测控技术2013，Vol.32Issue(7)：15-18,22,5.
基于EEMD和变尺度随机共振的轴承故障诊断
Bearing Fault Diagnosis Based on EEMD and STSR
摘要
Abstract
A fault feature extraction method of rolling bearing based on ensemble empirical mode decomposition (EEMD) and scale-transformation stochastic resonance(STSR) is proposed.Firstly,the vibration signal with noise is adaptively anti-aliasing decomposed by EEMD to conduct intrinsic mode function (IMF) of different frequency bands.Then making the IMFs as the input of bi-stable system,the low frequency fault features signal is extracted by the step-changed numberical algorithm and the adjustment of the bi-stable system parameters.Finally,slice bi-spectrum is adopted to postprocess the output of the bi-stable system.Simulation analysis is performed to prove the characteristics of STSR,the analysis on measured signal of the rolling bearing in strong background noise shows that the approach can extract the weak fault features of rolling bearing with the full use of Gaussian white noise successfully.关键词
EEMD/STSR/滚动轴承故障/切片双谱Key words
EEMD/ STSR/ fault of rolling bearing/ slice bi-spectrum分类
数理科学引用本文复制引用
崔颖,赵军,赖欣欢..基于EEMD和变尺度随机共振的轴承故障诊断[J].测控技术,2013,32(7):15-18,22,5.基金项目
国家自然科学基金资助项目(10972207) （10972207）
