A neural network used for PD pattern recognition with genetic algorithm

Author

Wu, Guangning ; Jiang, Xiongwei ; Xie, Hengkun

Author_Institution

Southwest Jiaotong Univ., Chengdu, China

Volume

1

fYear

2000

fDate

2000

Firstpage

451

Abstract

In this paper, a new neural network with genetic algorithm (GA) is described. GA can overcome the disadvantages of back propagation (BP) artificial neural network (ANN), such as slow convergence and possibility of being trapped at locally minimum value. Compared with BP-ANN, the convergence and generalization ability of GA-ANN is improved remarkably. Some typical discharges in large turbine generators are presented and discussed. Test results show that the neural network may discriminate unknown patterns successfully. Some new results are given, and practical application of neural network for pattern recognition of PD in with genetic algorithm is also discussed

Keywords

backpropagation; convergence; generalisation (artificial intelligence); genetic algorithms; insulation testing; machine insulation; machine testing; neural nets; partial discharges; pattern recognition; turbogenerators; artificial neural network; backpropagation; convergence; electrical insulation; generalization; genetic algorithm; high voltage power apparatus; partial discharge; pattern recognition; turbine generator; Artificial neural networks; Convergence; Dielectrics and electrical insulation; Encoding; Evolution (biology); Genetic algorithms; Neural networks; Partial discharges; Pattern recognition; Power system reliability;

fLanguage

English

Publisher

ieee

Conference_Titel

Properties and Applications of Dielectric Materials, 2000. Proceedings of the 6th International Conference on

Conference_Location

Xi´an

Print_ISBN

0-7803-5459-1

Type

conf

DOI

10.1109/ICPADM.2000.875727

Filename

875727