摘要
局部均值分解(Local Mean Decomposition,LMD)将复杂的多分量信号自适应地分解为有限个乘积函数(PF)的和,在计算了各个分量的瞬时幅值(IA)和瞬时频率(IF)后,可以计算出基于LMD的边际谱。针对直接法求取瞬时频率存在端点误差大问题,提出一种改进的直接求取瞬时频率的方法;提出了基于LMD的边际谱的滚动轴承故障诊断方法,将该方法应用于实际滚动轴承故障诊断中,结果表明该方法能有效地提取出滚动轴承的故障特征频率,从而确定故障部位。
Local mean decomposition（LMD）can be used to decompose a complex multi-component signal into a linear combination of several product functions （PFs ）.After obtaining the instantaneous amplitudes and instantaneous frequencies of all PF components,the marginal spectrum based on LMD can be calculated.Aiming at the big error problem of the instantaneous frequency at end-points extracted with the direct method,an improved direct method was put forward.The marginal spectrum method based on LMD for rolling bearing fault diagnosis was proposed,and it was applied in actual rolling bearing fault diagnosis.The analysis results showed that the fault characteristic frequency can be extracted effectively,and the fault position can be determined.
出处
《振动与冲击》
EI
CSCD
北大核心
2014年第3期5-8,13,共5页
Journal of Vibration and Shock
基金
军队科研计划项目
关键词
局部均值分解
边际谱
滚动轴承
故障诊断
瞬时频率
local mean decomposition
marginal spectrum
rolling bearing
fault diagnosis
instantaneous frequency
