摘要
针对轴承故障诊断中轴的转速变化影响振动信号提取的特点,将阶比分析法与总体平均经验模式分解方法相结合,提出一种研究轴承非平稳振动信号的故障诊断方法。对轴承的振动信号按传统的方法在时域上进行采样,通过计算阶比跟踪将其转化为角域上的准平稳信号,对上述角域信号进行总体平均经验模态分解得出包含故障信息的模态函数分量,并对该分量进行频谱分析。应用结果表明:该方法能够有效地提取出轴承的故障特征。
Aimed at the characteristics of fault vibration signals processes were affected by the variable speed of the bearing in fault diagnosis,a new fault diagnosis method combined of order tracking analysis with Ensemble Empirical Mode Decomposition （EE-MD） was proposed for studying of signals of unstable vibration of bearing. The bearing vibration signal was sampled at constant time increments traditionally,and computer order tracking was used to transform the data at constant angle increments in angle-domain. With the method of EEMD,the angle domain stationary signal was adaptively decomposed into a finite number of Intrinsic Mode Func-tion （IMF） containing fault information. Each IMF was analyzed by frequency spectrum. The application results show that this meth-od can effectively extract the fault characteristics of the bearing.
出处
《机床与液压》
北大核心
2014年第9期170-172,共3页
Machine Tool & Hydraulics
