BEARING FAULT DETECTION IN ROTATING ELECTRICAL MACHINES USING WAVELET TRANSFORM
Abstract

Author(s): Alka Thakur, S. Wadhwani, A.K. Wadhwani

In almost all the industrial drive systems induction motors plays a vital role because of their simple, efficient and robust nature. Detection and diagnosis of faults while the system is running can m inimise all kind of losses.Bearing problems are one major cause for induction motor drive failures. Motor failure due to bearing defect is an issue that has drawn an increasing industrial interest over recent years. Commonly-used signal analysis techniques, based on spectral approaches such as the fast Fourier transform, are powerful in diagnosing a variety of vibration-related problems in induction motor drives. Although these techniques provide powerful diagnostic tools in stationary conditions, they fail to do so in several practical cases involving non-stationary data. Wavelet transform tools are considered superior to the fast Fourier transforms as they can effectively analyze non-stationary signals. This work proposes the use of wavelet transform to analyze vibration data in motors affected by bearing defects. These wavelet tools are applied here, with a suitable choice of a mother wavelet function, to a vibration monitoring system to accurately detect and localize faults occurring in the system. Keywords: Induction motors; bearings; fault detection; wavelet transform. 

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Citations : 32

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