DocumentCode :
2955401
Title :
Automatic identification of electric loads using switching transient current signals
Author :
Thiruvaran, Tharmarajah ; Toan Phung ; Ambikairajah, E.
Author_Institution :
Sch. of Electr. Eng. & Telecommun., Univ. of New South Wales, Sydney, NSW, Australia
fYear :
2013
fDate :
17-19 April 2013
Firstpage :
252
Lastpage :
256
Abstract :
The 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.
Keywords :
Fourier transforms; Gaussian distribution; hidden Markov models; load forecasting; wavelet transforms; Gaussian mixture models; STFT; automatic identification; current waveform; electric loads; hidden Markov model; short time Fourier transform; switching transient current signals; wavelet transform; Accuracy; Feature extraction; Harmonic analysis; Hidden Markov models; Switches; Time-frequency analysis; Transient analysis; Electric load identification; Hidden Markov Model; Wavelet Transform; harmonic analysis;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
TENCON Spring Conference, 2013 IEEE
Conference_Location :
Sydney, NSW
Print_ISBN :
978-1-4673-6347-1
Type :
conf
DOI :
10.1109/TENCONSpring.2013.6584450
Filename :
6584450
Link To Document :
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