Motor current signal analysis using deep neural networks for planetary gear fault diagnosis-Reference-Cited by-同舟云学术

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Motor current signal analysis using deep neural networks for planetary gear fault diagnosis

Published:2019-10 Issue: Volume:145 Page:45-54
ISSN:0263-2241
Container-title:Measurement
language:en
Short-container-title:Measurement

Author:

Li Feng,Pang Xinyu,Yang Zhaojian

Funder

National Natural Science Foundation of China

Innovation Project in Postgraduate Education of Shanxi Province

Publisher

Elsevier BV

Subject

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

Reference33 articles.

1. Planetary gearbox fault diagnosis using an adaptive stochastic resonance method;Lei;Mechanical Systems and Signal Processing,2013

2. Iterative generalized time–frequency reassignment for planetary gearbox fault diagnosis under nonstationary conditions;Chen;Mech. Syst. Sig. Process.,2016

3. Customized multiwavelets for planetary gearbox fault detection based on vibration sensor signals;Sun;Sensors,2013

4. Planetary gearbox fault diagnosis based on hilbert vibration decomposition and higher order differential energy operator;Feng;J. Vib. Shock,2016

5. Planetary gearbox fault diagnosis based on data-driven valued characteristic multigranulation model with incomplete diagnostic information;Yu;J. Sound Vib.,2018

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