Early Fault Detection Method of Underground Cables Based on Time Domain Characteristic Parameters

As urban reliance on electricity grows, the cableization of distribution networks has increased, making early fault detection more challenging due to cable concealment. This paper proposes a detection method based on a second-order equivalent thermal circuit model and analysis of cable surface temperature changes during early fault stages. By extracting key time-domain features: temperature rise within a set interval and the peak of the temperature derivative. They are compared with reference simulation data to identify fault signatures and define protection criteria. Numerical and program simulations confirm its effectiveness in enhancing early fault detection efficiency.

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Publication Details

Published
2025-08-15
DOI
https://doi.org/10.1109/iccepe66357.2025.11193151
Primary Topic
Power Systems Fault Detection
Type
article
Field-Weighted Citation Impact
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article

Early Fault Detection Method of Underground Cables Based on Time Domain Characteristic Parameters

Zhongwen Zhan, Zikang Li, Lingfeng Gong, K. Wu et al.
Power Systems Fault Detection
article

Early Fault Detection Method of Underground Cables Based on Time Domain Characteristic Parameters

Zhongwen Zhan, Zikang Li, Lingfeng Gong, K. Wu, Xin Xu, Haoran Liu, Sicheng Wang, Ying Guo
article en

Abstract

As urban reliance on electricity grows, the cableization of distribution networks has increased, making early fault detection more challenging due to cable concealment. This paper proposes a detection method based on a second-order equivalent thermal circuit model and analysis of cable surface temperature changes during early fault stages. By extracting key time-domain features: temperature rise within a set interval and the peak of the temperature derivative. They are compared with reference simulation data to identify fault signatures and define protection criteria. Numerical and program simulations confirm its effectiveness in enhancing early fault detection efficiency.

Shanghai Electric (China) (CN)
Openalex Percentile: Top 63%
Power Systems Fault Detection
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Early Fault Detection Method of Underground Cables Based on Time Domain Characteristic Parameters — Zhongwen Zhan, Zikang Li, et al. · (2025) | TGRS Research Map | TGRS