谐波小波滤波与HHT在轴承故障诊断中的应用  

Application of Harmonic Wavelet Filtering and HHT in Fault Diagnosis for Bearings

作　　者：臧怀刚[1] 王石云[1] 王冀龙[1] 

机构地区：[1]燕山大学电气工程学院工业计算机控制工程河北省重点实验室,河北秦皇岛066004

出　　处：《轴承》2014年第9期44-47,共4页Bearing

基　　金：国家杰出青年科学基金项目(61225019)

摘　　要：谐波小波具有良好的盒形频谱特性,可以将非平稳振动信号既不交叠又无遗漏地分解到相互独立的频带上。将谐波小波作为滤波器,可以将特定频段的成分与信号的其他频率成分分离,进行重构后就能够提取出强背景噪声干扰下的特定信号频段成分,实现谐波小波滤波。然后,对故障敏感段信号进行HHT边际谱分析,并以边际谱的最大峰值作为特征向量判断轴承的工作状态和故障类型。The harmonic wavelet has a fine box-like spectral characteristics,which could decompose non-stationary vibration signal to independent frequency bands without any overlapping or leak.The harmonic wavelet is used as a fil-ter,the specific frequency band components is separated with other frequency components of signal.Then the specific signal frequency band component under strong background noise is abstracted after the reconstruction,the harmonic wavelet filtering is achieved.The Hilbert-Huang Transformation （HHT）marginal spectrum analysis is applied to the fault sensitive period of signal,and the maximal peak value of marginal spectrum is used as the characteristic vector to judge working state and fault type of bearings.

关 键 词：滚动轴承 故障诊断 谐波小波滤波 边际谱 

分 类 号：TH133.33[机械工程—机械制造及自动化] TP391[自动化与计算机技术—计算机应用技术]