A neural network used for PD pattern recognition in large turbine generators with genetic algorithm

Author

Wu, Guangning

Author_Institution

Sch. of Electr. Eng., Southwest Jiaotong Univ., Sichuan, China

fYear

2000

fDate

2000

Firstpage

1

Lastpage

4

Abstract

The paper introduces a new neural network with a genetic algorithm for use in on-line partial discharge (PD) monitoring of large turbine generators. The disadvantages of the BP algorithm which is generally used for PD pattern recognition are discussed. As a result of these shortcomings, a new neural network is presented using a genetic algorithm. To ensure the suitability of the chosen network for PD recognition, the PD patterns which generally occur in large generators were simulated and tested. Test results show that the new neural network can meet the need of PD pattern recognition in large generators satisfactory

Keywords

electric machine analysis computing; genetic algorithms; insulation testing; machine insulation; neural nets; partial discharges; pattern recognition; turbogenerators; PD pattern recognition; code optimizing variable; genetic algorithm; large turbine generators; model generator; neural network; on-line PD monitoring; Cities and towns; Genetic algorithms; Intelligent networks; Monitoring; Neural networks; Partial discharges; Pattern recognition; Test pattern generators; Testing; Turbines;

fLanguage

English

Publisher

ieee

Conference_Titel

Electrical Insulation, 2000. Conference Record of the 2000 IEEE International Symposium on

Conference_Location

Anaheim, CA

ISSN

1089-084X

Print_ISBN

0-7803-5931-3

Type

conf

DOI

10.1109/ELINSL.2000.845406

Filename

845406