Automatic identification of electric loads using switching transient current signals

dc.contributor.authorThiruvaran, T.
dc.contributor.authorPhung, T.
dc.contributor.authorAmbikairajah, E.
dc.date.accessioned2021-03-25T04:43:58Z
dc.date.accessioned2022-06-27T10:02:35Z
dc.date.available2021-03-25T04:43:58Z
dc.date.available2022-06-27T10:02:35Z
dc.date.issued2013
dc.description.abstractThe automatic identification of different electric loads using the current waveform at the time of switching, is analysed in this paper. The time variation of the harmonics at the time of switching is modelled using the Hidden Markov Model with Gaussian Mixture Models representing the probabilities. Short Time Fourier Transform (STFT) and Wavelet Transform (WT) based features are compared at their optimum configurations. The STFT based feature gave an accuracy of 97.9% while the WT features provided an accuracy of 93.75% in a cross fold validation experiment.en_US
dc.identifier.citationThiruvaran, T., Phung, T., & Ambikairajah, E. (2013, April). Automatic identification of electric loads using switching transient current signals. In IEEE 2013 Tencon-Spring (pp. 252-256). IEEE.en_US
dc.identifier.urihttp://repo.lib.jfn.ac.lk/ujrr/handle/123456789/2115
dc.language.isoenen_US
dc.publisherIEEEen_US
dc.subjectElectric load identificationen_US
dc.subjectharmonic analysisen_US
dc.titleAutomatic identification of electric loads using switching transient current signalsen_US
dc.typeArticleen_US

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