A component diagnostic and prognostic framework for pump bearings based on deep learning with data augmentation-Reference-Cited by-同舟云学术

A component diagnostic and prognostic framework for pump bearings based on deep learning with data augmentation

Published:2024-07 Issue: Volume:247 Page:110121
ISSN:0951-8320
Container-title:Reliability Engineering & System Safety
language:en
Short-container-title:Reliability Engineering & System Safety

Author:

Rivas Andy,Delipei Gregory Kyriakos^ORCID,Davis Ian,Bhongale Satyan,Yang Jinan,Hou Jason^ORCID

Funder

National Science Foundation

Advanced Research Projects Agency - Energy

U.S. Department of Energy

Publisher

Elsevier BV

Reference52 articles.

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3. McKee Kristoffer, et al. A review of major centrifugal pump failure modes with application to the water supply and sewerage industries. Western Australia: Curtin Universtiy.

4. Bearing performance degradation assessment using long short-term memory recurrent network;Zhang;Comput Ind,2019

5. Fault detection and identification method using observer-based residuals;Jeong;Reliab Eng Syst Saf,2019

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