Please wait a minute...
浙江大学学报(工学版)
Journal of ZheJiang University (Engineering Science)  2019, Vol. 53 Issue (6): 1190-1197    DOI: 10.3785/j.issn.1008-973X.2019.06.019
Computer and Aut omation Technology     
Short-circuit fault diagnosis and interval location method for constant current remote supply system in cabled underwater information networks
Zheng ZHANG(),Xue-jun ZHOU*(),Xi-chen WANG,Yuan-yuan ZHOU
College of Electronic Engineering, Naval University of Engineering, Wuhan 430033, China
Download: HTML     PDF(1014KB) HTML
Export: BibTeX | EndNote (RIS)      

Abstract  

The short-circuit fault status of constant current remote supply system was diagnosed by analyzing the directional matrix of the current flow direction and the mean error value. Fault intervals were located by calculating the change of mean error values of current in trunk before and after the fault in Laplace transform domain. Isolate the short-circuit fault to maintain normal operation of the rest of the system, thus improving the reliability of cabled underwater information networks. According to the established typical ring topology constant current remote supply system circuit model, the fault location scheme was designed to simulate the short-circuit faults of the primary nodes and the trunk cable sections in the constant current remote supply system, and to analyze the change of current located at the primary nodes in the Laplace transform domain before and after the fault. Results show that the current of each primary node changes in the Laplace transform domain when the system has a short-circuit fault. The fault interval can be analyzed and located by comparing the difference in current change before and after the fault. The designed method of short-circuit fault diagnosis and interval location for constant current remote supply system has high feasibility and practicability, which is suitable for the short-circuit fault monitoring and judgement of cabled underwater information networks in the future.

Key words： cabled underwater information networks      constant current      short-circuit fault      fault diagnosis      interval location     
Received: 15 May 2018      Published: 22 May 2019
CLC:  TM 773  
Corresponding Authors: Xue-jun ZHOU     E-mail: hjgczhangz@163.com;Xuejun-Zhou@163.com
Service
E-mail this article
Add to my bookshelf
Add to citation manager
E-mail Alert
RSS
Articles by authors
Zheng ZHANG
Xue-jun ZHOU
Xi-chen WANG
Yuan-yuan ZHOU
Cite this article:

Zheng ZHANG,Xue-jun ZHOU,Xi-chen WANG,Yuan-yuan ZHOU. Short-circuit fault diagnosis and interval location method for constant current remote supply system in cabled underwater information networks. Journal of ZheJiang University (Engineering Science), 2019, 53(6): 1190-1197.

URL:

http://www.zjujournals.com/eng/10.3785/j.issn.1008-973X.2019.06.019     OR     http://www.zjujournals.com/eng/Y2019/V53/I6/1190


缆系水下信息网恒流远供系统短路故障诊断及区间定位方法

通过分析电流流向的有向矩阵变化和平均误差值，诊断恒流远供系统短路故障状态；计算故障前、后干线电流在拉普拉斯变换域内变化的平均误差值，判定短路故障区间；隔离短路故障段以维护恒流远供系统其余部分正常运作，提高缆系水下信息网络的可靠性. 根据所建立的经典环形拓扑结构恒流模型设计故障定位方案，仿真恒流远供系统中主节点和干线海缆段的短路故障，分析故障前、后各节点处电流在拉普拉斯变换域内的变化. 结果显示，当系统出现短路故障时，各节点电流在拉普拉斯变换域内发生变换，通过对比故障前、后电流变化差值可以分析出故障区间。所设计的恒流远供系统短路故障诊断及区间定位方案具有较高的可行性和实用性，适用于未来水下信息网络的短路故障监测判定.


关键词： 缆系水下信息网络,  恒流供电,  短路故障,  故障诊断,  区间定位 
Fig.1 Schematic diagram of operation and maintenance of constant current remote supply system
Fig.2 Schematic diagram of isolating short-circuit fault in constant current remote supply system
Fig.3 Model diagram of dual-end 9-node annular constant current remote supply system
Fig.4 Schematic diagram of short-circuit fault feedback of constant current remote supply system
Fig.5 Equivalent drawing of current impulse feedback through submarine cable section
$s$域电流等效值 ${I_{{\rm PN}1}}$ ${I_{{\rm PN}2}}$ ${I_{{\rm PN}3}}$ ${I_{{\rm PN}4}}$ ${I_{{\rm PN}5}}$ ${I_{{\rm PN}6}}$ ${I_{{\rm PN}7}}$ ${I_{{\rm PN}8}}$ ${I_{{\rm PN}9}}$
故障前 1.501 1.494 1.504 1.513 1.511 1.499 1.501 1.490 1.498
故障瞬间 1.577 1.579 1.582 1.586 1.428 1.434 1.438 1.441 1.442
变化值 0.076 0.085 0.078 0.073 ?0.08 ?0.065 ?0.063 ?0.049 ?0.057
Tab.1 Equivalent values of field currents at each PN short-circuit faults occurs before and immediately in PN4 and PN5 in Laplace transform domain
Fig.6 Schematic diagram of short-circuit fault current of sea optical cable between PN4 and PN5
$s$域电流等效值 ${I_{{\rm PN}1}}$ ${I_{{\rm PN}2}}$ ${I_{{\rm PN}3}}$ ${I_{{\rm PN}4}}$ ${I_{{\rm PN}5}}$ ${I_{{\rm PN}6}}$ ${I_{{\rm PN}7}}$ ${I_{{\rm PN}8}}$ ${I_{{\rm PN}9}}$
故障前 1.503 1.489 1.509 1.504 1.502 1.494 1.498 1.502 1.518
故障瞬间 3.051 1.133 1.137 1.153 1.159 1.155 1.159 1.162 1.163
变化值 1.548 ?0.356 ?0.372 ?0.351 ?0.343 ?0.339 ?0.339 ?0.340 ?0.355
Tab.2 Equivalent values of field currents at each PN short-circuit faults occurs before and immediately in PN1 and PN2 in Laplace transform domain
Fig.7 Schematic diagram of short-circuit fault current of sea optical cable between PN1 and PN2
$s$域电流等效值 ${I_{{\rm PN}1}}$ ${I_{{\rm PN}2}}$ ${I_{{\rm PN}3}}$ ${I_{{\rm PN}4}}$ ${I_{{\rm PN}5}}$ ${I_{{\rm PN}6}}$ ${I_{{\rm PN}7}}$ ${I_{{\rm PN}8}}$ ${I_{{\rm PN}9}}$
故障前 1.491 1.504 1.496 1.501 1.497 1.502 1.497 1.502 1.504
故障瞬间 2.155 2.156 0 1.297 1.303 1.309 1.313 1.316 1.317
变化值 0.664 0.652 ?1.496 ?0.204 ?0.194 ?0.193 ?0.184 ?0.186 ?0.187
Tab.3 Equivalent values of field current at each PN short-circuit fault occurs before and immediately in PN3 in Laplace transform domain
Fig.8 Schematic diagram of short-circuit fault current of PN3
[1]   “中国工程科技2035发展战略研究”海洋领域课题组 中国海洋工程科技2035发展战略研究[J]. 中国工程科学, 2017, 19 (1): 108- 117
Task Force for the Research on China’s Engineering Science and Technology Development Strategy 2035 Marine Research Group Development strategy for China’s marine engineering science and technology to 2035[J]. Engineering Sciences, 2017, 19 (1): 108- 117
[2]   上海海洋科技研究中心. 海底观测——科学与技术的结合[M]. 上海: 同济大学出版社, 2011: 123-237.
[3]   汪品先 从海底观察地球——地球系统的第三个观测平台[J]. 自然杂志, 2007, 29 (3): 125- 130
WANG Pin-xian Seafloor observatories: the third platform for earth system observation[J]. Chinese Journal of Nature, 2007, 29 (3): 125- 130
doi: 10.3969/j.issn.0253-9608.2007.03.001
[4]   吕枫, 周怀阳 缆系海底科学观测网研究进展[J]. 工程研究-跨学科视野中的工程, 2016, 8 (2): 139- 154
LV Feng, ZHOU Huai-yang Progress of scientific cabled seafloor observatory networks[J]. Journal of Engineering Studies, 2016, 8 (2): 139- 154
[5]   李春光, 王瑛剑 水下信息网络" 三网合一”分析[J]. 光通信技术, 2012, 36 (9): 16- 18
LI Chun-guang, WANG Ying-jian Analysis for " combination of three nets” of underwater information network[J]. Optical Communication Technology, 2012, 36 (9): 16- 18
doi: 10.3969/j.issn.1002-5561.2012.09.005
[6]   陈燕虎. 基于树型拓扑的缆系海底观测网供电接驳关键技术研究[D]. 杭州: 浙江大学, 2012: 23-38.
CHEN Yan-hu. Research on the key technologies of power junction for cabled ocean observatories system based on tree topology [D]. Hangzhou: Zhejiang University, 2012: 23-38.
[7]   王克林, KATE Moran 加拿大海王星: 科学、运行、管理[J]. 地球科学进展, 2013, 28 (5): 521- 528
WANG Ke-lin, KATE Moran NEPTUNE Canada: science, operation, and management[J]. Advances in Earth Science, 2013, 28 (5): 521- 528
[8]   HOWE B M, KIRKHAM H, VORPERIAN V Power system considerations for undersea observatories[J]. IEEE Journal of Oceanic Engineering, 2002, 27 (2): 267- 274
doi: 10.1109/JOE.2002.1002481
[9]   周学军, 樊诚, 李大伟, 等 缆系海底观测网恒流输电系统供电方案选择[J]. 电力系统自动化, 2015, 39 (19): 126- 131
ZHOU Xue-jun, FAN Cheng, LI Da-wei, et al Power scheme selecting method for constant current power system of cabled seafloor observatory network[J]. Automation of Electric Power Systems, 2015, 39 (19): 126- 131
doi: 10.7500/AEPS20141221005
[10]   KAWAGUCHI K, KANEDA Y, ARAKI E. The DONET: a real-time seafloor research infrastructure for the precise earthquake and tsunami monitoring [C] // OCEANS 2008. Kobe: MTS/IEEE, 2008: 1-4.
[11]   KAWAGUCHI K, ARAKI E, KANEDA Y. A design concept of seafloor observatory network for earthquakes and tsunamis [C] // Symposium on Underwater Technology and Workshop on Scientific Use of Submarine Cables and Related Technologies. Tokyo: IEEE, 2007: 176-178.
[12]   林芳, 肖先勇, 李国栋, 等 考虑电压测量误差的故障概率定位方法[J]. 电网技术, 2015, 39 (12): 3592- 3597
LIN Fang, XIAO Xian-yong, LI Guo-dong, et al Probabilistic fault localization method considering voltage measurement errors[J]. Power System Technology, 2015, 39 (12): 3592- 3597
[13]   冯迎宾, 李智刚, 王晓辉, 等 海底观测网光电复合缆开路故障识别及区间定位方法[J]. 电力系统自动化, 2015, 39 (10): 151- 156
FENG Ying-bin, LI Zhi-gang, WANG Xiao-hui, et al Open-circuit fault identification and interval locating method of optoelectric cable of seafloor observatory network[J]. Automation of Electric Power Systems, 2015, 39 (10): 151- 156
doi: 10.7500/AEPS20140305006
[14]   ZHANG Z, XU F, JIN B, et al. An active node isolating method based on discrete-voltage intervention for seafloor observation network [C] // OCEANS 2015. Washington: MTS/IEEE, 2015: 1-5.
[15]   徐兴华, 马伟明, 崔小鹏, 等 分段供电切换传感器的在线故障诊断方法[J]. 国防科技大学学报, 2016, 38 (6): 24- 36
XU Xing-hua, MA Wei-ming, CUI Xiao-peng, et al Online fault diagnosis method of segment-powered switch control sensor[J]. Journal of National University of Defense Technology, 2016, 38 (6): 24- 36
[16]   张烁. 高压直流输电系统线路保护、故障重启及故障测距方法的研究 [D]. 天津: 天津大学, 2014: 23-34.
ZHANG Shuo. Research on HVDV line protection, DC line fault recovery and fault location [D]. Tianjin: Tianjin University, 2014: 23-34.
[17]   林圣, 武骁, 何正友, 等 基于行波固有频率的电网故障定位方法[J]. 电网技术, 2013, 37 (1): 270- 275
LIN Sheng, WU Xiao, HE Zheng-you, et al A power system fault location method based on natural frequencies of traveling waves[J]. Power System Technology, 2013, 37 (1): 270- 275
[18]   杨凡. CAN网络暂态性连接故障定位方法研究[D], 杭州: 浙江大学, 2016: 35-52.
YANG Fan. Fault localization of intermittent connections for CAN networks[D]. Hangzhou: Zhejiang University, 2016: 35-52.
[19]   HARRISDW, DUENNEBIER FK Powering cabled ocean-bottom observatories[J]. IEEE Journal of Oceanic Engineering, 2002, 27 (2): 201- 211
[20]   工业和信息化部第四研究院. 海底光缆通用规范: GJB 4489—2002[S]. 北京: 中央军委装备发展部, 2002.
[21]   王希晨. 缆系水下基础信息网络平台关键技术研究[D]. 武汉: 海军工程大学, 2015: 71-74.
WANG Xi-chen. Research on the key technologies of cabled underwater basic information network platform[D]. Wuhan: Naval University of Engineering, 2015: 71-74.
[1] Le XIE,Xi-dan HENG,Yang LIU,Qi-long JIANG,Dong LIU. Transformer fault diagnosis based on linear discriminant analysis and step-by-step machine learning[J]. Journal of ZheJiang University (Engineering Science), 2020, 54(11): 2266-2272.
[2] Jing-jing LIN,Yan-xia SHEN. Stator current sensors’ fault tolerant control for permanent magnet synchronous motor drive system[J]. Journal of ZheJiang University (Engineering Science), 2019, 53(9): 1815-1825.
[3] TONG Shui-guang, ZHANG Yi-dong, XU Jian, CONG Fei-yun. Spectral band refined composite multiscale fuzzy entropy and its application in fault diagnosis of rolling bearings[J]. Journal of ZheJiang University (Engineering Science), 2018, 52(8): 1509-1516.
[4] GE Yun-long, CHEN Zi-qiang, ZHENG Chang-wen. Time-varying parameters estimation and fault diagnosis of li-ion battery using UTSTF[J]. Journal of ZheJiang University (Engineering Science), 2018, 52(6): 1223-1230.
[5] YU Jian-bo, LI Chuan-feng, LV Jing-xiang. Average combination difference morphological filter analysis on fault signals of rolling bearing[J]. Journal of ZheJiang University (Engineering Science), 2018, 52(10): 1845-1853.
[6] ZHU Wen-ying, FENG Zhi-peng. Analysis of planetary gear vibration signal based on iterated Hilbert transform[J]. Journal of ZheJiang University (Engineering Science), 2017, 51(8): 1587-1595.
[7] ZHONG Wei, PENG Liang, ZHOU Yong gang, XU Jian, CONG Fei yun. Slagging diagnosis of boiler based on wavelet packet analysis and support vector machine[J]. Journal of ZheJiang University (Engineering Science), 2016, 50(8): 1499-1506.
[8] CHEN Chen,LI Xiao run. Fault diagnosis method of circuit breaker operating mechanism based on coil current analysis[J]. Journal of ZheJiang University (Engineering Science), 2016, 50(3): 527-535.
[9] HAN Ling, LU Yan hui, AN Ying, TIAN Li yuan. Faults diagnosis and classification based on fault-tolerant  theory for continuously variable transmission[J]. Journal of ZheJiang University (Engineering Science), 2016, 50(10): 1927-1936.
[10] MI Gang-gang, ZHOU Wen-hua, SHEN Cheng-yu, GUO Xiu-qi. Design of driving module and fault diagnosis for
high-speed solenoid valve of diesel[J]. Journal of ZheJiang University (Engineering Science), 2012, 46(9): 1654-1659.
[11] YANG Xian-Yong, ZHOU Xiao-Jun, LIN Yong, ZHANG Wen-Bin, CHEN Lu. Fault diagnosis approach for rolling bearing based on V-detector algorithm[J]. Journal of ZheJiang University (Engineering Science), 2010, 44(9): 1805-1810.
[12] YANG Xian-Yong, ZHOU Xiao-Jun, ZHANG Wen-Bin, YANG Fu-Chun. Rolling bearing fault diagnosis based on local wave method
and KPCA-LSSVM[J]. Journal of ZheJiang University (Engineering Science), 2010, 44(8): 1519-1524.
[13] DU Wen-Chi, WANG Kun, JIAN Feng. Feature space dimensionreduction based process monitoring of solvent dehydration separation process[J]. Journal of ZheJiang University (Engineering Science), 2010, 44(7): 1255-1259.
[14] HU Zhi-Kun, WANG Mei-Ling, GUI Wei-Hua, YANG Chun-Hua, DING Jia-Feng. Support vector machine based classification method for
timeseries periodic waveform[J]. Journal of ZheJiang University (Engineering Science), 2010, 44(7): 1327-1332.
[15] ZHANG Gen-Yuan, ZHOU Hong, CHANG Zong-Yu. Dynamic response of deep groove ball bearing with point defects[J]. Journal of ZheJiang University (Engineering Science), 2009, 43(8): 1497-1450.