电气技术2024，Vol.25Issue(6)：39-46,55,9.
基于信号包络与希尔伯特边际谱的高阻接地故障检测方法
High-impedance fault detection method based on signal envelope and Hilbert marginal spectrum
摘要
Abstract
The diagnosis of high-impedance fault(HIF)is a critical challenge due to the presence of faint signals that exhibit distortion and randomness.In this study,a novel diagnostic approach for HIF based on the signal envelope(SE)and Hilbert marginal spectrum(HMS)is proposed.Longer timescale zero-sequence voltage is used to extract SE and HMS,representing HIF distortion and randomness characteristics.These features are transformed into images,and ResNet18 is employed to detect the presence of HIF.An industrial prototype of the proposed approach has been implemented and validated in a 10kV test system.The experimental results indicate that the proposed approach outperforms the comparison by a significant margin regarding detection accuracy,particularly in resonant distribution system.关键词
谐振接地系统/高阻接地故障(HIF)/故障检测/深度学习/信号包络(SE)/希尔伯特边际谱(HMS)Key words
resonant grounding system/high-impedance fault(HIF)/fault detection/deep learning/signal envelope(SE)/Hilbert marginal spectrum(HMS)引用本文复制引用
李宽宏,林金树,江捷,朱少芬,肖中波..基于信号包络与希尔伯特边际谱的高阻接地故障检测方法[J].电气技术,2024,25(6):39-46,55,9.基金项目
国网福建省电力有限公司科技项目"具有增量学习功能的配电线路弧光接地故障人工智能识别方法研究"(521370230001) （521370230001）
