An Improved Generic Hybrid Prognostic Method for RUL Prediction Based on PF-LSTM Learning-Reference-Cited by-同舟云学术

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An Improved Generic Hybrid Prognostic Method for RUL Prediction Based on PF-LSTM Learning

Published:2023 Issue: Volume:72 Page:1-21
ISSN:0018-9456
Container-title:IEEE Transactions on Instrumentation and Measurement
language:
Short-container-title:IEEE Trans. Instrum. Meas.

Author:

Xue Ke¹^ORCID,Yang Jun¹^ORCID,Yang Ming²^ORCID,Wang Dagui³^ORCID

Affiliation:

1. School of Electric Power Engineering, South China University of Technology, Guangzhou, China

2. College of Physics and Optoelectronic Engineering, Shenzhen University, Shenzhen, China

3. School of Mechanical and Electrical Engineering, Anhui Jianzhu University, Hefei, China

Funder

Soft Science Research Project of Guangdong Province

National Natural Science Foundation of China

Basic and Applied Basic Research Foundation of Guangdong Province

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Instrumentation

Link

http://xplorestaging.ieee.org/ielx7/19/10012124/10057430.pdf?arnumber=10057430

Reference187 articles.

1. Towards multi-model approaches to predictive maintenance: A systematic literature survey on diagnostics and prognostics

2. Review of Hybrid Prognostics Approaches for Remaining Useful Life Prediction of Engineered Systems, and an Application to Battery Life Prediction

3. Prognostics and health management design for rotary machinery systems-reviews, methodology and applications;lee;Mech Syst Signal Process,2014

4. Remaining useful life estimation: review

5. A Comprehensive Review of Available Battery Datasets, RUL Prediction Approaches, and Advanced Battery Management

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