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Probabilistic Bearing Fault Diagnosis Using Gaussian Process with Tailored Feature Extraction
[article]
2021
arXiv
pre-print
Rolling bearings are subject to various faults due to its long-time operation under harsh environment, which will lead to unexpected breakdown of machinery system and cause severe accidents. Deep learning methods recently have gained growing interests and extensively applied in the data-driven bearing fault diagnosis. However, current deep learning methods perform the bearing fault diagnosis in the form of deterministic classification, which overlook the uncertainties that inevitably exist in
arXiv:2109.09189v1
fatcat:2h76vbscc5b27jmwdv24eehg6i