为保障车辆安全运行，需要提高车辆实际运行中车钩防跳机构的运动可靠性来避免发生车钩分离故障。以车钩锁铁达到开锁位为评价指标，运用多体动力学（Multi Body Dynamic, MBD）仿真技术与支持向量机（Support Vector Machine, SVM）智能监督学习分类相结合的方法，对某型车钩的运动可靠性区间进行预测研究。在RecurDyn多体动力学软件环境中构建车辆实际运行时的车钩装置仿真模型，通过仿真实验模拟车辆运行时车钩内锁铁承受纵向和垂向冲击时的位移响应，反求车钩分离时的纵向、垂向以及二者耦合的临界加速度。仿真结果表明了垂向加速度是车钩分离的敏感因素。通过SVM机器学习方法求解出车钩达到分离条件的加速度界线，为车钩装置设计与运用维护提供了约束条件。研究成果为预测铁路车辆车钩装置等复杂机构的运动可靠性提供了一种新方法。
Abstract
In order to ensure the safe operation of a vehicle, it is necessary to improve the motion reliability of the coupler anti-jump mechanism in the actual operation of the vehicle to avoid the separation failure of the coupler.The unlocked position of the coupler knuckle lock was taken as an indicator and a prediction study was performed on the motion reliability of a certain type of coupler based on the technique of multi-body dynamics (MBD) simulation combined with the support vector machine (SVM) with intelligent supervised learning classification.The coupler model was built in RecurDyn, software environment, and the displacement responses of the coupler knuckle lock under longitudinal and vertical impact in the vehicle running state were simulated.The reverse solution gives the longitudinal acceleration, vertical acceleration and coupled acceleration of the two directions in the coupler seperation process.The SVM method was used to obtain the acceleration boundary between the coupler unlock zone and safety zone.The simulation results show that vertical acceleration is the sensitive factor for coupler separation.The SVM machine learning method is used to solve the acceleration boundary when the coupler reaches the separation condition, which provides constraints for the design and operation of the coupler device.The research results provide a new method for predicting the motion reliability of complex mechanisms such as the railway vehicle coupler device.
关键词
车钩 /
分离故障 /
运动可靠性 /
多体动力学 /
支持向量机
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Key words
coupler /
separation failure /
motion reliability /
multi-body dynamics /
SVM
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