A two-stage method based on extreme learning machine for predicting the remaining useful life of rolling-element bearings-Reference-Cited by-同舟云学术

A two-stage method based on extreme learning machine for predicting the remaining useful life of rolling-element bearings

Published:2020-10 Issue: Volume:144 Page:106899
ISSN:0888-3270
Container-title:Mechanical Systems and Signal Processing
language:en
Short-container-title:Mechanical Systems and Signal Processing

Author:

Pan Zuozhou^ORCID,Meng Zong^ORCID,Chen Zijun,Gao Wenqing,Shi Ying

Publisher

Elsevier BV

Subject

Computer Science Applications,Mechanical Engineering,Aerospace Engineering,Civil and Structural Engineering,Signal Processing,Control and Systems Engineering

Reference48 articles.

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2. Analysis of varying contact angles and load distributions in defective angular contact ball bearing;Li;Eng. Fail. Analy.,2018

3. Quantitative and localization diagnosis of a defective ball bearing based on vertical-horizontal synchronization signal analysis;Cui;IEEE Trans. Ind. Electron.,2017

4. Feature fusion using kernel joint approximate diagonalization of eigen-matrices for rolling bearing fault identification;Liu;J. Sound Vib.,2016

5. Accurate bearing remaining useful life prediction based on Weibull distribution and artificial neural network;Ben-Ali;Mech. Syst. Signal Process.,2015

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