基于数字孪生模型和状态监测系统的道岔预测性维修

Predictive maintenance of turnout based on digital twin model and condition monitoring system

随着智能制造和数字技术的进步,通过持续监测道岔状态以实现其预测性维修已成为可能。为根据列车和道岔间的相互作用构建道岔预测性维修技术体系,文章首先提出通过将多体仿真和有限元分析相结合,分析列车-道岔间相互作用,以确定道岔易损伤位置及相关传感器布设位置的建模方法;然后将有限元分析所得的钢轨动态柔度和接触力结果与多体仿真模拟计算结果进行比较,以验证模型的有效性;最后展望将数值模拟模型转化为数字孪生模型,以及利用3D打印技术实现基础设施智能监控的未来愿景。

With the development of intelligent manufacturing and digital technology,it is possible to achieve predictive maintenance by continuously monitoring the turnout status.In order to build a turnout predictive maintenance system based on the interaction between trains and turnouts and by the known aging laws and processes of the turnout system,this paper fi rst proposes a modeling method to determine the vulnerable position of turnout and the location of relevant sensors by combining multi-body simulation and finite element analysis to analyze the interaction between trains and turnouts;then,the rail dynamic flexibility and contact force obtained from the fi nite element model are compared with the results of multi-body simulation models to verify the effectiveness of the model.Finally,it looks forward to the future of transforming the numerical simulation model into a digital twin model,and to achieve intelligent,self-monitoring infrastructure by 3D printing technology.