Phase Selection Method for 10 kV Three-Core Cables Under Single-Phase Grounding Fault Transient Based on Surface Magnetic Field Sensing

Single-phase grounding is the dominant fault type in urban power distribution networks. Because the total magnetic flux would not change around the cable under a single-phase grounding fault, ferromagnetic zero-sequence current sensors cannot distinguish the faulted phase of belted cables, which are the main type in 10 kV distribution networks. To fill this gap, a two-step methodology is proposed using an annular TMR magnetic sensor to measure the magnetic field intensity at six points on the cable surface and to distinguish the faulted phase using the magnetic field intensity differences between the TMRs. The first step is calculating the rotation angles between the six magnetic sensors and the three cable cores after installation. A differential evolution algorithm is used to calculate the rotation angles in the sensing model. The second step is to detect the fault phase under a single-phase grounding fault transient, with the magnetic field intensity difference taken as the criterion. The methodology is verified through simulation and experiment. The results show that the relative errors of the rotation angles are all less than 1%. Under a single-phase grounding fault, the faulted phase can be accurately identified. The proposed method can effectively identify the faulted phase of 10 kV three-core cables under single-phase grounding and has significant engineering application value.

Authors

Institutions

Publication Details

Journal
Sensors
Published
2026-02-04
DOI
https://doi.org/10.3390/s26031016
Primary Topic
Magnetic Field Sensors Techniques
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Phase Selection Method for 10 kV Three-Core Cables Under Single-Phase Grounding Fault Transient Based on Surface Magnetic Field Sensing

Zheng Xiao, Tianhu Weng, Shuai Yang, Wenfang Ding et al.
Sensors
Magnetic Field Sensors Techniques
article

Phase Selection Method for 10 kV Three-Core Cables Under Single-Phase Grounding Fault Transient Based on Surface Magnetic Field Sensing

Zheng Xiao, Tianhu Weng, Shuai Yang, Wenfang Ding, Hang Wang, Hang Li, Jun Chen
article en

Abstract

Single-phase grounding is the dominant fault type in urban power distribution networks. Because the total magnetic flux would not change around the cable under a single-phase grounding fault, ferromagnetic zero-sequence current sensors cannot distinguish the faulted phase of belted cables, which are the main type in 10 kV distribution networks. To fill this gap, a two-step methodology is proposed using an annular TMR magnetic sensor to measure the magnetic field intensity at six points on the cable surface and to distinguish the faulted phase using the magnetic field intensity differences between the TMRs. The first step is calculating the rotation angles between the six magnetic sensors and the three cable cores after installation. A differential evolution algorithm is used to calculate the rotation angles in the sensing model. The second step is to detect the fault phase under a single-phase grounding fault transient, with the magnetic field intensity difference taken as the criterion. The methodology is verified through simulation and experiment. The results show that the relative errors of the rotation angles are all less than 1%. Under a single-phase grounding fault, the faulted phase can be accurately identified. The proposed method can effectively identify the faulted phase of 10 kV three-core cables under single-phase grounding and has significant engineering application value.

SensorsVol. 26(3)
State Grid Corporation of China (China) (CN), Hubei University of Technology (CN)
State Grid Corporation of China
Sustainable cities and communities
Openalex Percentile: Top 67%
Magnetic Field Sensors Techniques
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.