A novel deep learning approach for intelligent fault diagnosis applications based on time-frequency images
Author:
Funder
Türkiye Bilimsel ve Teknolojik Araştirma Kurumu
Publisher
Springer Science and Business Media LLC
Subject
Artificial Intelligence,Software
Link
https://link.springer.com/content/pdf/10.1007/s00521-021-06668-2.pdf
Reference23 articles.
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3. Lei Y, Yang B, Jiang X, Jia F, Li N, Nandi AK (2020) Applications of machine learning to machine fault diagnosis: a review and roadmap. Mech Syst Signal Process 138:106587. https://doi.org/10.1016/j.ymssp.2019.106587
4. Hoang D-T, Kang H-J (2019) A survey on deep learning based bearing fault diagnosis. Neurocomputing 335:327–335. https://doi.org/10.1016/j.neucom.2018.06.078
5. Hinton GE, Salakhutdinov RR (2006) Reducing the dimensionality of data with neural networks. Science 313(5786):504–507. https://doi.org/10.1126/science.1127647
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