Current Signature-Based Bearing Fault Severity Classification Using a Robust Multilevel Cascaded Framework

Current Signature-Based Bearing Fault Severity Classification Using a Robust Multilevel Cascaded Framework

Bearing faults are a critical concern in electrical machines, particularly permanent magnet synchronous motors (PMSMs), commonly used in electric vehicles. Early and accurate classification of bearing fault severity is essential for predictive maintenance, as it enhances cost-effectiveness, ensures...

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Bibliographic Details
Main Authors: Korawege N. C. Jayasena, Battur Batkhishig, Babak Nahid-Mobarakeh, Ali Emadi
Format: Article
Language:English
Published: IEEE 2025-01-01
Series:IEEE Access
Subjects:
Artificial neural networks (ANNs)
bearing fault severity
current signature
feature fusion
interpretable artificial intelligence
multilevel cascaded framework
Online Access:https://ieeexplore.ieee.org/document/11082138/
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https://ieeexplore.ieee.org/document/11082138/

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