多尺度柔性形态滤波在轴承故障诊断中的应用

针对经典的形态学滤波在取单一结构元素的情况下存在缺陷的问题,提出了一种基于多尺度柔性形态滤波的轴承振动信号滤波方法。多尺度柔性数学形态学在保留柔性形态学好的鲁棒性、滤除正负噪声和保留细节等优点的同时,进一步对其结构元素进行改进,以期获得更好的脉冲提取性能。将多尺度柔性形态滤波应用于轴承故障诊断,结果表明,其比经典的柔性形态滤波能更好地保留振动信号中的冲击脉冲,为轴承故障的进一步诊断打下基础。

Application of Multi-scale Soft Morphological Filter in Fault Diagnosis of Bearings

According to the deficiency of classical soft morphological filter(SMF) in keeping the signal′s pulse,a filtering method for bearing vibration signals is proposed based on multi-scale soft morphological filter(MSMF).At the time of keeping the advantages of SMF such as good robustness,filtering noise and keeping detail of the signal,the structure element are further improved to get better ability of extracting the impulse in the signal.Applying MSMF to the bearing fault diagnosis,the result shows that MSMF has better ability in keeping the shock impulse in the vibration signal which provides the foundation for further diagnosis of the bearing fault.