Analysis of PD patterns with integrated distribution parameters using modular neural networks

Author

Chang, C. ; Su, Q.

Author_Institution

Dept. of Electr. & Comput. Syst. Eng., Monash Univ., Clayton, Vic., Australia

Volume

1

fYear

2000

fDate

2000

Firstpage

259

Abstract

Computer based partial discharge (PD) source identification using phase resolved (PRPD) and/or pulse height resolved (PHPD) PD distribution variables is regarded as an important step for insulation diagnosis. Based on those defined in the IEC 270 international standard, distribution variables, derived from both PRPD and PHPD are investigated with a modular neural network approach for PD pattern classification purpose. In this paper, it has been illustrated that with a new PD measuring and analysis system, statistical parameters of PRPD and PHPD distribution variables are practically useful for the identification of PD sources of different type. The applicability of this approach has been demonstrated by obtaining the results from experiments

Keywords

IEC standards; insulation testing; neural nets; partial discharge measurement; pattern classification; power engineering computing; statistical analysis; IEC 270 international standard; PD patterns analysis; computer based partial discharge; distribution variables; insulation diagnosis; integrated distribution parameters; modular neural networks; pulse height resolved; pulse height resolved PD distribution variables; source identification; statistical analysis; statistical parameters; Computer networks; Detectors; Distributed computing; Frequency; IEC standards; Insulation; Neural networks; Partial discharge measurement; Partial discharges; Pattern analysis;

fLanguage

English

Publisher

ieee

Conference_Titel

Power System Technology, 2000. Proceedings. PowerCon 2000. International Conference on

Conference_Location

Perth, WA

Print_ISBN

0-7803-6338-8

Type

conf

DOI

10.1109/ICPST.2000.900066

Filename

900066