Genetic Optimization of a PD Diagnostic System for Cable Accessories

Author

Rizzi, Antonello ; Mascioli, Fabio Massimo Frattale ; Baldini, Francesco ; Mazzetti, Carlo ; Bartnikas, R.

Author_Institution

Univ. of Rome La Sapienza, Rome

Volume

24

Issue

3

fYear

2009

fDate

7/1/2009 12:00:00 AM

Firstpage

1728

Lastpage

1738

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.

Keywords

fuzzy neural networks; genetic algorithms; partial discharges; pattern recognition; power cables; power engineering computing; Min-Max classifier; PD diagnostic system; cable accessories; diagnostic system; electric power apparatus; fuzzy neural network; genetic algorithm; genetic optimization; partial-discharge pulse pattern identification; partial-discharge pulse pattern recognition; solid dielectric extruded power distribution cables; Cable shielding; Fault location; Fuzzy neural networks; Genetic algorithms; Insulation; Neural networks; Partial discharges; Pattern recognition; Polymers; Power cables; Automatic feature selection; XLPE; cable accessories; fuzzy neural networks; genetic algorithms (GAs); partial-discharge (PD) patterns classification;

fLanguage

English

Journal_Title

Power Delivery, IEEE Transactions on

Publisher

ieee

ISSN

0885-8977

Type

jour

DOI

10.1109/TPWRD.2009.2016826

Filename

5109853