Eren L.Devaney M.J.2023-06-162023-06-1620139.78E+121091-5281https://doi.org/10.1109/I2MTC.2013.6555437https://hdl.handle.net/20.500.14365/3532IEEE Instrumentation and Measurement Society (I and M)2013 IEEE International Instrumentation and Measurement Technology Conference: Instrumentation and Measurement for Life, I2MTC 2013 -- 6 May 2013 through 9 May 2013 -- Minneapolis, MN -- 98450Motor Current Signature Analysis (MCSA) is one of the most widely used methods in monitoring condition of induction motors. Traditionally, the stator current is preprocessed by notch filters to suppress line fundamental frequency. Then, the fast Fourier transform is utilized for the spectral analysis of the preprocessed stator current in most applications. However, this approach has a shortcoming in the analysis of non-stationary signals such as stator current under varying load conditions. The use of wavelet transform is suggested for providing better analysis results in recently published studies. Both approaches use some preprocessing of stator current in the analysis that is very sensitive to even slightest variations in sampling frequency. The resampling of current data at an exact integer multiple of line frequency is proposed in this study to improve the overall fault detection performance. © 2013 IEEE.eninfo:eu-repo/semantics/closedAccesscracked or broken rotor bar detectionfast Fourier transformmotor current signature analysiswavelet packet decompositionBroken rotor barDetection performanceFundamental frequenciesMotor current signature analysisNonstationary signalsSampling frequenciesStator currentsWavelet Packet DecompositionFast Fourier transformsFault detectionInduction motorsInstrumentsSpectrum analysisStatorsWavelet analysisMeasurementsConference Object10.1109/I2MTC.2013.65554372-s2.0-84882237371