Journal
SIGNAL PROCESSING
Volume 96, Issue -, Pages 118-124Publisher
ELSEVIER
DOI: 10.1016/j.sigpro.2013.05.013
Keywords
Spectral kurtosis; Signal transients; Time-frequency analysis; Morlet wavelet; Wavelet correlation filtering
Categories
Funding
- State Key Laboratory for Manufacturing Systems Engineering (Xi'an Jiaotong University) [sklms2011006]
- Natural science fund of Jiangsu Province [BK2010225]
- Perspective Research Foundation of Production Study and Research Alliance of Jiangsu Province of China [BY2012112]
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Spectral kurtosis (SK) provides a valuable tool for detecting the signal transients buried in noise, which makes it very powerful for designing a filter to extract the signal transients. However, SK requires the selection of a time-frequency frame for decomposition based on Short Time Fourier Transform (STFT). This paper presents an adaptive spectral kurtosis filtering technique to extract the signal transients based on Morlet wavelet. The Morlet wavelet is used as a filter bank whose center frequency is defined by the wavelet correlation filtering. Different bandwidth filter in the filter bank is used to select the optimal filter for extracting the signal transients as the one that maximizes the SK. Effectiveness of the proposed technique is verified through the transient extraction of a simulate signal. For the gear fault feature detection of vehicle transmission gearbox, the proposed technique is applied in the extraction of the signal transients that shows the gear fault, which proves the effectiveness of the proposed technique in extracting the signal transients in the practical application. (C) 2013 Elsevier B.V. All rights reserved.
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