【摘要】 滚动轴承是旋转机械中最常用的零件,它也是最容易损坏的零件之一。滚动轴承的质量直接影响整个机械系统的运行。采用经验模态分解(Empirical Mode Decomposition,EMD)与Hilbert变换相结合的HHT(Hilbert-Huang Transform)方法,对滚动轴承的故障机理和故障特征进行分析。通过实际应用与传统的时域分析、频谱分析方法相比较,该方法更能提取滚动轴承故障特征,并且所得结果与理论上滚动轴承的故障特征是一致的,因此,HHT方法对滚动轴承故障诊断是有效的、可行的。更多还原

【Abstract】 Rolling bearing is the most commonly used component in the rotating machinery and is one of the most easily damaged components.The quality’s badness or goodness of rolling bearing can directly influence the running of the whole machinery system.Adopts the integration of EMD and Hilbert transform.And it analyses the fault mechanism and fault characteristics of rolling bearing.By the practical application and the comparison between the traditional time-domain analysis and spectrum analysis.Means can better extract the fault characteristics of rolling bearing.And result is uniform with the fault characteristics of rolling bearing from theory.And so the HHT method is effective and feasible on the fault diagnosis of rolling bearing.更多还原