Experimental Diagnosis of Broken Rotor Bar Faults in Induction Motors at Low Slip via Hilbert Envelope and Optimized Subtractive Clustering Adaptive Neuro-Fuzzy Inference System

Experimental Diagnosis of Broken Rotor Bar Faults in Induction Motors at Low Slip via Hilbert Envelope and Optimized Subtractive Clustering Adaptive Neuro-Fuzzy Inference System

Knowledge of the distinctive frequencies and amplitudes of broken rotor bar (BRB) faults in the induction motor (IM) is essential for most fault diagnosis methods. Fast Fourier transform (FFT) is widely applied to diagnose the faults within BRBs. However, this method does not provide satisfactory re...

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Bibliographic Details
Main Authors: Seif Eddine Chehaidia, Hakima Cherif, Musfer Alraddadi, Mohamed Ibrahim Mosaad, Abdelaziz Mahmoud Bouchelaghem
Format: Article
Language:English
Published: MDPI AG 2022-09-01
Series:Energies
Subjects:
induction motor
broken rotor bars
Hilbert transform
adaptive neuro-fuzzy inference system
grid partitioning
subtractive clustering
Online Access:https://www.mdpi.com/1996-1073/15/18/6746

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https://www.mdpi.com/1996-1073/15/18/6746

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