摘要
为保障列车运行安全性并避免减振器过度维修,文章对地铁车辆在线监测技术进行研究,针对车辆垂向减振器提出了基于振动数据的递推最小二乘法(RLS)的过程参数评估模型和车辆的"输入-输出"模型,并通过构建地铁车辆的多体动力学模型以提取模型计算的输入/输出参数,从而实现减振器参数的识别;借助FMECA分析方法研究地铁车辆悬挂部件的失效模式和部件之间的可靠性框图,分析各悬挂部件失效模式之间的关联关系。诊断结果表明,RLS算法在进行减振器在线参数辨识时具有比较好的跟踪收敛效果。
To ensure the safety of train operation and avoid excessive maintenance of shock absorbers, based on the vibration data, a process parameter evaluation model of the recursive least squares （RLS） and a input-output model were presented according to the research of the metro vehicle on-line monitoring technology. By means of computer simulation, a multi-body dynamics model of metro vehicle was constructed, and input parameters and output parameters of the model were extracted to identify the parameters of the shock absorber. By means of FMECA analysis method, the failure mode of subway suspension components and the block diagram of reliability between parts were studied, and the correlation between failure modes of suspension components was analyzed. Diagnostic results show that the RLS algorithm has better tracking convergence effect in the shock absorber online parameter identification.
作者
王雨
吕宇
赵沐华
WANG Yu;LYU Yu;ZHAO Muhua(Zhuzhou CRRC Times Software Technology Co., Ltd., Zhuzhou, Hunan 412001, China)
出处
《控制与信息技术》
2018年第3期68-73,共6页
CONTROL AND INFORMATION TECHNOLOGY
基金
国家重点研发计划(2016YFB1200401)
