A fault diagnosis method based on improved convolutional neural network for bearings under variable working conditions-Reference-Cited by-同舟云学术

A fault diagnosis method based on improved convolutional neural network for bearings under variable working conditions

Published:2021-09 Issue: Volume:182 Page:109749
ISSN:0263-2241
Container-title:Measurement
language:en
Short-container-title:Measurement

Author:

Zhang Ke,Wang Jingyu,Shi Huaitao,Zhang Xiaochen,Tang Yinghan

Funder

Natural Science Foundation of Liaoning Province

Department of Education of Liaoning Province

Liaoning Revitalization Talents Program

National Natural Science Foundation of China

Publisher

Elsevier BV

Subject

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

Reference24 articles.

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2. Nonlinear vibrations of fiber-reinforced composite cylindrical shells with bolt loosening boundary conditions;Li;J. Sound Vib.,2021

3. Intelligent Fault Diagnosis and Remaining Useful Life Prediction of Rotating Machinery;Lei,2016

4. Incipient fault detection of rolling element bearings based on deep EMD-PCA algorithm;Shi;Shock Vib.,2020

5. Stator-winding incipient shorted-turn fault detection for motor system in motorized spindle using modified interval observers;Hou;IEEE Trans. Instrum. Meas.,2020

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