Online Short-Circuit Fault Diagnosis in Three-Core Power Distribution Cable Based on Magnetic Pattern

被引:5
作者
Liu, Jingyi [1 ]
Lee, Chi-Kwan [1 ]
Pong, Philip W. T. [2 ]
机构
[1] Univ Hong Kong, Dept Elect & Elect Engn, Hong Kong, Peoples R China
[2] New Jersey Inst Technol, Dept Elect & Comp Engn, Newark, NJ 07102 USA
关键词
Magnetic pattern; online fault diagnosis; power distribution network; tangential magnetic field; three-core power distribution cable; INCIPIENT FAULTS; LOCATION; IDENTIFICATION;
D O I
10.1109/JSEN.2023.3300126
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
The short-circuit fault in three-core power distribution cables is the leading cause of failure in the power distribution network. It is imperative to diagnose it as soon as possible to avoid the consequent power outages. Against the common fault diagnosis methods that either necessitate the three-phase current or the disconnection of cable from the grid, this article proposes an online fault diagnosis method by measuring the tangential magnetic field around the power cable surface in a nonintrusive way. The formulated magnetic pattern is first introduced to detect and classify short-circuit faults. A normal operation results in a circular magnetic pattern, while each type of short-circuit fault uniquely changes the magnetic pattern. In general, short-circuit faults result in a remarkable change in the radius of the magnetic pattern, which can be detected within five samples based on the cumulative sum-based algorithm. The sensitivity of the proposed method on load variation, homogeneous components, and cable structure is also evaluated. Both simulation and experimental results validate the effectiveness and robustness of the proposed method.
引用
收藏
页码:21832 / 21841
页数:10
相关论文
共 30 条
[1]  
[Anonymous], 2012, IEEE Std 400-2012 (Revision of IEEE Std 400-2001), P1
[2]   Tree-related high impedance fault location using phase shift measurement of high frequency magnetic field [J].
Bahador, Nooshin ;
Namdari, Farhad ;
Matinfar, Hamid Reza .
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS, 2018, 100 :531-539
[3]   Classification of Faults in Multicore Cable via Time-Frequency Domain Reflectometry [J].
Bang, Su Sik ;
Shin, Yong-June .
IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS, 2020, 67 (05) :4163-4171
[4]   A new approach to phase selection using fault generated high frequency noise and neural networks [J].
Bo, ZQ ;
Aggarwal, RK ;
Johns, AT ;
Li, HY ;
Song, YH .
IEEE TRANSACTIONS ON POWER DELIVERY, 1997, 12 (01) :106-115
[5]  
farnell, TMR2001 TMR Linear Sensor Datasheet
[6]   A Noninvasive Technique for Fault Detection and Location [J].
Ferreira, Kurt J. ;
Emanuel, Alexander E. .
IEEE TRANSACTIONS ON POWER DELIVERY, 2010, 25 (04) :3024-3034
[7]   Frequency-domain reflectometery for on-board testing of aging aircraft wiring [J].
Furse, C ;
Chung, YC ;
Dangol, R ;
Nielsen, M ;
Mabey, G ;
Woodward, R .
IEEE TRANSACTIONS ON ELECTROMAGNETIC COMPATIBILITY, 2003, 45 (02) :306-315
[8]  
Gao ZW, 2015, IEEE T IND ELECTRON, V62, P3768, DOI [10.1109/TIE.2015.2419013, 10.1109/TIE.2015.2417501]
[9]  
Gustafsson F, 2000, Adaptive Filtering and Change Detection
[10]   Characterization of Ageing for MV Power Cables Using Low Frequency Tan δ Diagnostic Measurements [J].
Hernandez-Mejia, J. C. ;
Harley, R. ;
Hampton, N. ;
Hartlein, R. .
IEEE TRANSACTIONS ON DIELECTRICS AND ELECTRICAL INSULATION, 2009, 16 (03) :862-870