基于集合经验模式分解和交叉能量算子的滚动轴承故障诊断

被引:9
作者
赵晓宁
冯志鹏
机构
[1] 北京科技大学机械工程学院
基金
中央高校基本科研业务费专项资金资助;
关键词
滚动轴承; 故障诊断; 交叉能量算子; 集合经验模式分解;
D O I
10.13374/j.issn2095-9389.2015.s1.011
中图分类号
TH165.3 [];
学科分类号
摘要
振动信号的周期性冲击及其重复频率是滚动轴承故障诊断的关键.本文提出了一种基于集合经验模式分解和交叉能量算子提取滚动轴承故障特征的方法.首先,应用集合经验模式分解方法将振动信号分解为本征模式函数以满足交叉能量算子对信号单分量的要求.然后根据相关程度和峭度从本征模式函数中选取敏感分量,计算敏感分量和原始信号的瞬时交叉能量及其傅里叶频谱.最后根据交叉能量的频谱结构和特征频率识别轴承故障.通过分析滚动轴承故障仿真信号和实验测试信号,诊断了滚动轴承元件故障,验证了该方法的有效性.
引用
收藏
页码:65 / 71
页数:7
相关论文
共 6 条
[1]
基于Teager能量算子的滚动轴承故障诊断研究 [J].
王天金 ;
冯志鹏 ;
郝如江 ;
褚福磊 .
振动与冲击, 2012, 31 (02) :1-5+85
[2]
An energy operator approach to joint application of amplitude and frequency-demodulations for bearing fault detection [J].
Liang, Ming ;
Bozchalooi, I. Soltani .
MECHANICAL SYSTEMS AND SIGNAL PROCESSING, 2010, 24 (05) :1473-1494
[3]
The application of energy operator demodulation approach based on EMD in machinery fault diagnosis [J].
Cheng Junsheng ;
Yu Dejie ;
Yang Yu .
MECHANICAL SYSTEMS AND SIGNAL PROCESSING, 2007, 21 (02) :668-677
[4]
A study of the characteristics of white noise using the empirical mode decomposition method [J].
Wu, ZH ;
Huang, NE .
PROCEEDINGS OF THE ROYAL SOCIETY A-MATHEMATICAL PHYSICAL AND ENGINEERING SCIENCES, 2004, 460 (2046) :1597-1611
[5]
Optimisation of bearing diagnostic techniques using simulated and actual bearing fault signals [J].
Ho, D ;
Randall, RB .
MECHANICAL SYSTEMS AND SIGNAL PROCESSING, 2000, 14 (05) :763-788
[6]
The empirical mode decomposition and the Hilbert spectrum for nonlinear and non-stationary time series analysis [J].
Huang, NE ;
Shen, Z ;
Long, SR ;
Wu, MLC ;
Shih, HH ;
Zheng, QN ;
Yen, NC ;
Tung, CC ;
Liu, HH .
PROCEEDINGS OF THE ROYAL SOCIETY A-MATHEMATICAL PHYSICAL AND ENGINEERING SCIENCES, 1998, 454 (1971) :903-995