Dynamic Parameter Optimization of High-Speed Pantograph Based on Swarm Intelligence and Machine Learning

doi:10.1142/S1758825123500783

CORC > 力学研究所 > 中国科学院力学研究所 > 非线性力学国家重点实验室

	Dynamic Parameter Optimization of High-Speed Pantograph Based on Swarm Intelligence and Machine Learning
	Zhou R(周睿)1,2; Xu XH(许向红)2
刊名	INTERNATIONAL JOURNAL OF APPLIED MECHANICS
	2023-09-22
页码	19
关键词	Contact force of pantograph-catenary system selective crow search algorithm surrogate model multi-parameter optimization
ISSN号	1758-8251
DOI	10.1142/S1758825123500783
通讯作者	Xu, Xianghong(xxh@lnm.imech.ac.cn)
英文摘要	Good pantograph-catenary interaction quality is a fundamental premise for ensuring stable and reliable current collection of high-speed trains, and the optimization of dynamic parameters of high-speed pantographs provides an effective approach to improve the current collection quality of the pantograph-catenary system. In this paper, with the objective of minimizing the standard deviation of the pantograph-catenary contact force, the multi-parameter joint optimization for pantograph at different filtering frequencies and running speeds was carried out by using swarm intelligence optimization algorithm and artificial neural network method. First, the selection operator in genetic algorithm (GA) was introduced into crow search algorithm (CSA), and the selective CSA was proposed, which can effectively improve the solution accuracy and convergence rate of multi-parameter optimization. Second, a radial basis function (RBF) neural network was used to construct a surrogate model of the standard deviation of contact force with respect to the running speed and pantograph dynamic parameters, and a method for optimizing the upper limit of mapping interval of the decision variables by the selective crow search algorithm (SCSA) was proposed, which effectively improves the generalization ability of the surrogate model. Finally, by combining the surrogate model and SCSA, optimization iterations for a total of 630 combined conditions such as cut-off frequency, running speed and pantograph dynamic parameters were conducted, and an optimization method for high-speed pantograph dynamic parameters with universal applicability was proposed.
分类号	二类
资助项目	National Natural Science Foundation of China[11672297]
WOS关键词	CATENARY ; DESIGN ; PERFORMANCE ; ALGORITHM
WOS研究方向	Mechanics
语种	英语
WOS记录号	WOS:001071612100001
资助机构	National Natural Science Foundation of China
其他责任者	Xu, Xianghong
内容类型	期刊论文
源URL	[http://dspace.imech.ac.cn/handle/311007/92978]
专题	力学研究所_非线性力学国家重点实验室
作者单位	1.Univ Chinese Acad Sci, Sch Engn Sci, Beijing 100049, Peoples R China 2.Chinese Acad Sci, Inst Mech, State Key Lab Nonlinear Mech, Beijing 100190, Peoples R China;
推荐引用方式 GB/T 7714	Zhou R,Xu XH. Dynamic Parameter Optimization of High-Speed Pantograph Based on Swarm Intelligence and Machine Learning[J]. INTERNATIONAL JOURNAL OF APPLIED MECHANICS,2023:19.
APA	周睿,&许向红.(2023).Dynamic Parameter Optimization of High-Speed Pantograph Based on Swarm Intelligence and Machine Learning.INTERNATIONAL JOURNAL OF APPLIED MECHANICS,19.
MLA	周睿,et al."Dynamic Parameter Optimization of High-Speed Pantograph Based on Swarm Intelligence and Machine Learning".INTERNATIONAL JOURNAL OF APPLIED MECHANICS (2023):19.