电力系统保护与控制2025，Vol.53Issue(20)：23-33,11.DOI:10.19783/j.cnki.pspc.241729
基于多模态残差网络融合波形与天气信息的输电线路故障原因辨识方法
Transmission line fault cause identification method based on multimodal residual network integrating waveform and weather information
摘要
Abstract
To address the limitation of existing transient waveform image-based transmission line fault cause identification methods,namely,that the use of single-type input features prevents fine-grained fault cause classification,this paper proposes a novel fault cause identification method based on multimodal residual network(ResNet).The method integrates transient waveform features with weather characteristics.First,the characteristics of different causes of transmission line faults are analyzed statistically in terms of both transient waveform and weather conditions.Second,transient waveform images and one-hot codes for weather conditions at the time of the fault are used as inputs to an improved multimodal ResNet classifier.A channel attention mechanism is used to fuse the extracted fault transient waveform image features and weather features,enabling training and testing of the fault identification model.Finally,real fault recording data are used to perform case study verification.The results show that the proposed method achieves a fault cause identification accuracy of 94.87%.Compared with traditional fault identification methods,it requires fewer fault features,offers superior discrimination for easily confusable fault types,and provides significantly higher identification accuracy.关键词
输电线路/故障辨识/多模态/残差网络/天气特征Key words
transmission line/fault identification/multimodal/residual network(ResNet)/weather feature引用本文复制引用
林丰恺,王建,赵启,薛汉,彭寅章,南东亮..基于多模态残差网络融合波形与天气信息的输电线路故障原因辨识方法[J].电力系统保护与控制,2025,53(20):23-33,11.基金项目
This work is supported by the National Natural Science Foundation of China(No.52277079). 国家自然科学基金项目资助(52277079) （No.52277079）
重庆市留学人员回国创业创新支持计划项目资助(cx2021036) （cx2021036）
