Fault diagnosis based on SPBO-SDAE and transformer neural network for rotating machinery-Reference-Cited by-同舟云学术

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Fault diagnosis based on SPBO-SDAE and transformer neural network for rotating machinery

Published:2022-01 Issue: Volume:188 Page:110545
ISSN:0263-2241
Container-title:Measurement
language:en
Short-container-title:Measurement

Author:

Du Xianjun,Jia Liangliang,Ul Haq Izaz

Funder

National Natural Science Foundation of China

Gansu Provincial Natural Science Foundation

Gansu Education Department

Publisher

Elsevier BV

Subject

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

Reference44 articles.

1. Rolling bearing fault diagnosis based on GCMWPE and parameter optimization SVM;Ding;Zhongguo Jixie Gongcheng/China Mech. Eng.,2021

2. A rolling bearing fault diagnosis method based on fast DTW and an AGBDBN;Zhiwu;Insight - Non-Destruct. Test. Cond. Monit.,2020

3. A rolling bearing fault diagnosis using time-frequency analysis and deep transfer convolutional neural network;Chen;IEEE Access,2020

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

5. Fault diagnosis of rolling element bearing based on artificial neural network;Gunerkar;J. Mech. Sci. Technol.,2019

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