• DocumentCode
    1651706
  • Title

    Wavelet transforms for fault detection using SVM in Power Systems

  • Author

    Sevakula, Rahul K. ; Verma, Nishchal K.

  • Author_Institution
    Dept. of Electr. Eng., Indian Inst. of Technol. Kanpur, Kanpur, India
  • fYear
    2012
  • Firstpage
    1
  • Lastpage
    6
  • Abstract
    In this paper we study how Wavelet Transforms and Support Vector Machine have been used successfully for fault detection in Power Systems. We then present a case study on machine fault diagnosis, where we are getting classification accuracies up to 99%. In similar lines, we propose ideas for better fault detection in Power Systems.
  • Keywords
    fault diagnosis; power engineering computing; power system faults; support vector machines; wavelet transforms; SVM; fault detection; machine fault diagnosis; power systems; support vector machine; wavelet transforms; Discrete wavelet transforms; Feature extraction; Power systems; Support vector machines; Wavelet domain; Fault Detection; Health Monitoring; Power Systems; SVM; Smart Grid; Wavelet Transforms;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Power Electronics, Drives and Energy Systems (PEDES), 2012 IEEE International Conference on
  • Conference_Location
    Bengaluru
  • Print_ISBN
    978-1-4673-4506-4
  • Type

    conf

  • DOI
    10.1109/PEDES.2012.6484324
  • Filename
    6484324
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=1651706