Research Output
Diagnosis of faults in induction generators under fluctuating load conditions through the instantaneous frequency of the fault components
  This paper introduces a methodology for
improving the reliability of diagnosis of different types of
faults in wound rotor induction generators which works under
variable load conditions; the method is based on the extraction
of the Instantaneous Frequency of the fault related
components of stator and rotor currents during speed
transients, caused by load changes. It is shown that under
these conditions, the Instantaneous Frequency plots of the
fault components versus the slip are straight lines with a
specific slope and offset for each kind of fault. In addition,
neither of these patterns are dependent on the machine
features, nor the way in which the load changes. Besides, the
practical methodology of this technique is introduced for
diagnosing two different kinds of fault: stator winding
asymmetry and rotor winding asymmetry. The approach is
validated by laboratory tests, for both types of faults

  • Date:

    30 September 2012

  • Publication Status:

    Published

  • Publisher

    Institute of Electrical and Electronics Engineers (IEEE)

  • DOI:

    10.1109/icelmach.2012.6350102

  • Library of Congress:

    TK Electrical engineering. Electronics Nuclear engineering

  • Dewey Decimal Classification:

    621.3 Electrical & electronic engineering

  • Funders:

    Spanish “Ministerio de Ciencia e Innovación”

Citation

Vedreno-Santos, F., Riera-Guasp, M., Henao, H., & Pineda-Sanchez, M. (2012). Diagnosis of faults in induction generators under fluctuating load conditions through the instantaneous frequency of the fault components. In 2012 XXth International Conference on Electrical Machines (ICEM)https://doi.org/10.1109/icelmach.2012.6350102

Authors

Keywords

Analytical signal; discrete wavelet transform; fault diagnosis; Hilbert transform; induction generator; instantaneous frequency; load fluctuating conditions; Time-frequency analysis; wind generation

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