A recurrent neural network based health indicator for remaining useful life prediction of bearings-Reference-Cited by-同舟云学术

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A recurrent neural network based health indicator for remaining useful life prediction of bearings

Published:2017-05 Issue: Volume:240 Page:98-109
ISSN:0925-2312
Container-title:Neurocomputing
language:en
Short-container-title:Neurocomputing

Author:

Guo Liang,Li Naipeng,Jia Feng,Lei Yaguo,Lin Jing

Funder

National Natural Science Foundation of China

Young Talent Support plan of Central Organization Department

Visiting Scholar Foundation of the State Key Lab. of Traction Power in Southwest Jiaotong University

Publisher

Elsevier BV

Subject

Artificial Intelligence,Cognitive Neuroscience,Computer Science Applications

Reference42 articles.

1. Condition monitoring and fault diagnosis of planetary gearboxes: a review;Lei;Measurement,2014

2. Probabilistic frequency-domain discrete wavelet transform for better detection of bearing faults in induction motors;Ghods;Neurocomputing,2016

3. An enhanced diagnostic scheme for bearing condition monitoring;Liu;IEEE Trans. Instrum. Meas.,2010

4. Rotating speed isolation and its application to rolling element bearing fault diagnosis under large speed variation conditions;Wang;J. Sound Vib.,2015

5. Deep neural networks: a promising tool for fault characteristic mining and intelligent diagnosis of rotating machinery with massive data;Jia;Mech. Syst. Signal Process.,2016

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