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
โฆ LIBER โฆ
Feature Extraction of Acoustic Signals Based on Complex Morlet Wavelet
โ 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
No coin nor oath required. For personal study only.
๐ SIMILAR VOLUMES
FEATURE EXTRACTION BASED ON MORLET WAVEL
โ
JING LIN; LIANGSHENG QU
๐
Article
๐
2000
๐
Elsevier Science
๐
English
โ 243 KB
Feature extraction and recognition of UH
โ
Yanbin Xie; Ju Tang; Qian Zhou
๐
Article
๐
2009
๐
John Wiley and Sons
๐
English
โ 292 KB
VIBRATION SIGNAL ANALYSIS AND FEATURE EX
โ
Z. PENG; F. CHU; Y. HE
๐
Article
๐
2002
๐
Elsevier Science
๐
English
โ 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
Feature extraction based on the 3D spect
โ
F.Q. Wu; G. Meng
๐
Article
๐
2006
๐
Springer
๐
English
โ 595 KB
Wavelet-based feature extraction for imp
โ
Jiang Li
๐
Article
๐
2004
๐
IEEE
๐
English
โ 286 KB
Correction to "Wavelet-Based Feature Ext
๐
Article
๐
2004
๐
IEEE
๐
English
โ 30 KB