Deep learning models for predictive maintenance: a survey, comparison, challenges and prospects
Author:
Funder
European Union’s Horizon 2020 research and innovation programme
Provincial Council of Gipuzkoa
Publisher
Springer Science and Business Media LLC
Subject
Artificial Intelligence
Link
https://link.springer.com/content/pdf/10.1007/s10489-021-03004-y.pdf
Reference159 articles.
1. Ahmed HOA, Wong MLD, Nandi AK (2018) Intelligent condition monitoring method for bearing faults from highly compressed measurements using sparse over-complete features. Mech Syst Sig Process 99:459–477. ISSN 10961216. https://doi.org/10.1016/j.ymssp.2017.06.027
2. Al-Raheem KF, Abdul-Karem W (2011) Rolling bearing fault diagnostics using artificial neural networks based on Laplace wavelet analysis. Int J Eng Sci Technol 2(6). ISSN 2141-2820. https://doi.org/10.4314/ijest.v2i6.63730
3. Amarbayasgalan T, Jargalsaikhan B, Ryu KH (2018) Unsupervised novelty detection using deep autoencoders with density based clustering. Appl Sci (Switzerland) 8(9):1468. ISSN 20763417. https://doi.org/10.3390/app8091468
4. Anderlini E, Salavasidis G, Harris CA, Wu P, Lorenzo A, Phillips AB, Thomas G (2021) A remote anomaly detection system for slocum underwater gliders. Ocean Eng 236:109531. ISSN 0029-8018. https://doi.org/10.1016/j.oceaneng.2021.109531
5. Chao MA, Adey BT, Fink O (2021) Implicit supervision for fault detection and segmentation of emerging fault types with deep variational autoencoders. Neurocomputing 454:324–338. ISSN 0925-2312. https://doi.org/10.1016/j.neucom.2021.04.122
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