Multi-physical Field Simulation and Time-frequency Characteristic Analysis of Incipient Fault in Medium Voltage Cables

ZHAO Jingtao; WANG Yisong; QIN Hui; HUANG Xizhi; ZHANG Jun; SHI Chaoqun; XU Yang

doi:10.13296/j.1001-1609.hva.2026.06.012

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Multi-physical Field Simulation and Time-frequency Characteristic Analysis of Incipient Fault in Medium Voltage Cables

Research & Analysis | 更新时间：2026-06-10

- Multi-physical Field Simulation and Time-frequency Characteristic Analysis of Incipient Fault in Medium Voltage Cables
- High Voltage Apparatus Vol. 62, Issue 6, Pages: 97-104(2026)
- 作者机构：
  
  国电南瑞科技股份有限公司，南京 211161
  西安交通大学电力设备电气绝缘国家重点实验室，西安 710049
  西安交通大学电气工程学院，西安 710049
- 作者简介：
- 基金信息：
- DOI：10.13296/j.1001-1609.hva.2026.06.012
  CLC：
- Received：10 November 2025，
  
  Revised：2026-01-21，
  
  Published：16 June 2026
- 稿件说明：
移动端阅览
ZHAO Jingtao, WANG Yisong, QIN Hui, et al. Multi-physical Field Simulation and Time-frequency Characteristic Analysis of Incipient Fault in Medium Voltage Cables[J]. High Voltage Apparatus, 2026, 62(6): 97-104.
DOI：

ZHAO Jingtao, WANG Yisong, QIN Hui, et al. Multi-physical Field Simulation and Time-frequency Characteristic Analysis of Incipient Fault in Medium Voltage Cables[J]. High Voltage Apparatus, 2026, 62(6): 97-104. DOI： 10.13296/j.1001-1609.hva.2026.06.012.

摘要

电缆的早期故障通常伴随着间歇性电弧产生，在电流过零点附近自主熄弧，表现为故障自清除，该过程的物理变化尚不明确。由于间歇性电弧放电持续时间极短，传统继电保护设备难以识别到早期故障，需要提取合适的特征对早期故障信号进行辨识。文中基于磁流体动力学理论（magneto hydro dynamics，MHD）开展了中压电缆的多物理场仿真研究，分析了1/4周波间歇性电弧电流密度、磁场强度与温度分布的变化，并对仿真波形作短时傅里叶变换（short-time Fourier transform，STFT），得到早期故障的频域特征。结果表明，电缆早期故障时出现高频分量，在Hanning窗处理的5 kHz频率下与正常运行时差异明显，振幅差距可达85 dB。而Hamming窗的处理效果较差，需要考虑选取或结合适当的特征进行识别。

Abstract

Incipient faults in cables are often accompanied by intermittent arcing

with self-extinuishing of the arc occuring near the current zero-crossinng point

manifesting as self fault clearanc. However

the physical changes durig this process are still not well understood. Due to the very short duration of intermittent arc discharge

it is difficult for traditional relay protection equipment to identify incipient faults and appropriate features need to be extracted to identify incipient fault signals. In this paper

based on the magneto hydro dynamics theory (MHD)

the multiphysical field simulation of medium voltage cables is performed to analyze the variation of current density

magnetic field intensity and temperature distribution during a quarter cycle of intermittent arcing. Short-time Fourier transform (STFT) is performed on the simulation waveform so to obtain the frequency domain characteristics of the incipient fault. The results show that in case of incipient fault in cables there is a high frequency component

which is obviously different from the normal operation under the 5 kHz frequency treated by Hanning window

and the amplitude difference can be up to 85 dB. While

the Hamming window has a weak processing effect

so it is necessary to select or combine appropriate features for identification.

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references

任广振,王云鹤,曹俊平,等.电力电缆初期绝缘故障检测方法综述[J].重庆大学学报,2023,46(11):1-12.

REN Guangzhen, WANG Yunhe, CAO Junping, et al. Review of incipient insulation fault detection methods for power cables[J]. Journal of Chongqing University,2023,46(11):1-12.

KOJOVIC L A, WILLIAMS C W. Sub-cycle detection of incipient cable splice faults to prevent cable damage[C]//2000 Power Engineering Society Summer Meeting(Cat. No.00CH37134).USA:IEEE,2000:1175-1180.

李露露,李永培,周新月,等.10 kV交联聚乙烯电缆内部多形态间歇性电弧故障建模[J].电工技术学报,2022,37(23):6104-6115.

LI Lulu, LI Yongpei, ZHOU Xinyue, et al. Modeling of internal multiform intermittent arc fault for 10 kV XLPE cable[J]. Transactions of China Electrotechnical Society,2022,37(23):6104-6115.

ROWLAND S M , WANG Miao.Fault development in wet , low voltage, oil - impregnated paper insulated cables[J]. IEEE Transactions on Dielectrics and Electrical Insulation,2008,15(2):484-491.

HAMEL A, GAUDREAU A, COTE M.Intermittent arcing fault on underground low-voltage cables[J]. IEEE Transactions on Power Delivery,2004,19(4):1862-1868.

SAMET H, KHALEGHIAN S, TAJDINIAN M, et al. A similaritybased framework for incipient fault detection in underground power cables[J]. International Journal of Electrical Power & Energy Systems,2021(133):107309.

MAYR O.Beiträge zur theorie des statischen und des dynamischen lichtbogens[J]. Archiv Fur Elektrotechnik,1943,12(37):588-608.

贾科,李昱霖,毕天姝,等.基于早期故障判别的直流并网系统主动保护[J].电工技术学报,2025,40(5):1427-1439.

JIA Ke, LI Yulin, BI Tianshu, et al.Incipient fault identification based active protection of DC collection line[J]. Transactions of China Electrotechnical Society,2025,40(5):1427-1439.

KIZILCAY M, PNIOK T.Digital simulation of fault arcs in power systems[J]. European Transactions on Electrical Power,1991,1(1):55-60.

KARETTA F, LINDMAYER M. Simulation of the gasdynamic and electromagnetic processes in low voltage switching arcs[J]. IEEE Transactions on Components, Packaging, and Manufacturing Technology:Part A,1998,21(1):96-103.

吴祺嵘,徐婧涵,张国钢,等.基于真型试验和磁流体仿真的电缆单相接地故障电弧场路耦合模型研究[J].电力系统保护与控制,2026,54(4):25-37. WU Qirong, XU Jinghan, ZHANG Guogang, et al. Arc field-circuit coupling modelling of cable single-phase-to-ground faults based on full-scale tests and magnetohydrodynamic simulations[J]. Power System Protection and Control,2026,54(4):25-37.

李兴文,陈德桂.空气开关电弧的磁流体动力学建模及特性仿真[J].中国电机工程学报,2007,27(21):31-37.

LI Xingwen, CHEN Degui.Magnetohydrodynamics modeling and characteristics simulation of air switching arc[J]. Proceedings of the CSEE,2007,27(21):31-37.

DON RUSSELL B, BENNER C, WISCHKAEMPER J, et al. Incipient electric circuit failure detection and outage prevention using advanced electrical waveform monitoring:Field experience[J]. IEEE Industry Applications Magazine,2023,29(3):36-45.

王晓卫,魏春燕,王毅钊,等.基于护层接地线电流和分段TKEO的电缆早期故障检测方法[J].电力系统保护与控制,2025,53 (13):47-58.

WANG Xiaowei, WEI Chunyan, WANG Yizhao, et al. Early fault detection method for cables based on sheath grounding current and segmentedTKEO[J]. Power System Protection and Control,2025, 53(13):47-58.

徐子弘.基于降噪自编码器和优化卷积神经网络的地下电缆早期故障检测和识别方法[D].广州:华南理工大学,2021.

XU Zihong.Detection and identification of underground cable incipient faults based on denoising autoencoder and optimized convolutional neural network[D]. Guangzhou: South China University of Technology,2021.

斯捷,陈植,赵建,等.基于阻抗谱的电力电缆绝缘缺陷诊断函数故障定位与状态评估方法研究[J].电测与仪表,2025,62 (7):217-224.

SI Jie, CHEN Zhi, ZHAO Jian, et al.Research on fault location and state evaluation method of diagnostic function for power cable insulation defects based on the impedancespectrum[J]. Electrical Measurement & Instrumentation,2025,62(7):217-224.

周正雄,夏向阳,朱鹏,等.高压电缆早期间歇性电弧接地故障识别方法[J].中国电力,2020,53(12):167-176.

ZHOU Zhengxiong, XIA Xiangyang, ZHU Peng, et al.Identification method for incipient intermittent arc ground fault of high-voltage cables[J]. Electric Power,2020,53(12):167-176.

GHANBARI T.Kalman filter based incipient fault detection method for underground cables[J]. IET Generation Transmission & Distribution,2015,9(14):1988-1997.

FARUGHIAN A, KUMPULAINEN L, KAUHANIEMI K, et al.Intermittent earth fault passage indication in compensated distribution networks[J]. IEEE Access,2021(9):45356-45366.

KULKARNI S, ALLEN A J, CHOPRA S, et al. Waveform characteristics of underground cable failures[C]//IEEE PES General Meeting.USA:IEEE,2010:1-8.

唐辰旭,吉畅.基于GOA-kmeans的电缆早期故障诊断技术研究[J].四川水力发电,2022,41(5):92-96.

TANG Chenxu, JI Chang.Research on cable early fault diagnosis technology based on GOA-kmeans[J]. Sichuan Water Power,2022, 41(5):92-96.

瞿科,张文海,肖先勇,等.基于波形衰减因子的电缆接头绝缘早期故障状态监测[J].高电压技术,2022,48(1):318-327.

QU Ke, ZHANG Wenhai, XIAO Xianyong, et al.Condition monitoring for incipient faults of cable joint insulation based on waveform attenuation factor[J]. High Voltage Engineering,2022,48 (1):318-327.

谢卓越.基于残差网络的电缆早期故障辨识技术研究[D].南宁:广西大学,2022.

XIE Zhuoyue.Research on incipient cable failures identification technology based on residual network[D]. Nanning:Guangxi University,2022.

熊思衡,刘亚东,方健,等.配电线路早期故障辨识方法[J].高电压技术,2020,46(11):3970-3976.

XIONG Siheng, LIU Yadong, FANG Jian, et al.Detection method of incipient faults of power distribution lines[J]. High Voltage Engineering,2020,46(11):3970-3976.

JANNATI M, VAHIDI B, HOSSEINIAN S H. Incipient faults monitoring in underground medium voltage cables of distribution systems based on a two-step strategy[J]. IEEE Transactions on Power Delivery,2019,34(4):1647-1655.

ZHANG Wenhai, XIAO Xianyong, ZHOU Kai, et al. Multicycle incipient fault detection and location for medium voltage underground cable[J]. IEEE Transactions on Power Delivery,2017, 32(3):1450-1459.

KULKARNI S, SANTOSO S, SHORT T A. Incipient fault location algorithm for underground cables[J]. IEEE Transactions on Smart Grid,2014,5(3):1165-1174.

刘欣桐.基于单端信号的10 kV地下电缆早期故障识别与定位[D].镇江:江苏大学,2022.

LIU Xintong. Incipient fault indification and location of 10 kV underground cable based on singleended signal[D]. Zhenjiang:Jiangsu University,2022.

HERRERA-OROZCO A R, BRETAS A S, OROZCO-HENAO C, et al. Incipient fault location formulation:A time-domain system model and parameter estimation approach[J]. International Journal of Electrical Power & Energy Systems,2017(90):112-123.

张姝,林圣,唐进,等.基于双层阻抗模型的三相单芯电缆自恢复故障定位[J].电工技术学报,2016,31(17):1-10.

ZHANG Shu, LIN Sheng, TANG Jin, et al. Fault location of selfclearing fault in three phase single core cables based on double impedance model[J]. Transactions of China Electrotechnical Society,2016,31(17):1-10.

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