This paper proposes an approach for identifying the nature of power quality disturbances using hybrid feature extraction technique combining S transform and Hilbert transform. Using the combined features obtained, the classification is performed using Extreme Learning Machine (ELM). The effectiveness of the proposed approach is tested using wide spectrum of power quality disturbances. The comparison with existing methods indicates that the proposed hybrid signal processing approach for feature extraction results in improved classification accuracy. Sensitivity of the proposed approach is examined for signals with noise and the results are presented.


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    Titel :

    Power Quality Data Mining Using Hybrid Feature Extraction Technique


    Weitere Titelangaben:

    Lect. Notes Electrical Eng.


    Beteiligte:


    Erscheinungsdatum :

    2023-03-12


    Format / Umfang :

    12 pages





    Medientyp :

    Aufsatz/Kapitel (Buch)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




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