Method of assessing the state of a rolling bearing based on the relative compensation distance of multiple-domain features and locally linear embedding-Reference-Cited by-同舟云学术

Method of assessing the state of a rolling bearing based on the relative compensation distance of multiple-domain features and locally linear embedding

Published:2017-03 Issue: Volume:86 Page:40-57
ISSN:0888-3270
Container-title:Mechanical Systems and Signal Processing
language:en
Short-container-title:Mechanical Systems and Signal Processing

Author:

Kang Shouqiang,Ma Danyang,Wang Yujing,Lan Chaofeng,Chen Qingguo,Mikulovich V.I.

Funder

National Natural Science Foundation of China

Natural Science Foundation of Heilongjiang Province

Hei Long Jiang Postdoctoral Foundation

Harbin University of Science and Technology

Publisher

Elsevier BV

Subject

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

Reference28 articles.

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3. Application of empirical mode decomposition and artificial neural network for automatic bearing fault diagnosis based on vibration signals;Ali;Appl. Acoust.,2015

4. 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

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

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