摘要
通过对图形化编程软件LabVIEW的二次开发实现了经验模态分解(EMD)算法,为利用LabVIEW构建振动信号分析系统提供了有利分析工具。根据滚动轴承故障产生机理和故障信号的振动特点,将此方法运用到对轴承故障信号的分解上,对分解出的高频本征模函数(IMF)做包络解调从而提取出故障信息,并通过对实际故障轴承数据的分析验证了此方法的有效性。
The EMD algorithm is implemented by further development on the graphics software： LabVIEW,offering a effective analysis tool to structure the vibration signal analysis system.According to the fault forming mechanisms of rolling bearing and the vibration feature of the fault signal,this method is used to the decomposition of rolling bearing fault signal and the method of envelope demodulation is used to the high frequency IMFs got by the decomposition to extract the fault information.The analytical result of actual fault bearing shows the efficiency of this method.
出处
《轴承》
北大核心
2011年第5期37-40,共4页
Bearing
