Bearing Fault Detection and Classification Based on Vibration Signal Analysis and ANFIS Classifier-Reference-Cited by-同舟云学术

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Bearing Fault Detection and Classification Based on Vibration Signal Analysis and ANFIS Classifier

Published:2022-05-06 Issue: Volume: Page:
ISSN:
Container-title:2022 19th International Multi-Conference on Systems, Signals & Devices (SSD)
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Author:

Attoui Issam¹,Boutasseta Nadir¹,Fergani Nadir¹,Oudjani Brahim¹,Bouakkaz Mohammed-Salah²,Bouraiou Ahmed³

Affiliation:

1. Research Center in Industrial Technologies CRTI,Cheraga,Algeria

2. LES,Department of Electrical Engineering,Skikda,Algeria

3. URERMS, Centre de Developpement des Energies Renouvelables CDER,Unite de Recherche en Energie Renouvelables en Milieu Saharien,Adrar,Algeria,01000

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9955493/9955494/09955711.pdf?arnumber=9955711

Reference17 articles.

1. The Application of High-Resolution Spectral Analysis for Identifying Multiple Combined Faults in Induction Motors

2. Vibration-based bearing fault diagnosis by an integrated DWT-FFT approach and an adaptive neuro-fuzzy inference system

3. Rolling bearing fault diagnosis based on Improved Complete Ensemble Empirical Mode Decomposition;attoui;4th International Conference on Control Engineering and Information Technology CElT 2016,2017

4. Fault detection and diagnosis in rotating machinery by vibration monitoring using FFT and Wavelet techniques

5. Supervised neural networks for the classification of structures

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