Bearing fault detection based on hybrid ensemble detector and empirical mode decomposition

Article ID	Journal	Published Year	Pages	File Type
6956661	Mechanical Systems and Signal Processing	2013	16 Pages	PDF

Abstract

âº We employed EMD for feature extraction from vibration signals of bearings. âº The frequency content of the IMFs can provide valuable information for fault detection. âº Simple anomaly detectors combined in a hybrid scheme can perfectly detect anomalies. âº The ensemble scheme compensates for the inefficiencies of the individual detectors.

Keywords

Empirical mode decomposition Anomaly detection One-class classification Hilbert Huang Transform bearings

Related Topics

Physical Sciences and Engineering Computer Science Signal Processing

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Bearing fault detection based on hybrid ensemble detector and empirical mode decomposition

Authors

George Georgoulas, Theodore Loutas, Chrysostomos D. Stylios, Vassilis Kostopoulos,