A Novel Method for Localizing PD Source in Power Transformer: Considering NLOS Propagation of Electromagnetic Waves

A novel partial discharge (PD) source localization method was proposed based on the traditional time difference in arrival (TDOA) method. Specifically, the non-line-of-sight (NLOS) propagation phenomenon of the ultra-high-frequency (UHF) signal was considered, and the NLOS propagation error was approximately replaced by a constant, thereby limiting the effect of NLOS propagation. Moreover, the strategy of utilizing more than four sensors was adopted to reduce the possible effect of overcorrection on NLOS propagation. In this paper, the derivation and implementation process of the proposed method is introduced from the perspectives of mathematical model and geometrical model, and its localization results were compared with the traditional TDOA method through an experimental study. The results showed that the speed of error increase of the traditional method presented faster, and the increment of sensor number helped to improve the localization accuracy, but the reduction in localization error becomes insignificant when the sensors exceed six. Finally, the experimental verifications were conducted based on a 35 kV testing transformer with six sensor installations. The experiments found that the proposed localization method had a better calculated accuracy and stability; the obtained minimum calculated error was 10.88 cm, the calculated accuracy can be improved by 82.04% and 78.94%, respectively, with six sensors than four and five sensors arrangement.

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Publication Details

Journal
Sensors
Published
2025-08-16
DOI
https://doi.org/10.3390/s25165099
Citations
1
Primary Topic
High voltage insulation and dielectric phenomena
Type
article
Field-Weighted Citation Impact
0.52

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article

A Novel Method for Localizing PD Source in Power Transformer: Considering NLOS Propagation of Electromagnetic Waves

Chao Gu, Zijun Pan, Cheng Pan, Mengzhao Zhu et al.
1 citations
Sensors
High voltage insulation and dielectric phenomena
0.52
article

A Novel Method for Localizing PD Source in Power Transformer: Considering NLOS Propagation of Electromagnetic Waves

Chao Gu, Zijun Pan, Cheng Pan, Mengzhao Zhu, Qingdong Zhu, Wenbing Zhu
article en
1 citations

Abstract

A novel partial discharge (PD) source localization method was proposed based on the traditional time difference in arrival (TDOA) method. Specifically, the non-line-of-sight (NLOS) propagation phenomenon of the ultra-high-frequency (UHF) signal was considered, and the NLOS propagation error was approximately replaced by a constant, thereby limiting the effect of NLOS propagation. Moreover, the strategy of utilizing more than four sensors was adopted to reduce the possible effect of overcorrection on NLOS propagation. In this paper, the derivation and implementation process of the proposed method is introduced from the perspectives of mathematical model and geometrical model, and its localization results were compared with the traditional TDOA method through an experimental study. The results showed that the speed of error increase of the traditional method presented faster, and the increment of sensor number helped to improve the localization accuracy, but the reduction in localization error becomes insignificant when the sensors exceed six. Finally, the experimental verifications were conducted based on a 35 kV testing transformer with six sensor installations. The experiments found that the proposed localization method had a better calculated accuracy and stability; the obtained minimum calculated error was 10.88 cm, the calculated accuracy can be improved by 82.04% and 78.94%, respectively, with six sensors than four and five sensors arrangement.

SensorsVol. 25(16)
Wuhan University (CN)
Science and Technology Project of State Grid, State Grid Shandong Electric Power Company
Openalex Percentile: Top 34%
High voltage insulation and dielectric phenomena
0.52
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A Novel Method for Localizing PD Source in Power Transformer: Considering NLOS Propagation of Electromagnetic Waves — Chao Gu, Zijun Pan, et al. · Sensors (2025) | TGRS Research Map | TGRS