摘要
小波变换不仅具有良好的时频局部化特性,而且它的时域分辨率和频域分辨率随着分解尺度变化而变化.广义的小波分析包括多分辨率分析和小波包分析,本文采用小波分解和信号重构的方法,提起了噪声掩盖下滚动轴承振动信号中的故障信息,并计算出 406滚动轴承外圈故障下的故障特征频率,通过对比由公式求取的故障特征频率,从而对滚动轴承的故障进行诊断.
Besides the time-frequency localization, a wavelet transform is characteristic of the adjustable time-frequency resolution. In this text, a method of wavelet decomposing and signal reconstruction is proposed to extract shock signal from vibration signal of rolling bearing, which is concealed by noise. In addition, it explicated how to calculate the eigenfrequency based on a wavelet transform.
出处
《南昌大学学报（工科版）》
CAS
2005年第1期77-80,共4页
Journal of Nanchang University(Engineering & Technology)
基金
南昌大学基金资助项目(Z1988)
关键词
小波变换
故障诊断
数据采集
滚动轴承
特征频率
信号重构
wavelet transform
failure diagnosis
data collection
rolling bearing
eigenfrequency
signal reconstruction
