组合切片分析在滚动轴承故障诊断中的应用研究

Abstract

通过对滚动轴承点蚀故障模型的研究,得到其二阶循环平稳特征,指出利用谱相关密度函数在循环频率域的信息,能够有效识别加性噪声干扰的点蚀故障类型,以此为依据提出了针对轴承局部故障识别的组合切片分析方法。该方法基于频域平滑循环谱估计算法,利用特征循环频率组对应的谱相关密度切片,通过切片间能量的对比判断轴承故障类型。组合切片分析计算效率较高,对噪声不敏感,在低信噪比信号特征识别中具有较大优势。文章最后通过来自实验台的内圈和外圈点蚀故障振动信号验证了该分析方法的有效性和实用性。

A statistical model of rolling element bearing with spot defect is studied.Theoretical analysis shows that vibration from rolling element bearing with local defect is a typical second-order cyclostationary phenomenon,and the information in the cyclic frequency domain is sufficient for fault diagnosis.Therefore,a specialized method for bearing local defect detection is brought forward,and it is named as C-SSCD.The new method employs spectral smoothing algorithm to evaluate character slices of spectral correlation density.Those slices show distinct energy distribution for different bearing faults that can be used for fault diagnosis.C-SSCD method possesses high efficiency and high resolution at the same time,and it also has the advantage of weak fault detection.Experimental result shows that our method is effective and practical.