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

Gyeong Hwan Ji; Geon Seok Lee; Chun Kwon Lee; Gu Young Kwon; Yeong Ho Lee; Yong June Shin

doi:10.1109/ICD.2018.8468479

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

Gyeong Hwan Ji, Geon Seok Lee, Chun Kwon Lee, Gu Young Kwon, Yeong Ho Lee, Yong June Shin

Department of Electrical and Electronic Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

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.

Original language	English
Title of host publication	2018 IEEE 2nd International Conference on Dielectrics, ICD 2018
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)	9781538663899
DOIs	https://doi.org/10.1109/ICD.2018.8468479
Publication status	Published - 2018 Sept 19
Event	2nd IEEE International Conference on Dielectrics, ICD 2018 - Budapest, Hungary Duration: 2018 Jul 1 → 2018 Jul 5

Publication series

Name	2018 IEEE 2nd International Conference on Dielectrics, ICD 2018

Other

Other	2nd IEEE International Conference on Dielectrics, ICD 2018
Country/Territory	Hungary
City	Budapest
Period	18/7/1 → 18/7/5

Bibliographical note

Publisher Copyright:
© 2018 IEEE.

All Science Journal Classification (ASJC) codes

Electrical and Electronic Engineering
Electronic, Optical and Magnetic Materials

Access to Document

10.1109/ICD.2018.8468479

Cite this

Ji, G. H., Lee, G. S., Lee, C. K., Kwon, G. Y., Lee, Y. H., & Shin, Y. J. (2018). A Statistical Approach in Time-Frequency Domain Reflectometry for Enhanced Fault Detection. In 2018 IEEE 2nd International Conference on Dielectrics, ICD 2018 Article 8468479 (2018 IEEE 2nd International Conference on Dielectrics, ICD 2018). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICD.2018.8468479

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title = "A Statistical Approach in Time-Frequency Domain Reflectometry for Enhanced Fault Detection",

abstract = "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.",

keywords = "Fault detection, Reflectometry, Skewness, Time-frequency analysis",

author = "Ji, {Gyeong Hwan} and Lee, {Geon Seok} and Lee, {Chun Kwon} and Kwon, {Gu Young} and Lee, {Yeong Ho} and Shin, {Yong June}",

note = "Publisher Copyright: {\textcopyright} 2018 IEEE.; 2nd IEEE International Conference on Dielectrics, ICD 2018 ; Conference date: 01-07-2018 Through 05-07-2018",

year = "2018",

month = sep,

day = "19",

doi = "10.1109/ICD.2018.8468479",

language = "English",

series = "2018 IEEE 2nd International Conference on Dielectrics, ICD 2018",

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Ji, GH, Lee, GS, Lee, CK, Kwon, GY, Lee, YH & Shin, YJ 2018, A Statistical Approach in Time-Frequency Domain Reflectometry for Enhanced Fault Detection. in 2018 IEEE 2nd International Conference on Dielectrics, ICD 2018., 8468479, 2018 IEEE 2nd International Conference on Dielectrics, ICD 2018, Institute of Electrical and Electronics Engineers Inc., 2nd IEEE International Conference on Dielectrics, ICD 2018, Budapest, Hungary, 18/7/1. https://doi.org/10.1109/ICD.2018.8468479

A Statistical Approach in Time-Frequency Domain Reflectometry for Enhanced Fault Detection. / Ji, Gyeong Hwan; Lee, Geon Seok; Lee, Chun Kwon et al.
2018 IEEE 2nd International Conference on Dielectrics, ICD 2018. Institute of Electrical and Electronics Engineers Inc., 2018. 8468479 (2018 IEEE 2nd International Conference on Dielectrics, ICD 2018).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

TY - GEN

T1 - A Statistical Approach in Time-Frequency Domain Reflectometry for Enhanced Fault Detection

AU - Ji, Gyeong Hwan

AU - Lee, Geon Seok

AU - Lee, Chun Kwon

AU - Kwon, Gu Young

AU - Lee, Yeong Ho

AU - Shin, Yong June

PY - 2018/9/19

Y1 - 2018/9/19

N2 - 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.

AB - 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.

KW - Fault detection

KW - Reflectometry

KW - Skewness

KW - Time-frequency analysis

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Ji GH, Lee GS, Lee CK, Kwon GY, Lee YH, Shin YJ. A Statistical Approach in Time-Frequency Domain Reflectometry for Enhanced Fault Detection. In 2018 IEEE 2nd International Conference on Dielectrics, ICD 2018. Institute of Electrical and Electronics Engineers Inc. 2018. 8468479. (2018 IEEE 2nd International Conference on Dielectrics, ICD 2018). doi: 10.1109/ICD.2018.8468479

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

Abstract

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