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《Journal of Xi'an Jiaotong University》 2003-01
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Independent Component Analysis for Features Extraction of Machine Condition

Li Li,Qu Liangsheng(School of Mechanical Engineering, Xi′an Jiaotong University, Xi′an 710049, China)  
Aimed at the acoustic signals from heavy sizingpress and rolling bearing rig, a preprocessing of autocorrelation for independent component analysis (ICA) is proposed. The preprocessing obviously stands out the nonGaussianity of the individual components in the signals to satisfy the ICA condition, i.e. statistical independence of sources. The fast ICA algorithm based on kurtosis is applied successfully to separate the signals, and some valuable sound sources and the corresponding machine parts are extracted. The results demonstrate that for ICA the correct preprocessing according to signal structure contributes to extracting features from mechanical signals effectively.
【CateGory Index】: TP14
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