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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vol. 197Vibration Analysis Based Feature Extraction for...

Vibration Analysis Based Feature Extraction for Bearing Fault Detection

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Abstract:

Rolling element bearings are widely used in various rotary machines. Most rotary machine failures are attributed to unexpected bearing faults. Accordingly, reliable bearing fault detection is critically needed in industries to prevent these machines’ performance degradation, malfunction, or even catastrophic failures. Feature extraction plays an important role in bearing fault detection and significant research efforts have thus far been devoted to this subject from both academia and industry. This paper intends to provide a brief review of the recent developments in feature extraction for bearing fault detection, and the focus will be placed on the advances in methods for dealing with the nonstationary characteristics of bearing fault signatures.

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Applied Sciences and Engineering

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Periodical:

Applied Mechanics and Materials (Volume 197)

Pages:

124-128

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.197.124

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Online since:

September 2012

Authors:

Jie Liu, Chun Sheng Yang, Qing Feng Lou

Keywords:

Bearing, Fault Detection, Feature Extraction, Health Condition Monitoring, Signal Processing, Vibration

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© 2012 Trans Tech Publications Ltd. All Rights Reserved

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