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HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 694-697Roller Bearing Fault Diagnosis Based on IMF...

Roller Bearing Fault Diagnosis Based on IMF Kurtosis and SVM

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Abstract:

This paper presents a fault diagnosis method of roller bearings based on intrinsic mode function (IMF) kurtosis and support vector machine (SVM). In order to improve the performance of kurtosis under strong levels of background noise, the empirical mode decomposition (EMD) method is used to decompose the bearing vibration signals into a number of IMFs. The IMF kurtosis is then calculated because of its sensitivity of impulses caused by faults. Subsequently, the IMF kurtosis values are treated as fault feature vectors and input into SVM for fault classification. The experimental results show the effectiveness of the proposed approach in roller bearing fault diagnosis.

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Periodical:

Advanced Materials Research (Volumes 694-697)

Pages:

1160-1166

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.694-697.1160

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Online since:

May 2013

Authors:

Ke Heng Zhu, Xi Geng Song, Dong Xin Xue

Keywords:

Empirical Mode Decomposition (EMD), Fault Diagnosis, Kurtosis, Roller Bearing, Support Vector Machine (SVM)

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© 2013 Trans Tech Publications Ltd. All Rights Reserved

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