Bearing Fault Diagnosis using DWT& SVM

Naidu, VPS (2018) Bearing Fault Diagnosis using DWT& SVM. International Journal of Engineering Research & Technology (IJERT), 6 (13). pp. 1-6. ISSN 2278-0181

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Abstract

Bearings are very critical components in all rotating machines used in the majority of the industries. Vibration analysis based condition monitoring is one of the best approaches for maintenance and diagnosing the faults in the rotating machinery. This paper deals with the vibration-based health condition-monitoring techniques used for bearing fault diagnosis. Discrete wavelet transform (DWT) and support vector machines (SVM) have been presented for the statistical feature extraction and fault classification of the bearings respectively. The useful features from normalized wavelets energy analysis and wavelets variance have been extracted. The results reveal that the vibration based health condition monitoring method is successful in fault diagnosis and clear classification of bearing faults using DWT and SVM.

Item Type: Article
Subjects: AERONAUTICS > Avionics & Aircraft Instrumentation
AERONAUTICS > Aircraft Propulsion and Power
ENGINEERING > Electronics and Electrical Engineering
Depositing User: Dr VPS Naidu
Date Deposited: 09 Aug 2018 12:46
Last Modified: 09 Aug 2018 12:46
URI: http://nal-ir.nal.res.in/id/eprint/12925

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