噪声与振动控制2018，Vol.38Issue(2)：150-153,161,5.DOI:10.3969/j.issn.1006-1355.2018.02.029
一种自适应提取有效信号的滚动轴承故障诊断方法
A Fault Diagnosis Method for Rolling Bearings based on Adaptive Extraction of Effective Signals
邢欣 1崔亚辉 1刘晓琳 1王增杰 1李龙龙1
作者信息
- 1. 西安理工大学 机械与精密仪器工程学院,西安710048
- 折叠
摘要
Abstract
Currently,it is difficult to adaptively extract the effective signals from a large number of signals.This paper proposes a method to select the effective signals by combining wavelet packet decomposition with Shannon entropy.First of all, the wavelet packet decomposition is carried out on the faulty signals to calculate the band entropy to quantify the complexity of the signals.With the value of the entropy as the index,the frequency signal corresponding to the maximum entropy of the wavelet packet is found,which is used as the effective signal for reconstruction of the wavelet packet signal. Then, the reconstructed signal is decomposed by EMD and the obtained IMF component is analyzed by Hilbert envelope spectrum.Finally,the fault frequency is effectively separated and highlighted.Through the experimental study,it is shown that the method can effectively select the effective signal,which can guarantee the validity and intuition of the characteristic frequency of the bearing fault,and improve the real-time performance of the fault diagnosis.关键词
振动与波/故障诊断/自适应/小波包最大熵/EMD包络谱Key words
vibration and wave/fault diagnosis/adaptive/wavelet packet maximum entropy/EMD envelope spectrum分类
机械制造引用本文复制引用
邢欣,崔亚辉,刘晓琳,王增杰,李龙龙..一种自适应提取有效信号的滚动轴承故障诊断方法[J].噪声与振动控制,2018,38(2):150-153,161,5.
