Identification of multi-fault in rotor-bearing system using spectral kurtosis and EEMD
Author:
Publisher
JVE International Ltd.
Subject
Mechanical Engineering,General Materials Science
Link
http://www.jvejournals.com/Vibro/fulltextpdf/JVE-18671.pdf
Reference18 articles.
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2. Miao Q., Wang D., Pecht M. A probabilistic description scheme for rotating machinery health evaluation. Journal of Mechanical Science and Technology, Vol. 24, 2010, p. 2421-2430.
3. Lal M., Riwari R. Multi-fault identification in simple rotor-bearing-coupling systems based on forced response measurements. Mechanism and Machine Theory, Vol. 51, 2012, p. 87-109.
4. Zhang D. C., Yu D. J. Multi-fault diagnosis of gearbox based on resonance-based signal sparse decomposition and comb filter. Measurement, Vol. 103, 2017, p. 361-369.
5. Liu Z. W., Wei G., Hu J. H., Ma W. S. A hybrid intelligent multi-fault detection method for rotating machinery based on RSGWPT. KPCA and Twin SCM, Vol. 66, 2017, p. 249-261.
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