Multiphase Degradation Modeling and Remaining Useful Life Prediction Considering Aleatory and Epistemic Uncertainty-Reference-Cited by-同舟云学术

Multiphase Degradation Modeling and Remaining Useful Life Prediction Considering Aleatory and Epistemic Uncertainty

Published:2023-11-15 Issue:22 Volume:23 Page:27757-27770
ISSN:1530-437X
Container-title:IEEE Sensors Journal
language:
Short-container-title:IEEE Sensors J.

Author:

Cao Xuerui¹^ORCID,Peng Kaixiang²^ORCID

Affiliation:

1. Key Laboratory of Knowledge Automation for Industrial Processes of the Ministry of Education, School of Automation and Electrical Engineering, University of Science and Technology Beijing, Beijing, China

2. Key Laboratory of Knowledge Automation for Industrial Processes of the Ministry of Education, School of Automation and Electrical Engineering, National Engineering Research Center for Advanced Rolling Technology, University of Science and Technology Beijing, Beijing, China

Funder

National Key Research and Development Program of China

National Natural Science Foundation of China

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Instrumentation

Link

http://xplorestaging.ieee.org/ielx7/7361/10316685/10286372.pdf?arnumber=10286372

Reference47 articles.

1. A review on machinery diagnostics and prognostics implementing condition-based maintenance

2. A Novel Lifetime Estimation Method for Two-Phase Degrading Systems

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

4. Remaining useful life prognostic method based on two-stage adaptive Wiener process;dong;ACTA Automatica Sinica,2022

5. A Hybrid Approach to Cutting Tool Remaining Useful Life Prediction Based on the Wiener Process

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1. Towards unified aleatory and epistemic uncertainty quantification for machinery health prognostic through sequential heteroscedastic Gaussian process regression;Advanced Engineering Informatics;2024-10

2. Degradation modeling and remaining life prediction for a multi-component system under triple uncertainties;Computers & Industrial Engineering;2024-09