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Hilbert-Huang变换在滚动轴承故障诊断中的应用
引用本文:于德介,程军圣,杨宇.Hilbert-Huang变换在滚动轴承故障诊断中的应用[J].中国机械工程,2003,14(24):2140-2142.
作者姓名:于德介  程军圣  杨宇
作者单位:[1]湖南大学机械与汽车工程学院教授、博士研究生导师,长沙市410082 [2]湖南大学机械与汽车学院副教授、博士研究生 [3]湖南大学机械与汽车学院讲师、博士研究生
基金项目:国家自然科学基金资助项目(50275050),高等学校博士学科点专项科研基金资助项目(20020532024)
摘    要:提出了一种新的滚动轴承故障诊断方法——基于小波系数包络信号的局部Hilbert边际谱方法,在Hilbert—Huang变换的基础上介绍了局部Hilbert谱和局部Hilbert边际谱,并将它应用于滚动轴承的故障诊断中。用小波基将滚动轴承故障振动信号分解,对高频段的小波系数用Hilbert进行包络分析得到包络信号,再对包络信号进行Hilbert—Huang变换求出局部Hilbert边际谱,从局部Hilbert边际谱中就可以判断滚动轴承的故障部位和类型。通过对滚动轴承具有外圈缺陷、内圈缺陷的情况下的振动信号的分析,说明该方法比传统的包络分析方法更能有效地提取滚动轴承故障特征。

关 键 词:滚动轴承  Hilbert-Huang变换  局部Hilbert边际谱  小波基  包络分析  故障诊断
文章编号:1004-132X(2003)24-2140-03

Application of the Hilbert-Huang Transform Method to Roller Bearing Fault Diagnosis
Yu De jie,Cheng Junsheng,Yang Yu Hunan University,Changsha,China.Application of the Hilbert-Huang Transform Method to Roller Bearing Fault Diagnosis[J].China Mechanical Engineering,2003,14(24):2140-2142.
Authors:Yu De jie  Cheng Junsheng  Yang Yu Hunan University  Changsha  China
Abstract:Based upon the Hilbert -- Huang trans-form, a method for fault diagnosis of roller bearings wasproposed. The concepts of Iocal Hilbert spectrum and lo-cal Hilbert marginal spectrum were introduced. The or-thogonal bases of wavelet were used to translate vibrationsignals of a roller bearing into time -- scale representa-tion, then, an envelope signal could be obtained by enve-lope spectrum analysis of wavelet coefficients of highscales. By making Hilbert --Huang transform of the en-velope signal, we could get the local Hilbert marginalspectrum from which the faults in a roller bearing couldbe diagnosed and fault patterns could be identified. Prac-tical vibration signals acquired from roller bearings without -- race faults or inner -- race faults were analyzed bythe proposed method. The results show that the pro-posed method is superior to the traditional envelope spec-trum method in extracting the fault characteristics ofroller bearings.
Keywords:roller bearing  Hilbert-Huang transform  local Hilbert marginal spectrum  wavelet base  envelope analysis
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