摘要
斜楔是货车转向架重要的减振元件,基于力学分析推导斜楔参数与斜楔垂向、纵向、横向及抗菱等效作用的解析关系式,根据关系式建立便于优化斜楔参数的斜楔等效模型,在考虑部件柔性的C 70E货车刚柔耦合模型中建立斜楔各向等效力元模拟斜楔作用;该斜楔处理方法下货车模型的振动模态特征和临界速度均与实际接近。据此方法,计算266组不同斜楔参数下车体垂向及纵向加速度响应;并利用遗传算法优化的BP神经网络,建立斜楔参数与车体加速度的关系模型。以此为基础,运用遗传算法寻找使车体加速度最小的斜楔参数。通过建立的货车模型,验证与原始参数相比,优化参数下车身垂向和纵向加速度均有所下降,提升了转向架的减振性能;货车的脱轨系数与轮重减载率也有所下降,提升了货车的运行性能,表明该优化方法对斜楔理论设计有一定的指导作用。
The wedge is an important vibration damping element of freight car bogies.According to mechanical analysis,the analytical relationship between the wedge parameters and the wedge equivalent effects in the vertical,longitudinal,transverse and anti-wrap directions was derived,based on which,the wedge equivalent model was developed to simplify the optimization of the wedge parameters.The wedge vertical,longitudinal,transverse and anti-warp equivalent parameter force elements were established to simulate the wedge effects in the C 70E freight car rigid-flexible coupling model considering the flexibility of the vehicle components.Based on this wedge handling method,the vibration modal characteristics and critical velocities of the freight car model were close to the reality.According to this method,the vertical and longitudinal acceleration responses of the vehicle body were calculated for 266 sets of different wedge parameters.The BP neural network optimized by genetic algorithm was used to establish the relationship model between the wedge parameters and the vehicle body acceleration.Based on this,the genetic algorithm was used to find the wedge parameter that minimized the vehicle body acceleration.The established freight car model shows that compared with the original parameters,the body vertical and longitudinal accelerations are reduced under the optimized parameters,improving the vibration damping performance of the bogie.The derailment coefficient and wheel weight reduction rate of the freight cars are also reduced,improving the running performance of the freight cars.It shows that the optimization method is an improvement to the wedge theoretical design.
作者
刘嘉兴
吕大立
吕可维
张琪昌
李玉龙
LIU Jiaxing;LYU Dali;LYU Kewei;ZHANG Qichang;LI Yulong(School of Mechanical Engineering,Tianjin University,Tianjin 300072,China;Tianjin Key Laboratory of Nonlinear Dynamics and Control,Tianjin 300072,China;Tianjin Internal Combustion Engine Research Institute,Tianjin University,Tianjin 300072,China;Dalian R&D Center of CRRC Qiqihar Vehicle Co.,Ltd.,Dalian 116042,China)
出处
《铁道学报》
EI
CAS
CSCD
北大核心
2023年第10期52-59,共8页
Journal of the China Railway Society
基金
中车齐齐哈尔车辆有限公司科研项目(T20190035)。
关键词
转向架斜楔
BP神经网络
遗传算法
刚柔耦合
参数优化
bogie wedge
BP neural network
genetic algorithms
rigid-flexible coupling
parameter optimization
