A Scalo Gram-Based CNN Ensemble Method With Density-Aware SMOTE Oversampling for Improving Bearing Fault Diagnosis

A Scalo Gram-Based CNN Ensemble Method With Density-Aware SMOTE Oversampling for Improving Bearing Fault Diagnosis

Machine learning (ML) based bearing fault detection is an emerging application of Artificial Intelligence (AI) that has proven its utility in effectively classifying various faults for timely measures. There are myriad studies dedicated to the effective classification of bearing faults under differe...

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Bibliographic Details
Main Authors: Muhammad Irfan, Zohaib Mushtaq, Nabeel Ahmed Khan, Salim Nasar Faraj Mursal, Saifur Rahman, Muawia Abdelkafi Magzoub, Muhammad Armghan Latif, Faisal Althobiani, Imran Khan, Ghulam Abbas
Format: Article
Language:English
Published: IEEE 2023-01-01
Series:IEEE Access
Subjects:
Bearing fault detection
deep convolutional neural network
transfer learning
fine tuning
time series
data pre-processing
Online Access:https://ieeexplore.ieee.org/document/10315006/

Internet

https://ieeexplore.ieee.org/document/10315006/

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