作者: Abd Almonam Zahed , Ayman H. El-Hag , Nasser Qaddoumi , Ramy Hussein , Khaled B. Shaban
关键词:
摘要: Three Hilbert fractal antenna designs are proposed in this work to capture and classify common types of partial discharge (PD) an oil insulated system. Each design shows unique characteristics terms resonant frequencies, inception voltage, classification capabilities noise performance. PD signals artificially generated; namely, corona, surface sharp PD. The captured from each analyzed then fed a trained artificial neural network for classification. A recognition rate 97% is achieved when classifying the different using one antennas. Moreover, SNR determine best detection under intense noisy environments.