基于高阶统计量的滚动轴承故障诊断方法  

Roller Bearing Fault Diagnosis Based on Higher-Order Statistics

作　　者：蔡剑华[1] 胡惟文[1] 王先春[1] 

机构地区：[1]湖南文理学院信息研究所,常德415000

出　　处：《振动．测试与诊断》2013年第2期298-301,342-343,共4页Journal of Vibration,Measurement & Diagnosis

基　　金：国家高技术研究发展计划("八六三"计划)资助项目(2006AA06Z105);湖南省"十一五"重点建设学科--光学基金资助项目;湖南文理学院博士启动资助项目;湖南省自然科学基金资助项目(12JJ4034)

摘　　要：针对滚动轴承故障振动信号易受高斯噪声影响的问题,从高阶统计量的理论入手,提出了由信号的高阶谱恢复功率谱。由恢复的功率谱提取故障特征信息的高阶统计量方法,建立了通过高阶谱恢复功率谱的数学模型,并对仿真数据和实测故障数据进行了分析。结果表明,利用高阶累积量对高斯噪声不敏感的特点,可实现高斯噪声下瞬态信号频率与功率谱的正确估计。与传统方法相比,本研究方法可以有效地提取滚动轴承故障特征,同时具有更高的分辨率。Based on the fact that the fault roller bearing signal is affected easily by Gauss noise,the fault diagnosis method based on the high-order statistics is proposed.This method uses higher-order spectra to reconstruct power spectra and extracts fault feature information with the reconstructed power spectra.A model is established using higher-order spectra to reconstruct power spectra.Meanwhile,analysis is conducted using the man-made data and recorded MT data.The results show that the presented method is superior to the traditional power spectral method in suppressing Gaussian noise and can extract more useful information.Compared with the traditional method,the analysis results from roller bearing signals with inner-race,out-race or bearing ball faults show that the diagnosis approach could extract fault characteristics effectively and its resolution is higher.

关 键 词：高阶统计量 滚动轴承 故障诊断 高斯噪声 

分 类 号：TH133.33[机械工程—机械制造及自动化] TH911.6