Induction motor bearing fault classification using deep neural network with particle swarm optimization‐extreme gradient boosting

Induction motor bearing fault classification using deep neural network with particle swarm optimization‐extreme gradient boosting

Abstract Intelligent motor fault diagnosis in industrial applications requires identifying key characteristics to differentiate various fault types effectively. Solely relying on statistical features cannot guarantee high classification accuracy, while complex feature extraction techniques can pose...

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Bibliographic Details
Main Authors: Chun‐Yao Lee, Edu Daryl C. Maceren
Format: Article
Language:English
Published: Wiley 2024-03-01
Series:IET Electric Power Applications
Subjects:
fault currents
feature extraction
feedforward neural nets
induction motors
rolling bearings
vibrational signal processing
Online Access:https://doi.org/10.1049/elp2.12389

Internet

https://doi.org/10.1049/elp2.12389

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