Defect classification based on Weibull statistic of partial discharge height distribution with wavelet preprocessing

Author

Chia, P.Y. ; Liew, A.C.

Author_Institution

Dept. of Electr. Eng., Nat. Univ. of Singapore, Singapore

Volume

2

fYear

2000

fDate

6/22/1905 12:00:00 AM

Firstpage

1035

Abstract

The paper describes a stochastic analysis performed using two-parameter Weibull statistics involving a scheme whereby the PD signals are decomposed using discrete wavelet transform. In a high voltage experimental setup, artificial cylindrical voids were made in a Perspex column of 40 mm in length. The signals obtained from a corona detector were collected via an 8 bit oscilloscope with data storage capabilities. The signals were analyzed using PD height distribution (PDHD). The scheme presents itself as a multi-level Weibull analysis to identify and quantify voids in solid dielectric insulations based on nonultra wide band detection and wavelet aided signal processing

Keywords

Weibull distribution; corona; digital storage oscilloscopes; insulation testing; partial discharge measurement; pulse height analysers; stochastic processes; wavelet transforms; 40 mm; 8 bit oscilloscope; PD signals decomposition; Perspex column; Weibull statistic; artificial cylindrical voids; corona detector; data storage capabilities; defect classification; discrete wavelet transform; multi-level Weibull analysis; nonultra wide band detection; partial discharge height distribution; signals; solid dielectric insulations; stochastic analysis; two-parameter Weibull statistics; wavelet aided signal processing; wavelet preprocessing; Corona; Detectors; Discrete wavelet transforms; Performance analysis; Signal analysis; Statistical analysis; Statistics; Stochastic processes; Voltage; Wavelet analysis;

fLanguage

English

Publisher

ieee

Conference_Titel

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

Print_ISBN

0-7803-6338-8

Type

conf

DOI

10.1109/ICPST.2000.897163

Filename

897163