A bearing vibration data analysis based on spectral kurtosis and ConvNet
Author:
Publisher
Springer Science and Business Media LLC
Subject
Geometry and Topology,Theoretical Computer Science,Software
Link
http://link.springer.com/content/pdf/10.1007/s00500-018-3644-5.pdf
Reference47 articles.
1. Amar M, Gondal I, Wilson C (2015) Vibration spectrum imaging: a novel bearing fault classification approach. IEEE Trans Ind Electron 62(1):494–502
2. Antoni J (2006) The spectral kurtosis: a useful tool for characterising non-stationary signals. Mech Syst Signal Process 20(2):282–307
3. Antoni J (2007) Fast computation of the kurtogram for the detection of transient faults. Mech Syst Signal Process 21(1):108–124
4. Antoni J, Randall R (2006) The spectral kurtosis: application to the vibratory surveillance and diagnostics of rotating machines. Mech Syst Signal Process 20(2):308–331
5. Arel I, Rose DC, Karnowski TP (2010) Deep machine learning—a new frontier in artificial intelligence research. IEEE Comput Intell Mag 5(4):13–18
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