基于数据驱动的 CRH 高速列车悬挂系统早期故障检测
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作者单位:

1.江苏科技大学;2.东北大学流程工业综合自动化国家重点实验室;3.Ss Cyril and Methodius University

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中图分类号:

TP273

基金项目:

国家自然科学基金项目(61803185);江苏省自然科学基金(BK20201451);中国-北马其顿科技合作委员会第6届例会人员交流项目6-3.


Data--driven design based incipient fault detection for CRH suspension system
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Jiangsu University of Science and Technology

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    摘要:

    作为CRH(China Railway High-speed)高速列车的重要组成部分, 悬挂系统的可靠性对列车的安全运行和乘坐舒适性具有重要意义. 本文利用悬挂系统传感器数据, 提出了一种基于数据驱动的早期故障检测方法. 首先, 根据系统动态搭建列车悬挂系统Simpack模型, 其中作动器的主动控制力作为系统输入, 轨道不平顺由不平顺功率谱模拟产生激励信号, 并作为系统的扰动信号. 然后, 在悬挂系统离散模型的基础上, 通过传感器的输出构建数据模型, 并构造输入输出数据矩阵. 最后, 通过数据矩阵构造残差量,并依照离线和在线的故障检测方案,实现对故障的指示. 仿真结果表明, 所提出的故障检测方案对悬挂系统执行器和传感器的早期故障具有较高的灵敏度.

    Abstract:

    As an important part of CRH(China Railway High-speed)trains, the reliability of the high-speed train suspension system is of critical importance to the safety of the entire trains. A data-driven based incipient fault detection scheme is proposed in this paper based on the sensor data of suspension system. Firstly, a suspension system model is established by using Simpack, where the active force of actuator is acted as system input, and the track irregularity is regarded as system disturbance. Secondly, based on the discrete model of suspension system, the data model and input/output data matrices are constructed by using the sensor measurements. Finally, the off-line and on-line detection scheme are proposed based on the residual constructed by data matrices. The simulation results show that the proposed scheme has high sensitivity on incipient actuator and sensor faults of high-speed train suspension systems.

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历史
  • 收稿日期:2020-11-11
  • 最后修改日期:2021-01-19
  • 录用日期:2021-02-10
  • 在线发布日期: 2021-03-03
  • 出版日期: