小波变换在轴承故障诊断中的应用  

Wavelet Transform Applied in Bearing Fault Diagnosis

作　　者：董志峰[1] 杨会甲[1] 杨大伟[1] 敬川[1] 王振飞[1] 李彬[1] 曲荣新 

机构地区：[1]中国矿业大学(北京)机电与信息工程学院,北京100083 [2]鹤岗广新机械有限责任公司,黑龙江鹤岗154100

出　　处：《煤矿机械》2013年第6期269-270,共2页Coal Mine Machinery

基　　金：中央高校基本科研业务费专项基金资助项目(2010YJ04)

摘　　要：针对轴承故障诊断中非平稳信号的特征提取问题,采用小波变换理论对其进行处理。构建了减速器轴承故障实验平台,采集了大量实验数据。通过滚动体点蚀的典型故障实验与小波变换处理及轴承故障频率分析,获取了该故障的特征频率参数,表明小波变换在非平稳信号处理方面的有效性。Wavelet transform theory was applied to deal with the problem of the non-stationary signal feature extraction in the bearing fault diagnosis.The test bed of bearing fault experiment was constructed,and a lot of experimental data was collected.After the typical fault experiment of the rolling element pitting and data treatment using wavelet transform,the fault characteristic frequency parameters were obtained,which verified the effectiveness of the wavelet transform used in non stationary signal treatment.

关 键 词：滚动轴承 故障诊断 小波分析 特征频率 

分 类 号：TH133.33[机械工程—机械制造及自动化]