首页|电气化铁路弓网系统摩擦磨损性能研究进展

电气化铁路弓网系统摩擦磨损性能研究进展

扫码查看
针对电气化铁路弓网正常和异常状态的接触副,分析受电弓滑板磨耗周期内的摩擦磨损性能差异性,特别是受电弓滑板的磨耗率和磨耗型面的差异性,包括:发生异常磨损时受电弓滑板磨损率数倍甚至数十倍的增长差异,以及局部偏磨、波浪型磨耗和贯穿性凹坑等磨耗型面差异;着重归纳不同弓网系统载流摩擦磨损试验台的特点及异同,总结磨耗检测接触式测量方法与非接触式测量方法的优劣;分析弓网系统结构及参数、列车运行参数、弓网系统载流参数及外界环境等因素的影响,归纳总结弓网载流摩擦磨损特性的演变规律.在此基础上,综合分析弓网系统磨耗机理分析模型和数据拟合模型的研究现状和进展,并给出弓网系统载流摩擦磨损性能在后续研究中所需重点关注的研究方向和发展趋势,包括:弓网摩擦副的真实服役工况在实验室条件下的等效模拟;弓网磨耗性能的在线高精度检测;复杂气候条件及多物理场耦合作用下弓网磨耗性能的仿真和优化;结合大数据和智能算法的弓网磨耗预测,以及智能运维策略和全生命周期的能力保持技术等.
Friction and Wear Performance of Pantograph-Catenary System in Electrified Railways:State of the Art
For pantograph-catenary contact pairs in electrified railways operating in normal and abnormal states,the friction and wear performance of pantograph strip differentiates in a wear cycle,highlighted by differences in wear rate and wear profile.When abnormal wear occurs,the wear rate of pantograph strip will have a multifold increase or even dozens of times increase,but the wear profile acts differently,revealing partial eccentric wear,wavy wear,and penetrating wear.The similarities and differences in current-carrying friction and wear platforms are summarized for pantograph-catenary systems,as well as the advantages and disadvantages of contact and non-contact detection methods.The influential factors and evolution law are analyzed in view of the structure and parameters,train operation parameters,current-carrying parameters and external environment of pantograph-catenary system.Following above work,the state of the art of pantograph-catenary wear models,including mechanism analysis model and data fitting model,are analyzed extensively,and the prospective direction and development trend are put forward,such as,the equivalent simulation of a pantograph-catenary friction pair in real service under laboratory conditions,online high-precision detection of pantograph-catenary wear performance,simulation and optimization of pantograph-catenary wear performance in complex climatic conditions and multi-physical field coupling,pantograph-catenary wear prediction using big data and intelligent algorithms,intelligent operation and maintenance strategies,and capability maintenance in the whole life cycle.

Pantogrpah and catenary systemfriction and wear performancedetection methodprediction model

周宁、支兴帅、张静、郑伟、罗朝基、张卫华

展开 >

西南交通大学牵引动力国家重点实验室,四川 成都 610031

西南交通大学机械工程学院,四川 成都 610031

成自铁路有限责任公司,四川成都 610000

弓网系统 摩擦磨损特性 检测方法 预测模型

国家自然科学基金项目四川省科技计划重点研发项目中国国家铁路集团有限公司科技研究开发计划项目

520723192021YFG0066P2020J025

2024

西南交通大学学报
西南交通大学

西南交通大学学报

CSTPCD北大核心
影响因子:0.973
ISSN:0258-2724
年,卷(期):2024.59(5)
  • 47