An automatic procedure, based on a genetic algorithm capable of optimizing a diagnostic system for the recognition and identification of partial-discharge (PD) pulse patterns in the terminations and joints of solid dielectric extruded power distribution cables, is described. The core of the diagnostic system is a fuzzy neural network, namely a Min-Max classifier. The genetic optimization is capable for reducing the system complexity, while enhancing its diagnostic performance. The developed procedure is sufficiently general to be applied to PD source identification in the cables themselves as well as other electric power apparatus.
Genetic Optimization of a PD Diagnostic System for Cable Accessories / Rizzi, Antonello; FRATTALE MASCIOLI, Fabio Massimo; F., Baldini; MAZZETTI DI PIETRALATA, Carlo; R., Bartnikas. - In: IEEE TRANSACTIONS ON POWER DELIVERY. - ISSN 0885-8977. - 24:3(2009), pp. 1728-1738. [10.1109/tpwrd.2009.2016826]
Genetic Optimization of a PD Diagnostic System for Cable Accessories
RIZZI, Antonello;FRATTALE MASCIOLI, Fabio Massimo;MAZZETTI DI PIETRALATA, Carlo;
2009
Abstract
An automatic procedure, based on a genetic algorithm capable of optimizing a diagnostic system for the recognition and identification of partial-discharge (PD) pulse patterns in the terminations and joints of solid dielectric extruded power distribution cables, is described. The core of the diagnostic system is a fuzzy neural network, namely a Min-Max classifier. The genetic optimization is capable for reducing the system complexity, while enhancing its diagnostic performance. The developed procedure is sufficiently general to be applied to PD source identification in the cables themselves as well as other electric power apparatus.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
