Abstract
Signals with multiple transients are often encountered with much noise in engineering. The transient feature extraction has always been the key issue for signal analysis. A new signal de-noising method combining sparse representation and Morlet wavelet basis is proposed for signal de-noising and feature extraction. Simulation study concerning multiple transients signal shows the effectiveness of this method in transient feature extraction. The efficiency of this de-noising method is also verified by its application to extract fault signature for gearbox.
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