Contrastive Generative Replay Method of Remaining Useful Life Prediction for Rolling Bearings-Reference-Cited by-同舟云学术

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Contrastive Generative Replay Method of Remaining Useful Life Prediction for Rolling Bearings

Published:2023-10-01 Issue:19 Volume:23 Page:23893-23902
ISSN:1530-437X
Container-title:IEEE Sensors Journal
language:
Short-container-title:IEEE Sensors J.

Author:

Wang Tiancheng¹^ORCID,Guo Di²^ORCID,Sun Xi-Ming¹^ORCID

Affiliation:

1. Key Laboratory of Intelligent Control and Optimization for Industrial Equipment of Ministry of Education and the School of Control Science and Engineering, Dalian University of Technology, Dalian, China

2. School of Artificial Intelligence, Beijing University of Posts and Telecommunications, Beijing, China

Funder

National Natural Science Foundation of China

National Science and Technology Major Project

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Instrumentation

Link

http://xplorestaging.ieee.org/ielx7/7361/10269339/10234219.pdf?arnumber=10234219

Reference36 articles.

1. A Novel Convolution Network Based on Temporal Attention Fusion Mechanism for Remaining Useful Life Prediction of Rolling Bearings

2. Continual learning with recursive gradient optimization;liu;arXiv 2201 12522,2022

3. Remaining Useful Life Estimation for Rolling Bearings Using MSGCNN-TR

4. Recurrent convolutional neural network: A new framework for remaining useful life prediction of machinery

5. A BiGRU Autoencoder Remaining Useful Life Prediction Scheme With Attention Mechanism and Skip Connection

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