电网技术2026，Vol.50Issue(1)：中插162,373-382,中插163,12.DOI:10.13335/j.1000-3673.pst.2025.0023
融合故障波形及故障诱因信息的输电线路故障原因智能识别方法
Intelligent Identification Method for Transmission Line Fault Causes Integrating Fault Waveforms and Fault Inducing Factors
摘要
Abstract
Current research on transmission line fault identification faces several challenges,including the scarcity of real-world fault samples,insufficient extraction of fault cause information,and a lack of effective methods for integrating multi-source fault data.These issues limit the accuracy of practical fault identification.To address these problems,this paper proposes an intelligent comprehensive fault recognition framework that integrates both fault waveform data and fault cause information.First,based on existing fault mechanisms and real fault waveforms,a simulation scheme is developed to generate diverse waveform data for six common types of transmission line faults:lightning strikes,foreign object intrusion,wind deviation,icing,pollution flashover,and wildfires.Then,a fault waveform feature extraction algorithm based on improved polynomial features is proposed,along with enhancements to residual neural networks and Bayesian models for recognizing both waveform features and fault causes.Finally,a KL-divergence-based fault cause information fusion algorithm is introduced to combine the outputs from the two recognition models,forming a comprehensive fault identification solution.The proposed framework is validated using 200 sets of real fault data,demonstrating its optimal performance and the effectiveness of incorporating fault cause information.关键词
故障辨识/机理模型/多项式特征/深度学习/贝叶斯理论/KL散度Key words
fault recognition/mechanism model/polynomial features/deep learning/Bayesian theory/KL divergence分类
信息技术与安全科学引用本文复制引用
史高翔,杨佳泽,王增平,宿洪智,付旭程,王彤..融合故障波形及故障诱因信息的输电线路故障原因智能识别方法[J].电网技术,2026,50(1):中插162,373-382,中插163,12.基金项目
国家自然科学基金项目(U22B6006) （U22B6006）
国家电网公司华北分部科学技术项目(SGNC0000DKJS2400217).Project Supported by National Natural Science Foundation of China(U22B6006) （SGNC0000DKJS2400217）
Science and Technology Project of State Grid Corporation of China North China Branch(SGNC0000DKJS2400217). （SGNC0000DKJS2400217）
