Performance Evaluation of the Signal Processing Based Transfer Learning Algorithm for the Fault Classification at Different Datasets
Author:
Publisher
Springer Science and Business Media LLC
Subject
Mechanical Engineering,Mechanics of Materials,Safety, Risk, Reliability and Quality,General Materials Science
Link
https://link.springer.com/content/pdf/10.1007/s11668-023-01648-1.pdf
Reference15 articles.
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2. M.S. Rathore, S.P. Harsha, Roller bearing failure analysis using gaussian mixture models and convolutional neural networks. J Fail. Anal. Preven. 22, 1853–1871 (2022). https://doi.org/10.1007/s11668-022-01469-8
3. G. Ciaburro, Machine fault detection methods based on machine learning algorithms: a review. Math. Biosci. Eng. 19(11), 11453–11490 (2022)
4. H. Wang, J. Chen, G. Dong, Feature extraction of rolling bearing’s early weak fault based on EEMD and tunable Q-factor wavelet transform. Mech. Syst. Signal Process. 48(1–2), 103–119 (2014)
5. F. Jiang, Z. Zhu, W. Li, G. Zhou, G. Chen, Fault identification of rotor-bearing system based on ensemble empirical mode decomposition and self-zero space projection analysis. J. Sound Vib. 333(14), 3321–3331 (2014)
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