Rolling Bearing Performance Degradation Prediction Based on FBG Signal-Reference-Cited by-同舟云学术

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Rolling Bearing Performance Degradation Prediction Based on FBG Signal

Published:2021-11-01 Issue:21 Volume:21 Page:24134-24141
ISSN:1530-437X
Container-title:IEEE Sensors Journal
language:
Short-container-title:IEEE Sensors J.

Author:

Chen Yong^ORCID,Li Yuhuan,An Wangyue,Liu Huanlin^ORCID,Jiang Tao

Funder

National Nature Science Foundation of China

Chongqing Graduate Student Science Research Innovation of China

Chongqing Key Technology Innovation Project

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Instrumentation

Link

http://xplorestaging.ieee.org/ielx7/7361/9594098/09539205.pdf?arnumber=9539205

Cited by 10 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. A novel framework based on two-stage multi-view feature optimization and improved support vector data description for aeroengine bearing early fault detection;Reliability Engineering & System Safety;2024-05

2. 1D-SCRN: a novel approach for industrial machinery performance degradation trend prediction;Journal of the Brazilian Society of Mechanical Sciences and Engineering;2023-10-17

3. An integrated network architecture for data repair and degradation trend prediction;Mechanical Systems and Signal Processing;2023-10

4. A Data Augmentation Boosted Dual Informer Framework for the Performance Degradation Prediction of Aero-Engines;IEEE Sensors Journal;2023-06-01

5. Research on an early warning method for bearing health diagnosis based on EEMD-PCA-ANFIS;Electrical Engineering;2023-04-21

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