基于半动态拓扑优化算法的地铁车辆高压供电电路过流故障同步诊断方法  

Synchronous Diagnosis Method for OvercurrentFault in High Voltage Power Supply Circuit of Metro Vehicles Basedon Semi dynamic Topology Optimization Algorithm

作　　者：葛党朝 师睿 GE Dang-chao;SHI Rui(Shentie Line 2(Tianjin)Rail Transit Operation Co.,Ltd.,Tianjin 300300,China)

机构地区：[1]神铁二号线(天津)轨道交通运营有限公司,天津300300

出　　处：《计算技术与自动化》2023年第3期13-18,共6页Computing Technology and Automation

摘　　要：地铁车辆处于复杂的运行环境中,高压供电电路很容易发生过流故障,为迅速辨识过流故障类型,设计了一种基于半动态拓扑优化算法的地铁车辆高压供电电路过流故障同步诊断方法。应用半动态拓扑优化算法,构建模态坐标空间内高压供电电路的电流微分运动模型。结合粒子群算法与优化VDM分解方法,提取模型的过流故障特征。基于BP神经网络与遗传算法构建过流故障同步诊断模型,实现高压供电电路过流故障的同步诊断。案例测试结果表明,该方法对于变压器过流故障、变流器过流故障以及弓网接触不良故障的诊断都比较准确,特别是对于变压器与变流器的过流故障诊断十分准确。Metro vehicles are in a complex operating environment,and the high-voltage power supply circuit is prone to overcurrent fault.In order to quickly identify the type of overcurrent fault,a synchronous diagnosis method for overcurrent fault of the high-voltage power supply circuit of metro vehicles based on semi dynamic topology optimization algorithm is designed.The current differential motion model of high-voltage power supply circuit in modal coordinate space is constructed by using semi dynamic topology optimization algorithm.Combining particle swarm optimization algorithm and optimized VDM decomposition method,the overcurrent fault characteristics of the model are extracted.Based on BP neural network and genetic algorithm,a synchronous diagnosis model of overcurrent fault is built to realize synchronous diagnosis of overcurrent fault in high-voltage power supply circuit.The case test results show that the method is quite accurate for the diagnosis of transformer overcurrent fault,converter overcurrent fault and pantograph catenary poor contact fault,especially for the diagnosis of transformer and converter overcurrent fault.

关 键 词：半动态拓扑优化算法 粒子群算法 高压供电电路 优化VDM分解 过流故障同步诊断 

分 类 号：TP913.7[自动化与计算机技术]