A feedforward artificial neural network has been realized and trained to individualize subharmonics frequencies in an electric network. The adopted sampling window is fixed in 20 ms correspondent to a period of the fundamental frequency of 50 Hz, nevertheless the net is able to identify the subharmonics frequencies even if their period is not completed. The particular binary successive approximation structure realized for the ANN forecasts the scalability of the same net so allowing to recognize the subharmonics with a prefixed resolution. The net has been widely tested on synthesized signals
Leccese, F. (2010). Subharmonics Determination Method based on Binary Successive Approximation Feed Forward Artificial Neural Network: a preliminary study. In 9th International Conference on Environment and Electrical Engineering (pp.442-446) [10.1109/EEEIC.2010.5489913].
Subharmonics Determination Method based on Binary Successive Approximation Feed Forward Artificial Neural Network: a preliminary study
LECCESE, Fabio
2010-01-01
Abstract
A feedforward artificial neural network has been realized and trained to individualize subharmonics frequencies in an electric network. The adopted sampling window is fixed in 20 ms correspondent to a period of the fundamental frequency of 50 Hz, nevertheless the net is able to identify the subharmonics frequencies even if their period is not completed. The particular binary successive approximation structure realized for the ANN forecasts the scalability of the same net so allowing to recognize the subharmonics with a prefixed resolution. The net has been widely tested on synthesized signalsI documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
