Effect of Current Resampling in Motor Current Signature Analysis

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Date

2013

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Abstract

Motor 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.

Description

IEEE 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 -- 98450

Keywords

cracked or broken rotor bar detection, fast Fourier transform, motor current signature analysis, wavelet packet decomposition, Broken rotor bar, Detection performance, Fundamental frequencies, Motor current signature analysis, Nonstationary signals, Sampling frequencies, Stator currents, Wavelet Packet Decomposition, Fast Fourier transforms, Fault detection, Induction motors, Instruments, Spectrum analysis, Stators, Wavelet analysis, Measurements

Fields of Science

0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology

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N/A

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Q3
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3

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Conference Record - IEEE Instrumentation and Measurement Technology Conference

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345

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348
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