Condition Monitoring and Preventive Maintenance of Ballastless Track Systems for High-speed Railways

被引:1
|
作者
Liu D. [1 ]
Huang X. [1 ]
机构
[1] China Railway Siyuan Survey and Design Group Co., Ltd., Wuhan
关键词
Back propagation(BP) neural network; Ballastless track; High-speed railway; Monitor; Preventive maintenance;
D O I
10.3969/j.issn.1004-132X.2019.03.017
中图分类号
学科分类号
摘要
The ballastless track systems of high-speed railways directly beared the high-frequency impacts and vibrations of high-speed trains, and the state changes of rail stretch deformation seriously affected trained safety. Traditional periodic maintenances were prone to overhaul or disrepair. A condition monitoring platform for ballastless track systems of high-speed railways was established by using fiber Bragg grating sensing technology, and the monitoring contents and monitoring point layout schemes were proposed. By analyzing the basic characteristics of monitoring data and combining with the track quality index, a back propagation(BP) neural network prediction model for ballastless track states was established, which was used to predict the service stats of rails. Prediction results guide the operation and maintenance departments to carry out timely and reasonable track maintenance and maintenance, so as to achieve preventive maintenance of high-speed rail systems. © 2019, China Mechanical Engineering Magazine Office. All right reserved.
引用
收藏
页码:349 / 353
页数:4
相关论文
共 7 条
  • [1] TG/GW 115-2012 Maintenance Rules for Ballastless Track Lines of High Speed Railway (Trial Implementation), (2013)
  • [2] Li R., Forecast and Application of Railway Track Irregularity State, (2018)
  • [3] Jin W., Liao Y., Zhang Z., Guided Wave Optical Sensor: Principle and Technology, (1998)
  • [4] Zhang A., Li Y., Zhang S., Et al., The Optical Fiber Bragg Grating Sensor and Its Applications, Measurement & Control Technology, 5, pp. 43-45, (2002)
  • [5] Li W., Lu X., Pang J., Et al., FBG Monitoring Technology on Urban Railway Expansion Device of Elevated Bridg, Journal of Wuhan University of Technology, 35, 9, pp. 133-137, (2013)
  • [6] Zhang D., Application Design of MATLAB Neural Network, pp. 214-218, (2009)
  • [7] Sun G., Analysis and Prediction Method for Monitoring Data of Elevated Station Track System in High-speed Railway, (2017)