Data compression and pattern recognition for partial discharge ultrasonic signal based on fractal theory

Author

Yunpeng, Liu ; Fangcheng, Lu ; Zhiye, Chen ; Yanqing, Li

Author_Institution

Dept. of Electr. Eng., North China Electr. Power Univ., Hebei, China

Volume

2

fYear

2002

fDate

2002

Firstpage

958

Abstract

According to the complex, nonstationary and nonderivative characteristics of partial discharge (PD) ultrasonic signal, the piecewise self-affine iterated function system (IFS) model of PD ultrasonic signals is established. The IFS parameters of this model are calculated to realize data compression. The IFS fractal dimension is extracted based on this model which is provided for partial discharge pattern recognition. The novel route is that both the tasks of compression and feature extraction in a single step, affords a new tool for on-line monitoring of partial discharge in a transformer.

Keywords

acoustic signal processing; data compression; fractals; insulation testing; partial discharge measurement; pattern recognition; power transformer insulation; power transformer testing; ultrasonic measurement; PD ultrasonic signals; data compression; fractal theory; on-line monitoring; partial discharge pattern recognition; partial discharge ultrasonic signal; pattern recognition; piecewise self-affine iterated function system; transformer; Contracts; Data compression; Fractals; Interpolation; Partial discharges; Pattern recognition; Power system security; Power system stability; Power transformer insulation; Power transformers;

fLanguage

English

Publisher

ieee

Conference_Titel

Power System Technology, 2002. Proceedings. PowerCon 2002. International Conference on

Print_ISBN

0-7803-7459-2

Type

conf

DOI

10.1109/ICPST.2002.1047541

Filename

1047541