Bearing Fault Diagnosis in Induction Motors Using Low-Cost Triaxial ADXL355 Accelerometer and a Hybrid CWT-DCNN-LSTM Model

Bearing Fault Diagnosis in Induction Motors Using Low-Cost Triaxial ADXL355 Accelerometer and a Hybrid CWT-DCNN-LSTM Model

This paper presents a novel approach for bearing fault diagnosis in induction motor utilizing an improved hybrid Continuous Wavelet Transform-Deep Convolutional Neural Network-Long Short-Term Memory (CWT-DCNN-LSTM) model. The vibration data, recorded using an low-cost ADXL355 accelerometer, was prep...

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Bibliographic Details
Main Authors: Muhammad Ahsan, Jose Rodriguez, Mohamed Abdelrahem
Format: Article
Language:English
Published: IEEE 2025-01-01
Series:IEEE Access
Subjects:
ADXL355 accelerometer
continuous wavelet transform
classification
CWT-DCNN-LSTM
induction motor
rotating bearing
Online Access:https://ieeexplore.ieee.org/document/11028613/
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https://ieeexplore.ieee.org/document/11028613/

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