Study on planetary gear fault diagnosis based on variational mode decomposition and deep neural networks-Reference-Cited by-同舟云学术

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Study on planetary gear fault diagnosis based on variational mode decomposition and deep neural networks

Published:2018-12 Issue: Volume:130 Page:94-104
ISSN:0263-2241
Container-title:Measurement
language:en
Short-container-title:Measurement

Author:

Li Yong,Cheng Gang,Liu Chang,Chen Xihui

Funder

Priority Academic Program Development of Jiangsu Higher Education Institutions

Fundamental Research Funds for the Central Universities

Publisher

Elsevier BV

Subject

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

Reference29 articles.

1. Recent advances in time-frequency analysis methods for machinery fault diagnosis: a review with application examples;Feng;Mech. Syst. Sig. Process.,2013

2. Vibration signal models for fault diagnosis of planetary gearboxes;Feng;J. Sound Vib.,2012

3. Gear fault identification based on Hilbert-Huang transform and SOM neural network;Cheng;Measurement,2013

4. Vibration Signal Simulation and Fault Diagnosis of Planetary Gearboxes Based on Transmission Mechanism Analysis;Lei;J. Mech. Eng.,2014

5. Comparison between the efficiency of LMD and EMD algorithms for early detection of gear defects;Thameur;Mech. Industry,2013

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