Machine diagnosis with independent component analysis and envelope analysis
作者
Li Li,Liangsheng Qu
标识
DOI:10.1109/icit.2002.1189377
摘要
A novel method, integration of independent component analysis (ICA) and envelope analysis (EA), is proposed to diagnose machine sound sources. Microphones measure the acoustic signals. In ICA implementing, the auto-covariance of signals replaces the mixing signal and the three components are separated. Further ICA is applied the data between strikes of the machine, another component is obtained. EA extracts the sounds of machine from these separated components. Applications indicate that ICA can be used to recover the embedded information and improve the diagnosis.