微型电脑应用2025，Vol.41Issue(2)：284-287,4.
基于CNN-SVM算法的高压输电线路故障识别研究
Research on High Voltage Transmission Line Fault Identification Based on CNN-SVM Algorithm
宋文志 1刘柯余2
作者信息
- 1. 北京国电通网络技术有限公司,北京 100192
- 2. 国网四川省电力公司物资公司,四川,成都 610000
- 折叠
摘要
Abstract
When the transmission line fails in use,the safety of the power grid is adversely affected.In order to improve the sta-bility of HV transmission lines,HV transmission line a fault diagnosis method based on convolutional neural networks-support vector machine(CNN-SVM)algorithm is designed.The SVM model is constructed to judge the phase fault grounding state,and the transmission line fault diagnosis is realized accurately.The test results show that the identification accuracy of both sin-gle-phase and three-phase ground faults is very high,but the initial identification process only achieves a very low recognition rate of both phase and phase ground faults.The method presented in this paper can obtain higher accuracy and achieve higher precision identification effect of phase-to-phase faults.The accuracy of the proposed method is 99.87％in identifying AB phase faults.关键词
输电线路/故障识别/CNN/SVM/特征提取/故障接地Key words
transmission line/fault identification/CNN/SVM/feature extraction/fault grounding分类
信息技术与安全科学引用本文复制引用
宋文志,刘柯余..基于CNN-SVM算法的高压输电线路故障识别研究[J].微型电脑应用,2025,41(2):284-287,4.
