Induction Machine Bearing Fault Diagnosis With Discrete Wavelet Transform Using Vibration Signal

Ashwani Kumar Chandel*, Raj Kumar Patel**
* Associate Professor, Department of Electrical and Electronics Engineering, National Institute of Technology, Hamirpur, HP India.
** M.Tech Student, Department of Electrical and Electronics Engineering, National Institute of Technology, Hamirpur (H.P.).
Periodicity:April - June'2012
DOI : https://doi.org/10.26634/jee.5.4.1858

Abstract

Condition monitoring and fault diagnosis of electrical machinery are of great concern in industries. Pre fault detection in machinery can save millions of rupee required as emergency maintenance cost. In the present paper a methodology for the diagnosis of bearing faults in an induction machine has been given. The proposed discrete wavelet transform methodology extracts principal features from vibration signals caused by the faulty bearings and subsequently analyse these for determining the type of fault. The discrete wavelet transform is fed with the accelerometer signals and it is found that the impulses appear periodically with time period corresponding to defect frequencies. The results thus obtained reveal that the proposed pre-faults detection method is very efficient and effective.

Keywords

Bearing, condition, faults, induction machine, monitoring, wavelet transform

How to Cite this Article?

Ashwani Kumar Chandel and Raj Kumar Patel (2012). Induction Machine Bearing Fault Diagnosis With Discrete Wavelet Transform Using Vibration Signal. i-manager’s Journal on Electrical Engineering, 5(4), 11-17. https://doi.org/10.26634/jee.5.4.1858

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