基于LCD和局部Hilbert边际能量谱的滚动轴承故障特征提取方法  

FAULT FEATURE EXTRACTION METHOD FOR ROLLER BEARINGS BASED ON LCD AND LOCAL HILBERT MARGINAL ENERGY SPECTRUM

作　　者：杨潘[1,2] 李东文[1,2] 曾鸣[1,2] 

机构地区：[1]湖南大学机械与运载工程学院 [2]湖南大学汽车车身先进设计制造国家重点实验室,长沙410082

出　　处：《机械强度》2015年第1期9-12,共4页Journal of Mechanical Strength

基　　金：国家自然科学基金(51075131;51175158);湖南省自然科学基金(11JJ2026)资助~~

摘　　要：在定义局部Hilbert边际能量谱的基础上,提出了一种基于局部特征尺度分解(Local characteristic-scale decomposition,LCD)和局部Hilbert边际能量谱的滚动轴承故障特征提取方法。采用LCD方法对滚动轴承原始振动信号进行分解得到若干内禀尺度分量(Intrinsic scale component,ISC),然后对各个ISC分量进行Hilbert解调得到信号的时频分布。根据信号时频分布中能量分布确定频率段的下限和上限频率,从而得到相应的局部Hilbert边际能量谱,计算该频率段内信号的能量并将其作为故障特征参数。实验分析结果表明,所提出的方法能有效地提取滚动轴承故障特征信息。Based on the definition of local Hilbert marginal energy spectrum, a fault feature extraction method for roller bearings is further proposed based on LCD and local Hilbert marginal energy spectrum. By using LCD, an original roiling bearing vibration signal could be adaptively decomposed imo a number of intrinsic scale components （ISC）, and then the time-frequency distribution （TFD） could be obtained by applying Hilbert demodulation to all the components. According to the distribution of the signal energy revealed by the TFD, a local Hilbert marginal energy spectrum could be acquired once the lower and upper limit frequency for the corresponding frequency band are determined. Then the signal energy over this frequency band could be computed subsequently and regarded as the fault feature parameter. The analysis results from rolling bearing vibration signals show that the proposed approach can effectively extract the fault feature information.

关 键 词：局部特征尺度分解 局部Hilbert边际 能量谱 能量 滚动轴承 故障诊断 

分 类 号：TH165.3[机械工程—机械制造及自动化]