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Detection of Winding (Shorted-Turn) Fault in Induction Machine at Incipient Stage Using DC-Centered Periodogram

  • ỌdunAyọ ImoruEmail author
  • M. Arun Bhaskar
  • Adisa A. Jimoh
  • Yskandar Hamam
  • Jacob Tsado
Conference paper

Abstract

The problem of detecting shorted turns faults in stator windings has been difficult. The risk of the failure or the breaking down of this machine can be circumvented provided there is a proper way to detect the shorted turns faults. From literature, there are many methods of faults detection and diagnosis of the machine, however, DC-centered periodogram has not really been applied to detect and diagnose a fault in the electrical machine. This chapter describes stator winding shorted-turn fault detection of induction machine using DC-centered periodogram. Codes to analyses the DC-centered periodogram for both induction Machine under Healthy and shorted fault conditions were written from the general algorithm of periodogram. It is observed that the abnormality showed from the stator current signals for each condition corresponds to the plots generated by the DC-centered periodogram. The results obtained are also compared with another technique (DWT-Energy) using the same data. The peak values of the shorted turn-(S) is greater than the peak of the healthy-(H) state in both techniques. Thus, with DC-periodogram method, an electrical machine can be placed under close monitor for fault detection when the peak value of the PSD of a healthy machine under operation is started deviating from 0 dB/Hz.

Keywords

Data capture Electrical machine Fault diagnosis Periodogram Power spectral density (PSD) Winding faults 

Notes

Acknowledgements

The authors would like to thank Rand Water Professorial Chair (Electrical Engineering) of Tshwane University of Technology, Pretoria for financing the material required to carry out an experiment for the research. The authors would like to thank the National Research Foundation (NRF) for the financial support received for the research work.

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Copyright information

© Springer Nature Singapore Pte Ltd. 2019

Authors and Affiliations

  • ỌdunAyọ Imoru
    • 1
    Email author
  • M. Arun Bhaskar
    • 2
  • Adisa A. Jimoh
    • 3
  • Yskandar Hamam
    • 3
  • Jacob Tsado
    • 1
  1. 1.Department of Electrical & ElectronicsFederal University of TechnologyMinnaNigeria
  2. 2.Department of EEEVelammal Engineering CollegeChennaiIndia
  3. 3.Department of Electrical EngineeringTshwane University of TechnologyPretoriaSouth Africa

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