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

Research output: Chapter in Book/Report/Conference proceedingConference 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 languageEnglish
Title of host publication2018 IEEE 2nd International Conference on Dielectrics, ICD 2018
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781538663899
DOIs
Publication statusPublished - 2018 Sep 19
Event2nd IEEE International Conference on Dielectrics, ICD 2018 - Budapest, Hungary
Duration: 2018 Jul 12018 Jul 5

Publication series

Name2018 IEEE 2nd International Conference on Dielectrics, ICD 2018

Other

Other2nd IEEE International Conference on Dielectrics, ICD 2018
CountryHungary
CityBudapest
Period18/7/118/7/5

Fingerprint

Fault detection
Cables
Accidents

All Science Journal Classification (ASJC) codes

  • Electrical and Electronic Engineering
  • Electronic, Optical and Magnetic Materials

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 [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
Ji, Gyeong Hwan ; Lee, Geon Seok ; Lee, Chun Kwon ; Kwon, Gu Young ; Lee, Yeong Ho ; Shin, Yong June. / A Statistical Approach in Time-Frequency Domain Reflectometry for Enhanced Fault Detection. 2018 IEEE 2nd International Conference on Dielectrics, ICD 2018. Institute of Electrical and Electronics Engineers Inc., 2018. (2018 IEEE 2nd International Conference on Dielectrics, ICD 2018).
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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.",
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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; Kwon, Gu Young; Lee, Yeong Ho; Shin, Yong June.

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 proceedingConference contribution

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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.

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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). https://doi.org/10.1109/ICD.2018.8468479