Title :
Application of neural network with genetic algorithm to UHF PD pattern recognition in transformers
Author :
Ping, Shan ; Dake, Xu ; Guoli, Wang ; Yanming, Li
Author_Institution :
Sch. of Electr. Eng., Xi´´an Jiaotong Univ., China
Abstract :
In this paper, an automated recognition system of ultra-high-frequency (UHF) PD designed by authors has been put forward to study the discharge properties in transformers. This paper presents Genetic Algorithm (GA) to train neural network (NN). Using BP-NN and GA-NN, we distinguish between basic types of defects appearing in transformers, such as corona, void, bubble, creeping discharge and floating discharge. Tests in laboratory give satisfactory results of classification. Compared with BP-NN, GA-NN can overcome slow convergence and possibility of being trapped at local minimum value. Thus, the convergence, discrimination and generalization ability of GA-NN is improved remarkably.
Keywords :
genetic algorithms; neural nets; partial discharges; power transformer insulation; UHF PD pattern recognition; bubble; corona; creeping discharge; floating discharge; genetic algorithm; neural network application; partial discharge; transformers; void; Convergence; Corona; Fingerprint recognition; Frequency; Genetic algorithms; Intelligent networks; Neural networks; Partial discharges; Pattern recognition; Transformers;
Conference_Titel :
Electrical Insulation and Dielectric Phenomena, 2002 Annual Report Conference on
Print_ISBN :
0-7803-7502-5
DOI :
10.1109/CEIDP.2002.1048900