小波理论在滚动轴承故障诊断中的应用  

Application of Wavelet Theory to Fault Diagnosis of Rolling Bearing

作　　者：李雅梅[1] 陈明霞[1] 杜晶[1] 

机构地区：[1]辽宁工程技术大学电气工程学院,葫芦岛125105

出　　处：《计算机系统应用》2012年第7期172-176,共5页Computer Systems & Applications

摘　　要：主要研究小波变换消噪的性能,以及循环自相关函数分析算法。在理论分析的基础上,对多组实测信号进行了基于小波阈值消噪的自相关函数分析,通过仿真结果,指出对自相关函数幅值进行谱分析,可有效提取出滚动轴承故障特征频率并抑制其他频率成分的干扰,仿真结果证明了该方法的有效性。This paper studies the performance of wavelet transform denoising,and the algorithm of Cyclic autocorrelation analysis.Based on theoretical analysis,it makes Cyclic Autocorrelation function analysis of the measured multiple signals based on wavelet threshold denoising.From the results of simulation,it is effective in extracting bearing fault characteristic frequency and suppress interference from other frequency components by the cyclic autocorrelation function amplitude spectrum.The simulation results demonstrate the effectiveness of the method.

关 键 词：小波 消噪 自相关 轴承 

分 类 号：TH165.3[机械工程—机械制造及自动化]