Enhancement of the AR-MED Deconvolution Process using Ensemble Empirical Mode Decomposition in Bearing Fault Detection-Reference-Cited by-同舟云学术

Enhancement of the AR-MED Deconvolution Process using Ensemble Empirical Mode Decomposition in Bearing Fault Detection

Published:2023-03-06 Issue: Volume: Page:
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Container-title:2023 International Conference on Advances in Electronics, Control and Communication Systems (ICAECCS)
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Author:

Damine Yasser¹,Bessous Noureddine²,Megherbi Ahmed Chaouki¹,Sbaa Salim SbaaSalim SbaaSalim SbaaSalim³,Ünsal Abdurrahman⁴

Affiliation:

1. University of Mohamed Khider,Laboratory of LI3CUB,dept. Electrical Engineering,Biskra,Algeria

2. University of El Oued,Laboratory of LGEERE,dept. Electrical Engineering,El Oued,Algeria

3. University of Mohamed Khider,Laboratory of VSC,dept. Electrical Engineering,Biskra,Algeria

4. University of KÜtahya Dumlupınar,Laboratory of Electrical Machines,dept. Electrical Engineering,Kütahya,Turkey

Publisher

IEEE

Link

Reference19 articles.

Cited by 3 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. A Bearing Faults Diagnosis Enhancement Using EMD and MEDA;2024 2nd International Conference on Electrical Engineering and Automatic Control (ICEEAC);2024-05-12

3. Incipient Fault Diagnosis of Rolling Bearing Based on ACMD and Parametric Optimized MNAD;2023 Global Reliability and Prognostics and Health Management Conference (PHM-Hangzhou);2023-10-12