Skip to content
2000
Volume 18, Issue 5
  • ISSN: 2352-0965
  • E-ISSN: 2352-0973

Abstract

Background

The large-scale aging of cross-linked polyethylene (XPLE) leads to an increase in the frequency of power cable accidents, which poses a threat to the safe operation of the power grid.

Objective

Traditional time-frequency domain reflectometry (TFDR) techniques for fault localization in power cables are susceptible to cross-terms interference, which makes it impossible to accurately locate defects. To overcome the limitation, this paper has proposed a novel cable fault localization method based on S-transform.

Methods

The method employs S-transform to perform time-frequency analysis on the collected signals of TFDR, mapping the time-domain signals into time-frequency domain signals. Then, cross-correlation of the time-frequency domain signals is estimated, allowing for accurate positioning of cable defects.

Results

The results of the field experiments conducted on a 10 kV cross-linked polyethylene cable with artificially introduced defects have demonstrated that the proposed method could effectively locate the cable defects with small absolute error.

Conclusion

Compared to existing TFDR methods, the proposed method has been found to be free from interference of cross-terms, resulting in higher reliability and smaller blind spots for detecting cable defects.

© 2025 Bentham Science Publishers
Loading

Article metrics loading...

/content/journals/raeeng/10.2174/0123520965266890231125133247
2025-06-01
2025-11-05

  • From This Site

    /content/journals/raeeng/10.2174/0123520965266890231125133247
    dcterms_title,dcterms_subject,pub_keyword
    -contentType:Contributor -contentType:Concept -contentType:Institution
    10
    5
Loading full text...

Full text loading...

References

  1. WangY. YanZ. WuY. Numerical simulation of fretting fatigue damage evolution of cable wires considering corrosion and wear effects.Comput. Model. Eng. Sci.202313621339137010.32604/cmes.2023.025830
     [Google Scholar]
  2. WangY. ZhengY. Simulation of damage evolution and study of multi-fatigue source fracture of steel wire in bridge cables under the action of pre-corrosion and fatigue.Comput. Model. Eng. Sci.2019120237541910.32604/cmes.2019.06905
     [Google Scholar]
  3. NielsonT. OwensG. MillerB. MeneghiniE. DeckardE.R. MeneghiniR.M. Large femoral heads in total hip arthroplasty with vitamin e highly cross-linked polyethylene: Head penetration rates compared to highly cross-linked polyethylene.J. Arthroplasty2022377S685S69110.1016/j.arth.2022.01.075 35227535
     [Google Scholar]
  4. MaglarasL.A. FerragM.A. JanickeH. AyresN. TassiulasL. Reliability, security, and privacy in power grids.Computer2022559858810.1109/MC.2022.3184425
     [Google Scholar]
  5. Iturrino GarciaC.A. BindiM. CortiF. LuchettaA. GrassoF. PaolucciL. PiccirilliM.C. AizenbergI. Power quality analysis based on machine learning methods for low-voltage electrical distribution lines.Energies2023169362710.3390/en16093627
     [Google Scholar]
  6. CaicedoJ.E. Agudelo-MartínezD. Rivas-TrujilloE. MeyerJ. A systematic review of real-time detection and classification of power quality disturbances.Prot. Control Mod. Power Sys.202381310.1186/s41601‑023‑00277‑y
     [Google Scholar]
  7. FritschM. WolterM. Transmission model of partial discharges on medium voltage cables.IEEE Trans. Power Deliv.202237139540410.1109/TPWRD.2021.3061201
     [Google Scholar]
  8. SteinerJ.P. ReynoldsP.H. WeeksW.L. Estimating the location of partial discharges in cables.IEEE Trans. Electr. Insul.1992271445910.1109/14.123440
     [Google Scholar]
  9. MardianaR. SuC. Partial discharge location in power cables using a phase difference method.IEEE Trans. Dielectr. Electr. Insul.201017617381746[J].10.1109/TDEI.2010.5658224
     [Google Scholar]
  10. OhkiY. HiraiN. YamadaT. Highly sensitive location method of an abnormal temperature point in a cable by frequency domain reflectometrytIEEE International Conference on Solid Dielectrics (ICSD)201311712030 June 2013 - 04 July 2013, Bologna, Italy10.1109/ICSD.2013.6619799
     [Google Scholar]
  11. ChungY.C. FurseC. PruittJ. Application of phase detection frequency domain reflectometry for locating faults in an F-18 flight control harness.IEEE Trans. Electromagn. Compat.200547232733410.1109/TEMC.2005.847403
     [Google Scholar]
  12. OhkiY. HiraiN. Effects of the structure and insulation material of a cable on the ability of a location method by FDR.IEEE Trans. Dielectr. Electr. Insul.2016231778410.1109/TDEI.2015.005521
     [Google Scholar]
  13. ZhouZ. ZhangD. HeJ. LiM. Local degradation diagnosis for cable insulation based on broadband impedance spectroscopy.IEEE Trans. Dielectr. Electr. Insul.20152242097210710.1109/TDEI.2015.004799
     [Google Scholar]
  14. TangZ. ZhouK. MengP. LiY. A frequency-domain location method for defects in cables based on power spectral density.IEEE Trans. Instrum. Meas.202271900511011010.1109/TIM.2022.3189636
     [Google Scholar]
  15. ShiX. ZhangL. JingT. Research of aircraft cable fray fault detecting method based on Hilbert Huang transformation2010 8th World Congress on Intelligent Control and Automation202007-09 July 2010, Jinan
     [Google Scholar]
  16. KafalM. CozzaA. PichonL. Locating faults with high resolution using single-frequency TR-MUSIC processing.IEEE Trans. Instrum. Meas.201665102342234810.1109/TIM.2016.2578578
     [Google Scholar]
  17. BangS.S. ShinY.J. Classification of faults in multicore cable via time-frequency domain reflectometry.IEEE Trans. Ind. Electron.20206754163417110.1109/TIE.2019.2920606
     [Google Scholar]
  18. LimH. KwonG.Y. ShinY.J. Fault detection and localization of shielded cable via optimal detection of time–frequency-domain reflectometry.IEEE Trans. Instrum. Meas.202170352151011010.1109/TIM.2021.3092514
     [Google Scholar]
  19. LeeC. CoatsD. LeeC. Diagnosis of cables in nuclear power plants using joint time-frequency domain reflectometryIFAC Proceedings201346297478
     [Google Scholar]
  20. ZouX. MuH. QuL. ZhangH. XieC. ZhangG. Localization and assessment of breakage defect in cables based on time–frequency domain reflectometry.Energy Rep.2022851474148110.1016/j.egyr.2022.02.202
     [Google Scholar]
  21. WuY. LiX. Elimination of cross‐terms in the Wigner–Ville distribution of multi‐component LFM signals.IET Signal Process.201711665766210.1049/iet‑spr.2016.0358
     [Google Scholar]
  22. KwonG.Y. LeeC.K. LeeG.S. LeeY.H. ChangS.J. JungC-K. KangJ-W. ShinY-J. Offline fault localization technique on HVDC submarine cable via time-frequency domain reflectometry.IEEE Trans. Power Deliv.20173231626163510.1109/TPWRD.2017.2680459
     [Google Scholar]
  23. LiuW. LiuY. LiS. Demodulated multisynchrosqueezing S transform for fault diagnosis of rotating machinery.IEEE Sens. J.20222221207732078410.1109/JSEN.2022.3206509
     [Google Scholar]
  24. WeiZ. MaoY. YinZ. SunG. ZangH. Fault detection based on the generalized s-transform with a variable factor for resonant grounding distribution networks.IEEE Access20208913519136710.1109/ACCESS.2020.2994139
     [Google Scholar]
  25. SongE. ShinY.J. StoneP.E. WangJ. ChoeT-S. YookJ-G. ParkJ.B. Detection and location of multiple wiring faults via time–frequency-domain reflectometry.IEEE Trans. Electromagn. Compat.200951113113810.1109/TEMC.2008.2007964
     [Google Scholar]
  26. ShinY.J. PowersE.J. ChoeT-S. HongC-Y. SongE-S. YookJ-G. ParkJ.B. Application of time-frequency domain reflectometry for detection and localization of a fault on a coaxial cable.IEEE Trans. Instrum. Meas.20055462493250010.1109/TIM.2005.858115
     [Google Scholar]
  27. ZhangL. WangX. TianS. LiY. Fault location method of distribution network based on transient energy relative entropy of S-transform2012 24th Chinese Control and Decision Conference (CCDC)20122325May 2012, Taiyuan, China
     [Google Scholar]
  28. DashP.K. PanigrahiB.K. PandaG. Power quality analysis using s-transform.IEEE Trans. Power Deliv.200318240641110.1109/TPWRD.2003.809616
     [Google Scholar]
  29. KrzysztofG.Ó.R.E.C.K.I. MirosławS.Z.M.A.J.D.A. JarosławZ.Y.G.A.R.L.I.C.K.I. Zaawansowane metody analiz w pomiarach jakości energii elektrycznej.Pomiary Automatyka Kontrola2011573284286
     [Google Scholar]
  30. Shweta NandK. Time- frequency based detection of faulted line and fault instant using wide area signals2019 International Conference on Electrical, Electronics and Computer Engineering (UPCON)2019 08-10 November 2019, Aligarh, India
     [Google Scholar]
  31. KimN-K. OhS-J. Comparison of methods for parameter estimation of frequency hopping signalsInternational Conference on Information and Communication Technology Convergence (ICTC)201756756918-20 October 2017, Jeju, Korea10.1109/ICTC.2017.8191042
     [Google Scholar]
  32. TangZ. XuY. ZhouK. MengP. HuangJ. LiangZ. A frequency sweep location method for soft faults of power cables based on MUSIC-pseudospectrum.IEEE Trans. Instrum. Meas.202372351041011010.1109/TIM.2023.3258522
     [Google Scholar]
/content/journals/raeeng/10.2174/0123520965266890231125133247
Loading
A Novel Time-frequency Domain Reflectometry Method Based on S-transform for Power Cable Defect Localization
Recent Advances in Electrical & Electronic Engineering 18, 563 (2025); https://doi.org/10.2174/0123520965266890231125133247
/content/journals/raeeng/10.2174/0123520965266890231125133247
/content/journals/raeeng/10.2174/0123520965266890231125133247
Loading

Data & Media loading...


  • Article Type:     Research Article
Keyword(s): cross-correlation; cross-linked polyethylene; Defect localization; power cable; S-transform; time-frequency domain reflectometry

Most Cited Most Cited RSS feed

This is a required field
Please enter a valid email address
Approval was a Success
Invalid data
An Error Occurred
Approval was partially successful, following selected items could not be processed due to error
Please enter a valid_number test