重载货车车钩多元载荷解耦识别技术研究

Research on Multiple Load Decoupling Identification Technology for Heavy Haul Freight Train Coupler

车钩是重载货运列车的关键连接部件,而车钩结构特性响应是纵向拉伸、垂向点头、水平摇头等多元载荷的耦合力学问题,鉴于传统理论研究与监测手段均聚焦于纵向载荷,而对车钩的横向、垂向载荷的解耦识别理论与方法研究甚少,因此提出重载货运列车车钩多元载荷解耦识别方法。考虑车钩结构受到纵向载荷、水平摇头载荷、垂向点头载荷的耦合力学问题,建立基于车钩结构特性应变感知面的多元载荷识别理论模型;通过多元载荷识别模型表征出七种载荷解耦方式,并通过有限元数值仿真获取载荷与应变之间的关系系数,进行耦合随机加载,验证了七种多元载荷解耦识别的鲁棒性和识别相对误差。结果表明,该车钩多元载荷解耦识别方法能够解耦出车钩的三向载荷,并得出七种解耦方式中的第四种的识别精度最高,其多元载荷的识别精度在5%以内,可以满足实际工程应用需求。

The structural characteristic response of the coupler,as a key connecting component of heavy-haul freight trains,is a coupled mechanical problem of multivariate loads such as longitudinal stretching,vertical nodding,horizontal hunting.In view of traditional theoretical research and monitoring methods focusing on longitudinal loads,and little research on the decoupling identification theory and methods for lateral and vertical loads on train couplers,this paper proposed a multivariate load decoupling identification method for heavy-haul freight train couplers.Firstly,considering the coupling mechanics of longitudinal load,horizontal hunting load and vertical nodding load of the coupler structure,a multivariate load recognition theory model of the strain sensing surface based on the structural characteristics of the coupler was established.Then,seven load decoupling methods were characterized by the multivariate load identification model,with the relationship coefficients between load and strain obtained through finite element numerical simulation.The robustness and recognition relative error of the seven multivariate load decoupling recognition were verified by coupling random loading.The results show that the multiple load decoupling identification method for the coupler can decouple the three-way load of the coupler,and the recognition accuracy of the fourth way to decouple solution of the seven decoupling methods is the highest,with a recognition accuracy of less than 5%for multivariate loads,which can meet the actual engineering application needs.