Title :
Machine diagnosis with independent component analysis and envelope analysis
Author :
Li, Li ; Qu, Liangsheng
Author_Institution :
Res. Inst. of Diagnostics & Cybern., Xi´´an Jiaotong Univ., China
Abstract :
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.
Keywords :
condition monitoring; fault diagnosis; independent component analysis; auto-covariance; envelope analysis; independent component analysis; machine diagnosis; Acoustic measurements; Acoustic signal processing; Biomedical signal processing; Cybernetics; Data mining; Frequency; Independent component analysis; Mechanical sensors; Microphones; Vibrations;
Conference_Titel :
Industrial Technology, 2002. IEEE ICIT '02. 2002 IEEE International Conference on
Print_ISBN :
0-7803-7657-9
DOI :
10.1109/ICIT.2002.1189377