Research On Cable Fault Location Method Based on Improved Variational Modal Decomposition

Cable is an important carrier of electric power transmission and distribution in electric power system, due to the long-term operation of the cable in the complex environment is susceptible to a variety of factors affecting the occurrence of faults. In this paper, a cable fault location technique based on improved variational modal decomposition (VMD) is proposed to improve the accuracy and reliability of cable fault location by introducing the concept of instantaneous frequency mean to optimise the VMD algorithm and combining with the Wegner-Ville Distribution (WVD) signal processing technique, and the accuracy and applicability of the method are verified by simulation experiments under different fault scenarios.

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Publication Details

Published
2025-06-20
DOI
https://doi.org/10.1109/eee64897.2025.11162818
Primary Topic
Power Systems Fault Detection
Type
article
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article

Research On Cable Fault Location Method Based on Improved Variational Modal Decomposition

Chunjie Lian, D.C. Wang, Hanmin Huang, Chengcheng Wang et al.
Power Systems Fault Detection
article

Research On Cable Fault Location Method Based on Improved Variational Modal Decomposition

Chunjie Lian, D.C. Wang, Hanmin Huang, Chengcheng Wang, Yu‐Ye Li, Jun Chen, Xintong Han
article en

Abstract

Cable is an important carrier of electric power transmission and distribution in electric power system, due to the long-term operation of the cable in the complex environment is susceptible to a variety of factors affecting the occurrence of faults. In this paper, a cable fault location technique based on improved variational modal decomposition (VMD) is proposed to improve the accuracy and reliability of cable fault location by introducing the concept of instantaneous frequency mean to optimise the VMD algorithm and combining with the Wegner-Ville Distribution (WVD) signal processing technique, and the accuracy and applicability of the method are verified by simulation experiments under different fault scenarios.

Guangxi Science and Technology Department (CN)
Openalex Percentile: Top 68%
Power Systems Fault Detection
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