电机与控制应用2026，Vol.53Issue(4)：328-339,12.DOI:10.12177/emca.2026.147
基于多源信息融合与一维卷积神经网络的低压供电电缆故障诊断研究
Research on Low Voltage Power Supply Cable Fault Diagnosis Based on Multi-Source Information Fusion and One Dimensional Convolutional Neural Network
摘要
Abstract
[Objective]To address issues in traditional low-voltage power cable fault diagnosis,such as reliance on a single signal,insufficient feature extraction,and weak anti-interference capability,an intelligent diagnostic strategy is proposed that can achieve high robustness and high-precision identification under complex operating conditions.[Methods]An intelligent diagnostic method integrating variational mode decomposition-Hilbert transform(VMD-HT)and multi-source one-dimensional convolutional neural network(MS-1DCNN)was proposed.A time-frequency analysis framework was constructed using VMD and HT to adaptively decompose signals of different modes and quantify feature parameters.Meanwhile,the MS-1DCNN structure was designed to achieve unified modeling and diagnosis of multiple types of cable faults.[Results]The experimental results demonstrated that the proposed MS-1DCNN diagnostic model outperformed conventional methods in terms of fault feature separability,classification accuracy,and stability under complex noise conditions.Superior robustness to hyperparameter variations was also verified.[Conclusion]The proposed MS-1DCNN model significantly enhances the reliability of fault identification in low-voltage cables,making it suitable for online monitoring and early warning scenarios in actual power grids.It provides a scalable technical solution for ensuring the operational safety of low-voltage distribution systems.关键词
低压供电电缆/故障诊断/变分模态分解/希尔伯特变换/多源一维卷积神经网络Key words
low-voltage power cable/fault diagnosis/variational mode decomposition/Hilbert transform/multi-source one-dimensional convolutional neural network分类
信息技术与安全科学引用本文复制引用
李陈莹,曹京荥,谭笑,周立,张伟,王齐,张毅明,吴淑群..基于多源信息融合与一维卷积神经网络的低压供电电缆故障诊断研究[J].电机与控制应用,2026,53(4):328-339,12.基金项目
国网江苏省电力有限公司科技项目(J2025032) State Grid Jiangsu Electric Power Co.,Ltd.Science and Technology Project(J2025032) （J2025032）
