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基于多参量数据融合的干式空心串联电抗器匝间短路故障检测方法

王寅 王媛媛 曹成军 张立志 尹有鹏 籍宏震 窦笛

电力建设2025,Vol.46Issue(4):16-28,13.
电力建设2025,Vol.46Issue(4):16-28,13.DOI:10.12204/j.issn.1000-7229.2025.04.002

基于多参量数据融合的干式空心串联电抗器匝间短路故障检测方法

Dry-Type Air-Core Series Reactor Turn-to-Turn Short Circuit Fault Detection Method Based on Multi-Parameter Data Fusion

王寅 1王媛媛 1曹成军 1张立志 2尹有鹏 1籍宏震 1窦笛1

作者信息

  • 1. 电网防灾减灾全国重点实验室(长沙理工大学),长沙市 410114
  • 2. 国网湖南省电力有限公司超高压变电公司,长沙市 410004
  • 折叠

摘要

Abstract

[Objective]To address the problems of weak turn-to-turn short-circuit faults in dry-type air-core series reactors,which are difficult to recognize,and the lack of an early warning mechanism in traditional methods,this study proposes a multi-dimensional feature and intelligent algorithm fusion of an early fault diagnosis method.This method can overcome the lack of sensitivity of a single fault feature as it is easily interfered with by the noise of the fault leakage judgment.[Methods]First,the unbalance degree,power factor,zero sequence voltage,and characteristic impedance of the shunt capacitor bank are extracted as fault feature quantities,and their respective evolution laws after the fault are analyzed.Second,principal component analysis(PCA)is used to reduce the dimension and denoise the original data to eliminate interfering information.Subsequently,the denoised features with high saturation are input into the k-nearest neighbors(KNN)algorithm to construct a fault identification and classification model.Based on Maxwell,a field-circuit coupling model is established to generate single-turn,slight,and multi-turn short-circuit datasets;noise-free and 5%noise conditions are considered to verify the robustness of the algorithm.[Results]Simulation results show that the proposed method can achieve 100%recognition accuracy for minor turn-to-turn short circuits under both no noise and 5%noise,and manually adjusting the action threshold is not required.[Conclusions]This study realized high-precision early identification of weak faults through the three-stage architecture of"feature extraction-data noise reduction-intelligent classification."The innovations include four-dimensional feature synergy to improve fault sensitivity,a PCA-KNN joint anti-noise mechanism;and an adaptive non-threshold discrimination system.The results provide a new idea for power-equipment condition monitoring,and the generalization ability of the model can be optimized by incorporating field data.

关键词

干式空心串联电抗器/匝间短路/Maxwell/主成分分析/K近邻算法

Key words

dry-type air-core series reactor/turn-to-turn short-circuit/Maxwell/principal component analysis/K-nearest neighbor algorithm

分类

动力与电气工程

引用本文复制引用

王寅,王媛媛,曹成军,张立志,尹有鹏,籍宏震,窦笛..基于多参量数据融合的干式空心串联电抗器匝间短路故障检测方法[J].电力建设,2025,46(4):16-28,13.

基金项目

国家自然科学基金项目(52177069) (52177069)

国家电网科技项目(5216A321N018) This work is supported by the National Natural Science Foundation of China(No.52177069) (5216A321N018)

State Grid Science and Technology Program(No.5216A321N018). (No.5216A321N018)

电力建设

OA北大核心

1000-7229

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