Fault Detection in Induction Machines Using Learning Models and Fourier Spectrum Image Analysis

Fault Detection in Induction Machines Using Learning Models and Fourier Spectrum Image Analysis

Induction motors are essential components in industry due to their efficiency and cost-effectiveness. This study presents an innovative methodology for automatic fault detection by analyzing images generated from the Fourier spectra of current signals using deep learning techniques. A new preprocess...

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Bibliographic Details
Main Authors: Kevin Barrera-Llanga, Jordi Burriel-Valencia, Angel Sapena-Bano, Javier Martinez-Roman
Format: Article
Language:English
Published: MDPI AG 2025-01-01
Series:Sensors
Subjects:
fault diagnosis
induction motors
spectral images
deep learning
explainability
predictive maintenance
Online Access:https://www.mdpi.com/1424-8220/25/2/471
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