A Statistical Approach in Time-Frequency Domain Reflectometry for Enhanced Fault Detection

被引：0

作者：

Ji, Gyeong Hwan ^{[1
]}

Lee, Geon Seok ^{[1
]}

Lee, Chun-Kwon ^{[1
]}

Kwon, Gu-Young ^{[1
]}

Lee, Yeong Ho ^{[1
]}

Shin, Yong-June ^{[1
]}

机构：

[1] Yonsei Univ, Sch Elect & Elect Engn, Seoul, South Korea

来源：

2018 IEEE 2ND INTERNATIONAL CONFERENCE ON DIELECTRICS (ICD) | 2018年

基金：

新加坡国家研究基金会;

关键词：

fault detection; skewness; time-frequency analysis; reflectometry; DEGRADATION; MECHANISM;

D O I：

暂无

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

Fault detection and localization of an electrical cable are essential to prevent a serious accident of cable system originated from the cable failure. Despite the outstanding performance in fault detection and localization, time-frequency domain refletometry (TFDR) faces an important issue of reliability of the diagnostic result. In this paper, skewness of time-frequency cross-correlation is used as the additional index to examine the existence of the unrevealed fault. In order to verify the validity of the proposed method, simulation is carried out with various types of fault occurrence circumstances. The analytic discussion on the simulation results is presented, and it is found to support effectiveness of the proposed method. It is expected that the proposed method will contribute to enhance the diagnostic performance of TFDR.

引用

页数：4

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