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Fault diagnosis of rolling bearing of wind turbines based on the Variational Mode Decomposition and Deep Convolutional Neural Networks
Author(s):
Zifei Xu
,
Chun Li
,
Yang Yang
Publication date
Created:
October 2020
Publication date
(Print):
October 2020
Journal:
Applied Soft Computing
Publisher:
Elsevier BV
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Variational Mode Decomposition
Konstantin Dragomiretskiy
,
Dominique Zosso
(2014)
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A deep convolutional neural network with new training methods for bearing fault diagnosis under noisy environment and different working load
Zhujun Zhang
,
Yuanhang Chen
,
Gaoliang Peng
…
(2018)
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A Hybrid Prognostics Approach for Estimating Remaining Useful Life of Rolling Element Bearings
Biao Wang
,
Yaguo Lei
,
Naipeng Li
…
(2018)
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Author and article information
Contributors
Zifei Xu:
(View ORCID Profile)
Chun Li:
(View ORCID Profile)
Yang Yang:
(View ORCID Profile)
Journal
Title:
Applied Soft Computing
Abbreviated Title:
Applied Soft Computing
Publisher:
Elsevier BV
ISSN (Print):
15684946
Publication date Created:
October 2020
Publication date (Print):
October 2020
Volume
: 95
Page
: 106515
Article
DOI:
10.1016/j.asoc.2020.106515
SO-VID:
e94a292b-c801-414c-bedc-e60ca2cbddcb
Copyright ©
© 2020
License:
https://www.elsevier.com/tdm/userlicense/1.0/
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