Bearing Fault Classification Using Ensemble Empirical Mode Decomposition and Convolutional Neural Network

Bearing Fault Classification Using Ensemble Empirical Mode Decomposition and Convolutional Neural Network

Condition monitoring is used to track the unavoidable phases of rolling element bearings in an induction motor (IM) to ensure reliable operation in domestic and industrial machinery. The convolutional neural network (CNN) has been used as an effective tool to recognize and classify multiple rolling...

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Bibliographic Details
Main Authors:	Rafia Nishat Toma, Cheol-Hong Kim, Jong-Myon Kim
Format:	Article
Language:	English
Published:	MDPI AG 2021-05-01
Series:	Electronics
Subjects:	bearing fault diagnosis vibration signal EEMD envelope analysis CWT time-frequency representation
Online Access:	https://www.mdpi.com/2079-9292/10/11/1248

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