Bearing Fault Classification of Induction Motors Using Discrete Wavelet Transform and Ensemble Machine Learning Algorithms

Bearing Fault Classification of Induction Motors Using Discrete Wavelet Transform and Ensemble Machine Learning Algorithms

Bearing fault diagnosis at early stage is very significant to ensure seamless operation of induction motors in industrial environment. The identification and classification of faults helps to undertook maintenance operation in an efficient manner. This paper presents an ensemble machine learning-bas...

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Bibliographic Details
Main Authors: Rafia Nishat Toma, Jong-Myon Kim
Format: Article
Language:English
Published: MDPI AG 2020-07-01
Series:Applied Sciences
Subjects:
bearing fault diagnosis
condition monitoring
discrete wavelet transform (DWT)
extreme gradient boosting (XGBoost)
induction motors
random forest
Online Access:https://www.mdpi.com/2076-3417/10/15/5251

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https://www.mdpi.com/2076-3417/10/15/5251

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