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Feature Extraction of Acoustic Signals Based on Complex Morlet Wavelet

โœ Scribed by Ping He; Pan Li; Huiqi Sun


Book ID
119353540
Publisher
Elsevier
Year
2011
Tongue
English
Weight
259 KB
Volume
15
Category
Article
ISSN
1877-7058

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FEATURE EXTRACTION BASED ON MORLET WAVEL
โœ JING LIN; LIANGSHENG QU ๐Ÿ“‚ Article ๐Ÿ“… 2000 ๐Ÿ› Elsevier Science ๐ŸŒ English โš– 243 KB

The vibration signals of a machine always carry the dynamic information of the machine. These signals are very useful for the feature extraction and fault diagnosis. However, in many cases, because these signals have very low signal-to-noise ratio (SNR), to extract feature components becomes di$cult

VIBRATION SIGNAL ANALYSIS AND FEATURE EX
โœ Z. PENG; F. CHU; Y. HE ๐Ÿ“‚ Article ๐Ÿ“… 2002 ๐Ÿ› Elsevier Science ๐ŸŒ English โš– 354 KB

The wavelet scalogram has been widely used for vibration signal analysis, but it has low frequency concentration at small scales and low time concentration at large scales owing to the limitation of Heisenberg}Gabor inequality. In addition, misleading interference terms would appear in the scalogram