Induction motor bearing faults diagnosis based on Auto-Regressive spectral analysis-Reference-Cited by-同舟云学术

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Induction motor bearing faults diagnosis based on Auto-Regressive spectral analysis

Published:2023-09-01 Issue: Volume: Page:
ISSN:
Container-title:2023 International Aegean Conference on Electrical Machines and Power Electronics (ACEMP) & 2023 International Conference on Optimization of Electrical and Electronic Equipment (OPTIM)
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Author:

Aimer Ameur Fethi¹,Boudinar Ahmed Hamida²,Khodja Mohamed El-Amine³,Bendiabdellah Azeddine²

Affiliation:

1. University Dr. Tahar Moulay of Saida,Diagnosis Group, LDEE Laboratory (USTO-Oran) Department of Electrical Engineering,Saida,Algeria

2. University of Sciences and Technology USTO,Diagnosis Group, LDEE Laboratory Department of Electrical Engineering,Oran,Algeria

3. Diagnosis Group, LDEE Laboratory (USTO-Oran),National School of Built and Ground Works Engineering,Preparatory Classes Deprtment,Algiers,Algeria

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10287017/10287018/10287030.pdf?arnumber=10287030

Reference28 articles.

1. Outer Race Fault Diagnosis by Comparison between the Power Spectral Density and the Kurtogram

2. Choice of the window used in the interpolated discrete fourier transform method, Revue Roumaine des Sciences et Techniques--serie Electrotechnique et Energetique;belega,2009

3. Model-order selection: a review of information criterion rules;stoica;Signal Processing Magazine,2004

4. Improved Diagnosis of Induction Motor's Rotor Faults using the Papoulis Window

5. Frequency resolution improvements in induction motor fault diagnosis : Experimental validation

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