International Journal of Fuzzy Logic and Intelligent Systems

Korean Institute of Intelligent Systems (한국지능시스템학회)
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Fault Detection and Identification of Induction Motors with Current Signals Based on Dynamic Time Warping

  • Bae, Hyeon (School of Electrical and Computer Engineering, Pusan National University) ;
  • Kim, Sung-Shin (School of Electrical and Computer Engineering, Pusan National University) ;
  • Vachtsevanos, George (School of Electrical and Computer Engineering, Georgia Institute of Technology)
  • Published : 2007.06.01
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Abstract

The issues of preventive and condition-based maintenance, online monitoring, system fault detection, diagnosis, and prognosis are of increasing importance. This study introduces a technique to detect and identify faults in induction motors. Stator currents were measured and stored by time domain. The time domain is not suitable for representing current signals, so wavelet transform is used to convert the signal; onto frequency domain. The raw signals can not show the significant feature, therefore difference values are applied. The difference values were transformed by wavelet transform and the features are extracted from the transformed signals. The dynamic time warping method was used to identify the four fault types. This study describes the results of detecting fault using wavelet analysis.

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References

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