An Intelligent Fault Diagnosis Method of Rolling Bearings Based on Short-Time Fourier Transform and Convolutional Neural Network
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/s11668-023-01616-9.pdf
Reference43 articles.
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3. I. González-Prieto, M.J. Duran, N. Rios-Garcia et al., Open-switch fault detection in five-phase induction motor drives using model predictive control. IEEE Trans. Ind. Electron. 65, 3045–3055 (2018)
4. D. Jung, C. Sundstrom, A combined data-driven and model-based residual selection algorithm for fault detection and isolation. IEEE Trans. Control Syst. Technol. 27, 616–630 (2017)
5. D.C. Zhu, Y.Y. Pan, W.P. Gao, Fault feature extraction of rolling element bearing under complex transmission path based on multiband signals cross-correlation spectrum. J. Fail. Anal. and Preven. 22, 1164–1179 (2022)
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