Long short-term memory network with multi-resolution singular value decomposition for prediction of bearing performance degradation-Reference-Cited by-同舟云学术

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Long short-term memory network with multi-resolution singular value decomposition for prediction of bearing performance degradation

Published:2020-05 Issue: Volume:156 Page:107582
ISSN:0263-2241
Container-title:Measurement
language:en
Short-container-title:Measurement

Author:

He Mengfu,Zhou Youguang,Li Yang,Wu Gaofeng,Tang Gang

Funder

Open Fund of State Key Laboratory of Nuclear Power Safety Monitoring Technology and Equipment

Fundamental Research Funds for the Central Universities

China-Japan Friendship Hospital

Publisher

Elsevier BV

Subject

Applied Mathematics,Electrical and Electronic Engineering,Condensed Matter Physics,Instrumentation

Reference21 articles.

1. Prognostics and health management: a review of vibration based bearing and gear health indicators;Wang;IEEE Access,2018

2. Underdetermined blind separation of bearing faults in hyperplane space with variational mode decomposition;Li;Mech. Syst. Sig. Process.,2019

3. Degradation Assessment and Residual Life Prediction of Rolling Bearings Based on Multiple Features;Yan,2016

4. Bearing remaining useful life prediction based on a nonlinear wiener process model;Wen;Shock. Vib.,2018

5. A new method based on stochastic process models for machine remaining useful life prediction;Lei;IEEE Trans. Instrum. Meas.,2016

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