第二代小波分析在轴承故障诊断中的应用  

An Application of the Second Generation of Wavelet Transform in the Fault Diagnosis of Rolling Bearings

作　　者：高立新[1] 殷海晨[1] 张建宇[1] 胥永刚[1] 

机构地区：[1]北京工业大学,北京市先进制造技术重点实验室,北京100124

出　　处：《北京工业大学学报》2009年第5期577-581,共5页Journal of Beijing University of Technology

基　　金：国家自然科学基金项目(50705001)

摘　　要：针对传统小波分析在轴承冲击故障特征提取中的不足,引入第二代小波分析用于滚动轴承的故障诊断.基于插值细分原理,构造了预测算子和更新算子,并针对边界计算中出现的信号突变问题,采用一阶平滑边界延拓技术,解决了重构后信号的平滑问题.基于第二代小波分析的降噪方法,成功滤除噪声信号并保留故障的冲击特征,效果明显优于传统小波降噪技术.同时,将第二代小波变换与相关分析、解调分析等方法相结合,实现了轴承早期故障特征的有效提取.In dealing with the deficiency of traditional wavelet analysis in extracting fault feature of bearing, the second generation of wavelet transform(SGWT) is adopted in the fault diagnosis of bearing.The prediction operator and update operator of SGWT are constructed based on the interpolating subdivision principle.Furthermore,the first-order smoothing boundary constitution technology is used to solve the mutation problem in the calculating boundary.As a result,the reconstructed signal can be smoothed.The denoising technology based on SGWT can subtract the background noise to obtain the fault feature successfully,and the effect is much better than that of the traditional wavelet denoising.Finally,the incipient fault features have been extracted successfully by integrating the SWGT with correlation analysis and demodulation technology.

关 键 词：小波变换 二代小波变换 故障诊断 

分 类 号：TH17[机械工程—机械制造及自动化]