摘要
简述小波包分析的基本原理及其用于特征提取的机理,利用小波包将车床噪声信号分解到不同的频带内,并提取各频带能量作为特征向量,然后利用灰色故障诊断理论进行关联度分析,可快速准确地定位车床主轴箱噪声源。通过对实测信号的分析,证明了该方法的有效性。
This paper introduces the basic principle of wavelet packet analysis and its application for feature extraction. The lathe noise signal was decomposed to a different frequency band by using wavelet packets, and then the energy in different frequency band was extracted to use as features vector. Then make grey relational analysis by using grey fault diagnosis theory, which quickly and accurately locates the lathe head- stock noise source. The validity of this method has been proved by the analysis on the actual signal.
出处
《制造技术与机床》
CSCD
北大核心
2008年第9期62-64,共3页
Manufacturing Technology & Machine Tool
关键词
小波包
灰色理论
车床
噪声信号
Wavelet Packet
Grey Theory
Lathe
Noise Signal
