Design of Hilbert Fractal Antenna for Partial Discharge Detection and Classification

被引：0

作者：

Zahed, Abdalmonam H. ^{[1
]}

Harbaji, Mustafa M. ^{[1
]}

Habboub, Shahed A. ^{[1
]}

AlMajidi, Maryam A. ^{[1
]}

Assaf, Mustafa J. ^{[1
]}

El-Hag, Ayman H. ^{[1
]}

Qaddoumi, Nasser N. ^{[1
]}

机构：

[1] Amer Univ Sharjah, Dept Elect Engn, Sharjah, U Arab Emirates

来源：

2015 4TH INTERNATIONAL CONFERENCE ON ELECTRIC POWER AND ENERGY CONVERSION SYSTEMS (EPECS) | 2015年

关键词：

component; Condition monitoring; Hilbert fractal antenna; partial discharges (PDs); pattern recognition; Ultra-high frequency (UHF); PATTERN-RECOGNITION; POWER TRANSFORMERS; UHF; SIGNALS;

D O I：

暂无

中图分类号：

TE [石油、天然气工业]; TK [能源与动力工程];

学科分类号：

0807 ; 0820 ;

摘要：

This paper presents the design of a Hilbert fractal antenna for the purpose of detecting and classifying different partial discharge (PD) types in an oil-paper insulated system. Three common types of PDs are considered for the multi-class classification problem, namely; PD from a sharp point to ground plane, surface discharge, and PD from a void in the insulation. The designed antenna is connected to a high frequency spectrum analyzer to acquire PD samples in the frequency domain. The different PD types showed unique frequency patterns for each type. In addition, the collected samples are processed using pattern recognition techniques to automatically identify their corresponding PD types. A recognition rate of 95% was achieved when classifying the different PD types.

引用

页数：4

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