Design and Simulation of an Intelligent Current Monitoring System for Urban Rail Transit

被引:8
|
作者
Yao, Cheng [1 ]
Zhao, Qinglei [2 ]
Ma, Zelong [2 ]
Zhou, Wei [3 ]
Yao, Tong [3 ]
机构
[1] Univ Chinese Acad Sci, Beijing 100039, Peoples R China
[2] Chinese Acad Sci, Changchun Inst Opt Fine Mech & Phys, Changchun 130033, Peoples R China
[3] Chinese Acad Sci, Xian Inst Opt & Precis Mech, Xian 710119, Peoples R China
基金
中国国家自然科学基金;
关键词
Urban rail transit (URT); backpropagation neural network (BPNN); stray current; current monitoring system; STRAY CURRENT; POWER; OPTIMIZATION;
D O I
10.1109/ACCESS.2020.2975009
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Many urban rail transit (URT) systems adopt the DC traction power supply system. Because of the impedance and incomplete ground insulation of the running track, it is inevitable for a part of the traction current to flow into the ground from the track, creating the stray current. This type of current causes great safety hazards to the metal structures in and near the URT system. Considering the power supply mode of the URT, this paper explores the different resistances in each power supply section under unilateral power supply and bilateral power supply. Then, the defects of the current discharge method were identified in the context of stray current protection. To solve these defects, the backpropagation neural network (BPNN) was adopted to build a discharge flow prediction model. On this basis, an intelligent current monitoring system was established for the URT. Finally, the authors simulated the impact of each factor on stray current, and verified the reliability and stability of the proposed monitoring system. Compared with predicted values and the actual values, the prediction agrees with the actual data very well.
引用
收藏
页码:35973 / 35978
页数:6
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