粒子滤波算法在BDS高铁铁轨静态形变监测中的应用研究

熊武; 刘义

doi:10.12052/gdutxb.210123

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粒子滤波算法在BDS高铁铁轨静态形变监测中的应用研究

更新时间：2026-05-27

- 粒子滤波算法在BDS高铁铁轨静态形变监测中的应用研究
- Application of Particle Filter Algorithm in Static Deformation Monitoring of BDS High-Speed Rail
- 广东工业大学学报 2022年39卷第4期页码：66-72
- 作者机构：
  
  广东工业大学自动化学院,广东,广州,510006
- 作者简介：
  
  熊武(1997–)，男，硕士研究生，主要研究方向为形变监测算法，E-mail：xw10423@163.com
  刘义(1981–)，男，教授，博士，主要研究方向为无线通信网络、移动边缘计算，E-mail：yi.liu@gdut.edu.cn
- 基金信息：
  
  国家自然科学基金资助面上项目(61773126)
- DOI：10.12052/gdutxb.210123
  中图分类号： TP391;P288
- 网络首发：2022-07-10，
  
  纸质出版：2022
- 稿件说明：
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熊武, 刘义. 粒子滤波算法在BDS高铁铁轨静态形变监测中的应用研究[J]. 广东工业大学学报, 2022, 39(4): 66-72.

Xiong Wu, Liu Yi. Application of Particle Filter Algorithm in Static Deformation Monitoring of BDS High-Speed Rail[J]. 2022, 39(4): 66-72.
熊武, 刘义. 粒子滤波算法在BDS高铁铁轨静态形变监测中的应用研究[J]. 广东工业大学学报, 2022, 39(4): 66-72. DOI： 10.12052/gdutxb.210123.

Xiong Wu, Liu Yi. Application of Particle Filter Algorithm in Static Deformation Monitoring of BDS High-Speed Rail[J]. 2022, 39(4): 66-72. DOI： 10.12052/gdutxb.210123.

摘要

高铁因每天清晨需要6h的空窗期维修时间而无法通行，社会的发展需要减少空窗期时间来提高高铁运转效率。传统的基于北斗卫星导航系统(BeiDou Navigation Satellite System

BDS)的高铁铁轨路基的形变监测系统需要一天的观测时长对路基进行精确的监测，这远超高铁空窗期的观测时长无法对提高高铁运转效率起到作用。针对这种情况，在原形变监测解算算法上加入粒子滤波算法，尝试将观测时长缩减到高铁空窗期内；同时，在采样数据大幅度下降的情况下确保解算的监测点坐标值满足高铁路基的定位精度要求。本文利用广汕高铁的BDS形变监测系统的实测采样数据进行实验仿真，验证了粒子滤波算法加入后的有效性。实验结果表明，在粒子滤波算法加持下，观测时长缩减到15 min可确保监测点解算坐标值的

$ A

H $

img text_id='M1' class='formula-img' style='display:none;' src='gdgydxxb-39-4-66_M1.jpg'>

3个方向精度均满足高铁路基定位的±5 mm精度要求，为减少高铁空窗期时间，提升高铁运转效率提供了有效的方法和思路。

Abstract

High-speed rail needs 6 hours of repair time in the early morning every day

when it cannot be used. However

with the development of society

it is necessary to reduce the window time to improve the operation efficiency of high-speed rail. The traditional deformation monitoring system of high-speed railway track subgrade based on BDS (BeiDou Navigation Satellite System) needs one day observation time to accurately monitor the subgrade

but such observation time during the empty window period of ultra-high railway cannot play a role in improving the operation efficiency of high-speed railway. Particle filter algorithm is added to the original deformation monitoring algorithm. While trying to reduce the observation time to the high-speed railway empty window period

the particle filter algorithm is used to ensure that the coordinate values of the solved monitoring points meet the positioning accuracy requirements of the high railway base under the condition that the sampling data decreases substantially. An experimental simulation is carried out using the measured sampling data of BDS deformation monitoring system of Guangzhou-Shantou high-speed railway

and the effectiveness of particle filter algorithm is verified. The experimental results show that

with the help of particle filter algorithm

the observation time reduced to 15 min can ensure that the a

B and H coordinates of the monitoring points meet the accuracy requirement of ±5 mm for high railway base positioning

which provides an effective method and idea for reducing the time of high-speed railway gap period and improving the operation efficiency of high-speed railway.

关键词

Keywords

references

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