Diagnosis of rolling element bearing fault arising in gearbox based on sparse morphological component analysis
Author:
Publisher
JVE International Ltd.
Subject
Mechanical Engineering,General Materials Science
Link
http://www.jvejournals.com/Vibro/fulltextpdf/JVE-17265.pdf
Reference21 articles.
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3. Inalpolat M., Kahraman A. A theoretical and experimental investigation of modulation sidebands of planetary gear sets. Journal of Sound and Vibration, Vol. 323, 2009, p. 677-696.
4. McFadden P. D., Smith J. D. Explanation for the asymmetry of the modulation sidebands about the tooth meshing frequency in epicyclic gear vibration. Proceedings of the Institution of Mechanical Engineers Part C Mechanical Engineering Science, Vol. 199, 1985, p. 65-70.
5. Bin G. F., Gao J. J., Li X. J. Early fault diagnosis of rotating machinery based on wavelet packets-empirical mode decomposition feature extraction and neural network. Mechanical System and Signal Processing, Vol. 27, 2012, p. 696-711.
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1. Compound Faults Feature Extraction for Rolling Bearings Based on Parallel Dual-Q-Factors and the Improved Maximum Correlated Kurtosis Deconvolution;Applied Sciences;2019-04-23
2. Fault diagnosis method based on integration of RSSD and wavelet transform to rolling bearing;Measurement;2019-01
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