现代制造工程Issue(8)：131-134,4.
基于 Gabor 变换降噪和盲信号分离的轴承故障诊断方法
Fault diagnosis of rolling bearings based on Gabor transform denoising and blind signals separation
李兴慧 1武友德 1李小汝1
作者信息
- 1. 四川工程职业技术学院机电工程系，德阳618000
- 折叠
摘要
Abstract
Early fault signals of a rolling bearing submerged in system noises is weak and difficult to identify .Fault diagnosis of rolling bearings based on Gabor transform denoising and Blind Signals Separation ( BSS) is proposed .Using the Gabor transform with good time-frequency resolution and the advantages of BSS for rolling bearing fault diagnosis ,the composite noise of system signals was eliminated with the Gabor transform algorithm ,the denoised signals were separated with the BSS algorithm ,then the fault signal characters were extracted .The experimental results showed that this method is successful in separating fault patterns for rolling bearing .关键词
Gabor变换/故障诊断/盲信号分离Key words
Gabor transform/fault diagnosis/blind signals separation分类
机械制造引用本文复制引用
李兴慧,武友德,李小汝..基于 Gabor 变换降噪和盲信号分离的轴承故障诊断方法[J].现代制造工程,2014,(8):131-134,4.
