Simulation of Magnetic-Thermal Distribution Patterns and Fault Identification under Inter-Turn Short Circuits in Potential Transformer

WU Tian; LIU Xiulei; WANG Nanji; FENG Xinglong; WANG Shenhua; JU Xinyue

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Simulation of Magnetic-Thermal Distribution Patterns and Fault Identification under Inter-Turn Short Circuits in Potential Transformer

更新时间：2026-08-25

- Simulation of Magnetic-Thermal Distribution Patterns and Fault Identification under Inter-Turn Short Circuits in Potential Transformer
- High VoltageApparatus (2026)
- 作者机构：
  
  1.三峡大学电气与新能源学院，湖北宜昌 443002
  2.湖北省输电线路工程技术研究中心，湖北宜昌 443002
  3.国网濉溪县供电公司，安徽淮北 235100
  4.国网湖北直流公司，湖北宜昌 443005
  5.国网浙江省电力有限公司武义供电公司，浙江金华 321200
- 作者简介：
- 基金信息：
  
  Youth Foundation of National Natural Science Foundation of China(51807110)
- DOI：
  CLC：
- Received：02 June 2026，
  
  Revised：2026-08-11，
  
  Accepted：24 August 2026，
- 稿件说明：
移动端阅览
WU Tian, LIU Xiulei, WANG Nanji, et al. Simulation of Magnetic-Thermal Distribution Patterns and Fault Identification under Inter-Turn Short Circuits in Potential Transformer[J/OL]. High VoltageApparatus, 2026.
DOI：

WU Tian, LIU Xiulei, WANG Nanji, et al. Simulation of Magnetic-Thermal Distribution Patterns and Fault Identification under Inter-Turn Short Circuits in Potential Transformer[J/OL]. High VoltageApparatus, 2026. DOI：

摘要

电压互感器长期处于恶劣的运行环境中，在各种过应力下绕组绝缘可能发生局部匝间短路故障，影响设备的计量性能和运行安全。然而，现有针对电压互感器局部匝间短路故障引发漏磁畸变与局部过热的研究相对不足，尚难系统揭示短路位置和匝数对磁-热场分布形态的影响规律。此外，现有故障辨识特征多侧重于单点幅值或局部状态，难以刻画故障响应的空间差异，导致不同故障状态的辨识能力受限。为解决上述问题，本文提出了一种磁-热轴向分布形态特征驱动的电压互感器匝间短路故障辨识方法：基于COMSOL有限元软件构建场-路耦合与磁-热耦合仿真模型，提取漏磁和温度的轴向分布序列，构建用于表征故障响应的磁-热轴向分布形态特征；进而，采用贝叶斯优化极端梯度提升(Extreme Gradient Boosting

XGBoost)模型对单一物理量特征和磁-热融合特征进行分类验证，评价特征体系有效性。仿真结果表明：短路位置主要影响磁-热异常响应的轴向分布区域，短路匝数主要影响漏磁幅值和热点温升；磁-热融合特征输入下模型辨识效果最优，准确率达96.15%。

Abstract

Potential transformers are frequently exposed to harsh operating conditions. Under various overstresses

local inter-turn short circuit faults may occur in the winding insulation

which affects the metering performance and operation safety of the equipment. However

the existing research on the leakage flux distortion and local overheating caused by the local inter-turn short circuit fault of the potential transformer is relatively insufficient

and it is difficult to reveal the influence of the short circuit position and the number of turns on the distribution of the magnetic-thermal field. In addition

the existing fault identification features mostly focus on single point amplitude or local state

which is difficult to describe the spatial difference of fault response

resulting in limited identification ability of different fault states. In order to solve the above problems

this paper proposes a method for identifying the inter-turn short circuit fault of potential transformer driven by magnetic-thermal axial distribution characteristics: Based on COMSOL finite element software

the field-circuit coupling and magnetic-thermal coupling simulation models are constructed

and the axial distribution sequences of leakage flux and temperature are extracted to construct the magnetic-thermal axial distribution morphological characteristics used to characterize the fault response. Furthermore

the Bayesian optimized extreme gradient boosting ( XGBoost ) model is used to classify and verify the single physical quantity feature and the magnetic-thermal fusion feature to evaluate the effectiveness of the feature system. The simulation results show that the short circuit position mainly affects the axial distribution area of the magnetic-thermal anomaly response

and the number of short circuit turns mainly affects the magnetic flux leakage amplitude and the temperature rise of the hot spot. The model identification effect is the best under the magnetic-thermal fusion feature input

and the accuracy rate is 96.15 %.

关键词

Keywords

references

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