High-impedance fault detection method based on signal envelope and Hilbert marginal spectrum
LI Kuanhong1, LIN Jinshu2, JIANG Jie2, ZHU Shaofen2, XIAO Zhongbo2
1. Taining County Power Supply Company, State Grid Fujian Electric Power Co., Ltd, Sanming, Fujian 365000; 2. Sanming Power Supply Company, State Grid Fujian Electric Power Co., Ltd, Sanming, Fujian 365000
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.
[1] 王晓卫, 刘伟博, 郭亮, 等. 基于不同时段内积投影的灵活接地系统高阻故障选线方法[J]. 电工技术学报, 2024, 39(1): 154-167. [2] 钟逸涵, 邓丰, 史鸿飞, 等. 基于动态电阻串联的高阻接地故障精确建模[J]. 电工技术学报, 2024, 39(7): 2046-2059. [3] 林骏捷, 林佳壕, 郭谋发. 基于多暂态特征量聚类的配电网接地故障区段定位方法[J]. 电气技术, 2023, 24(5): 16-22. [4] PRASAD C D, BISWAL M, MISHRA M, et al.Optimal threshold-based high impedance arc fault detection approach for renewable penetrated dis- tribution system[J]. IEEE Systems Journal, 2023, 17(2): 2971-2981. [5] 王宾, 崔鑫. 基于伏安特性动态轨迹的谐振接地系统弧光高阻接地故障检测方法[J]. 中国电机工程学报, 2021, 41(20): 6959-6968. [6] 李天友, 徐丙垠, 薛永端. 配电网高阻接地故障保护技术及其发展[J]. 供用电, 2018, 35(5): 2-6, 24. [7] 王康, 高伟, 杨耿杰. 基于高频分量的配电网高阻接地故障识别[J]. 电气技术, 2022, 23(2): 61-66, 87. [8] XIAO Qiming, GUO Moufa, CHEN Duanyu.High- impedance fault detection method based on one- dimensional variational prototyping-encoder for distribution networks[J]. IEEE Systems Journal, 2022, 16(1): 966-976. [9] 郭谋发, 游林旭, 洪翠, 等. 基于LCD-Hilbert谱奇异值和多级支持向量机的配电网故障识别方法[J]. 高电压技术, 2017, 43(4): 1239-1247. [10] GUO Moufa, ZENG Xiaodan, CHEN Duanyu, et al.Deep-learning-based earth fault detection using continuous wavelet transform and convolutional neural network in resonant grounding distribution systems[J]. IEEE Sensors Journal, 2018, 18(3): 1291-1300. [11] 肖启明, 郭谋发. 基于变分模态分解与图信号指标的配电网高阻接地故障识别算法[J]. 电气技术, 2021, 22(5): 50-55. [12] 刘炳南, 郭谋发, 陈永往. 基于KNN的配电网高阻接地故障识别[J]. 电气技术, 2019, 20(1): 18-23. [13] 张君琦, 杨帆, 郭谋发. 配电网高阻接地故障时频特征SVM分类识别方法[J]. 电气技术, 2018, 19(3): 37-43. [14] WEI Mingjie, LIU Weisheng, SHI Fang, et al.Distortion-controllable arc modeling for high impedance arc fault in the distribution network[J]. IEEE Transactions on Power Delivery, 2021, 36(1): 52-63. [15] YEH H G, SIM S, BRAVO R J.Wavelet and denoising techniques for real-time HIF detection in 12-kV distribution circuits[J]. IEEE Systems Journal, 2019, 13(4): 4365-4373. [16] HE Kaiming, ZHANG Xiangyu, REN Shaoqing, et al.Deep residual learning for image recognition[C]//2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Las Vegas, NV, USA, 2016. [17] GAUTAM S, BRAHMA S M.Detection of high impedance fault in power distribution systems using mathematical morphology[J]. IEEE Transactions on Power Systems, 2013, 28(2): 1226-1234. [18] LIMA E M, SANTOS JUNQUEIRA C M, BRITO N S D, et al. High impedance fault detection method based on the short-time Fourier transform[J]. IET Generation, Transmission & Distribution, 2018, 12(11): 2577-2584. [19] GAO Jie, WANG Xiaohua, WANG Xiaowei, et al.A high-impedance fault detection method for distribution systems based on empirical wavelet transform and differential faulty energy[J]. IEEE Transactions on Smart Grid, 2022, 13(2): 900-912. [20] GUO Moufa, LIU Wenli, GAO Jianhong, et al.A data-enhanced high impedance fault detection method under imbalanced sample scenarios in distribution networks[J]. IEEE Transactions on Industry Appli- cations, 2023, 59(4): 4720-4733.
2024, Vol. 25 
