An identification technique is described, based on a developed adaptive fuzzy logic network, that enables the recognition of partial discharges (PD) generated by different defects in heat-shrinkable joints and terminations of XLPE insulated power distribution cables. It is shown that different sources of PD can be identified on the basis of fuzzy rules applied to a selection of parameters derived from PD-pulse phase and amplitude distributions. A comparison with other PD pattern recognition techniques based on traditional neural networks is presented and discussed.
Partial discharge pattern recognition by neuro-fuzzy networks in heat-shrinkable joints and terminations of XLPE insulated distribution cables / MAZZETTI DI PIETRALATA, Carlo; FRATTALE MASCIOLI, Fabio Massimo; F., Baldini; Panella, Massimo; R., Risica; R., Bartnikas. - In: IEEE TRANSACTIONS ON POWER DELIVERY. - ISSN 0885-8977. - STAMPA. - 21:3(2006), pp. 1035-1044. [10.1109/tpwrd.2006.875861]
Partial discharge pattern recognition by neuro-fuzzy networks in heat-shrinkable joints and terminations of XLPE insulated distribution cables
MAZZETTI DI PIETRALATA, Carlo;FRATTALE MASCIOLI, Fabio Massimo;PANELLA, Massimo;
2006
Abstract
An identification technique is described, based on a developed adaptive fuzzy logic network, that enables the recognition of partial discharges (PD) generated by different defects in heat-shrinkable joints and terminations of XLPE insulated power distribution cables. It is shown that different sources of PD can be identified on the basis of fuzzy rules applied to a selection of parameters derived from PD-pulse phase and amplitude distributions. A comparison with other PD pattern recognition techniques based on traditional neural networks is presented and discussed.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
