摘要
论述了一种新的自适应时频分析方法——局域均值分解的基本原理和算法,并将该方法引入到滚动轴承故障诊断中,提出了一种基于局域均值分解的滚动轴承故障诊断方法,该方法先将一个故障信号自适应地分解成若干个具有一定物理意义的生产函数分量,然后求出每个PF分量的瞬时幅值和瞬时频率,从而获得故障信号的特征信息。试验结果验证了该方法的有效性。
The basic theory and algorithm of local mean decomposition （LMD） as a new adaptive time -frequency analysis method is discussed. The method is introduced into the fault diagnosis of wiling bearings and a new fault diagnosis method based on LMD is proposed. By means of the proposed method, the vibration signal can be decomposed into a set of product functions （PF） components with the certain physical meaning, then the instantaneous amplitude and froquency of each PF component can be deduced, thus the feature information can be obtained. The experiment result shows that this method proposed is effective.
出处
《轴承》
北大核心
2009年第9期48-52,共5页
Bearing
基金
国家自然科学基金(50775208)
河南省教育厅自然科学基金(2006460005
2008C460003)
关键词
滚动轴承
故障诊断
局域均值分解
时频分析
rolling bearing
local mean decomposition
fault diagnosis
time- frequency analysis
