Aging recognition of partial discharge patterns using neural network and semi-fractal dimension

Author

Jang-seob, Lim ; Young-sik, Park ; Cheol-su, Kim ; Myoung-rae, Jeong ; Woo-sung, Jung ; Tae-sung, Kim

Author_Institution

Fac. of M.E.C. Eng., Mokpo Nat. Maritime Univ., Chonnam, South Korea

Volume

1

fYear

1997

Firstpage

290

Abstract

Aging diagnosis system using partial discharge (PD) is being highlighted as a research area for preventive diagnosis. But the application of PD for aging diagnosis requires complicated analysis method because of its complex progressing mechanism. In this paper, it has been developed new approach method to express the Semi-Fractal Dimension (SFD) of the tree pattern using image processing and the PD diagnosis system using Neural Network (NN). As a result after NN learning (SFD:1.2-1.3), the recognized rate of similar stress (SFD:1.2-1.4) was represented about 85%. In case of high stress (SFD:1.5-1.6), the safety area is possible to express the second output of NN in this experiments

Keywords

ageing; fractals; insulation testing; neural nets; partial discharges; pattern recognition; trees (electrical); aging; diagnosis system; image processing; neural network; partial discharge; pattern recognition; safety area; semi-fractal dimension; tree; Aging; Electrodes; Fractals; Image processing; Life estimation; Needles; Neural networks; Partial discharges; Pattern recognition; Safety;

fLanguage

English

Publisher

ieee

Conference_Titel

Properties and Applications of Dielectric Materials, 1997., Proceedings of the 5th International Conference on

Conference_Location

Seoul

Print_ISBN

0-7803-2651-2

Type

conf

DOI

10.1109/ICPADM.1997.617585

Filename

617585