Bearing Degradation Prediction by WPD and DPNN: Introducing a Novel Deep Learning Method-Reference-Cited by-同舟云学术

Bearing Degradation Prediction by WPD and DPNN: Introducing a Novel Deep Learning Method

Published:2023-01 Issue:1 Volume:9 Page:18-24
ISSN:2333-942X
Container-title:IEEE Systems, Man, and Cybernetics Magazine
language:
Short-container-title:IEEE Syst. Man Cybern. Mag.

Author:

Hong Sheng¹^ORCID,Duan Xiaochuan²,Peng Yao³,Liu Hao⁴^ORCID,Zio Enrico⁵

Affiliation:

1. Professor, Nanchang University, Nanchang, China

2. School of Automation Science and Electrical Engineering, Beihang University, Beijing, China

3. Project Management Director, Beijing AndiSec Technology Co. Ltd, Beijing, China

4. School of Astronautics, Beihang University, Beijing, China

5. Department of Nuclear Engineering, Kyung Hee University, Milano, Italy

Funder

Beijing Natural Science Fund-Haidian Original Innovation Joint Fund

Industrial Internet Innovation and Development Project

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Computer Networks and Communications,Computer Science Applications,Human-Computer Interaction,Human Factors and Ergonomics,Control and Systems Engineering

Link

http://xplorestaging.ieee.org/ielx7/6745853/10014542/10014587.pdf?arnumber=10014587

Reference21 articles.

1. Deep Machine Learning - A New Frontier in Artificial Intelligence Research [Research Frontier]

2. Deep learning

3. An Improved Empirical Wavelet Transform and Its Applications in Rolling Bearing Fault Diagnosis

4. Using multi-sensor data fusion for vibration fault diagnosis of rolling element bearings by accelerometer and load cell

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2. Remaining Useful Life Prediction Method for the Rolling Element of an Electrical Machine Using Linear Regression Analysis of the Vibration Signal of a Faulted Bearing;2023 15th International Conference on Electronics, Computers and Artificial Intelligence (ECAI);2023-06-29