with outer and inner faults.The result shows that the proposed method is effective in extracting periodic impulses and suppressing the noises of vibration signals.