A Combined Short Time Fourier Transform and Image Classification Transformer Model for Rolling Element Bearings Fault Diagnosis in Electric Motors

A Combined Short Time Fourier Transform and Image Classification Transformer Model for Rolling Element Bearings Fault Diagnosis in Electric Motors

The most frequent faults in rotating electrical machines occur in their rolling element bearings. Thus, an effective health diagnosis mechanism of rolling element bearings is necessary from operational and economical points of view. Recently, convolutional neural networks (CNNs) have been proposed f...

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Bibliographic Details
Main Authors: Christos T. Alexakos, Yannis L. Karnavas, Maria Drakaki, Ioannis A. Tziafettas
Format: Article
Language:English
Published: MDPI AG 2021-02-01
Series:Machine Learning and Knowledge Extraction
Subjects:
bearing fault
convolutional neural network
electric motors
short time fourier transform
image classification transformer
fault diagnosis
Online Access:https://www.mdpi.com/2504-4990/3/1/11

Internet

https://www.mdpi.com/2504-4990/3/1/11

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