The LPST-Net: A new deep interval health monitoring and prediction framework for bearing-rotor systems under complex operating conditions-Reference-Cited by-同舟云学术

The LPST-Net: A new deep interval health monitoring and prediction framework for bearing-rotor systems under complex operating conditions

Published:2024-10 Issue: Volume:62 Page:102558
ISSN:1474-0346
Container-title:Advanced Engineering Informatics
language:en
Short-container-title:Advanced Engineering Informatics

Author:

Yang Tongguang,Li Guanchen,Li Kaitai,Li Xiaoyong^ORCID,Han Qingkai

Funder

Guangdong Province Laboratory of Advanced Manufacturing Science and Technology

National Natural Science Foundation of China

Publisher

Elsevier BV

Reference60 articles.

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3. State-space modeling and novel entropy-based health indicator for dynamic degradation monitoring of rolling element bearing;Kumar;Reliab. Eng. Syst. Saf.,2022

4. A real-time adaptive model for bearing fault classification and remaining useful life estimation using deep neural network;Gupta;Knowl.-Based Syst.,2023

5. Deep transfer learning-based hierarchical adaptive remaining useful life prediction of bearings considering the correlation of multistage degradation;Zhang;Knowl.-Based Syst.,2023

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