Induction motor bearing fault classification using deep neural network with particle swarm optimization‐extreme gradient boosting
Chun‐Yao Lee,
Edu Daryl C. Maceren
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 challenges for industry practitioners. Conversely, advanced feature extraction may not ensure that the model effectively learns these features for classification. A feature fusion approach that combines statistical and deep … Show more
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