Online Surface Settlement Monitoring System of Image-based Ballastless Track

MIN Yong-zhi; DANG Jian-wu; ZHANG Zhen-hai

doi:10.3788/OPE.20132106.1621

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Online Surface Settlement Monitoring System of Image-based Ballastless Track

更新时间：2020-08-12

- Online Surface Settlement Monitoring System of Image-based Ballastless Track
- Optics and Precision Engineering Vol. 21, Issue 6, Pages: 1621-1627(2013)
- 作者机构：
  
  兰州交通大学自动化与电气工程学院,甘肃兰州,730070
- 作者简介：
- 基金信息：
- DOI：10.3788/OPE.20132106.1621
  CLC： U238;TP391
- Received：09 November 2012，
  
  Revised：26 February 2013，
  
  Published Online：20 June 2013，
  
  Published：15 June 2013
- 稿件说明：
移动端阅览
闵永智党建武张振海. 图像式无砟轨道表面沉降在线监测系统[J]. 光学精密工程, 2013,21(6): 1621-1627

MIN Yong-zhi DANG Jian-wu ZHANG Zhen-hai. Online Surface Settlement Monitoring System of Image-based Ballastless Track[J]. Editorial Office of Optics and Precision Engineering, 2013,21(6): 1621-1627
闵永智党建武张振海. 图像式无砟轨道表面沉降在线监测系统[J]. 光学精密工程, 2013,21(6): 1621-1627 DOI： 10.3788/OPE.20132106.1621.

MIN Yong-zhi DANG Jian-wu ZHANG Zhen-hai. Online Surface Settlement Monitoring System of Image-based Ballastless Track[J]. Editorial Office of Optics and Precision Engineering, 2013,21(6): 1621-1627 DOI： 10.3788/OPE.20132106.1621.

摘要

将激光准直及图像检测技术应用于无砟轨道表面沉降监测之中，建立了图像式表面沉降在线监测系统。首先，介绍了图像式沉降监测方法的工作原理，给出了表面沉降在线监测系统的构成及工作方式。分析了沉降监测靶面激光光斑图像特征，并采用背景差分法来提高监测系统的环境适应度。然后，采用变结构元多尺度广义形态滤波法对光斑图像进行了预处理。最后，依据采集图像灰度呈高斯分布的特性，提出了基于重心的灰度分布曲线拟合法来精确定位光斑中心。实验结果表明：沉降实验室测试的合成不确定度最大为0.198 mm；现场测试的10个月累积最大误差小于1 mm。这些数据显示提出的系统可满足无砟轨道表面沉降在线监测对稳定性、精度和抗干扰能力的要求。

Abstract

On the basis of laser alignment and image detection technologies

an image based online surface settlement monitoring system was established to achieve the online surface settlement monitoring of ballastless track. Firstly

the operational principle of the image based settlement monitoring method was introduced and the components and working model of the online surface settlement monitoring system were described. Then

the image features of laser spot on the target surface for settlement monitoring were analyzed and the background difference method was used to improve the environmental adaptability of the monitoring system. Furthermore

the images of laser spot were preprocessed by the algorithm based on the multi-scale and generalized morphological filter with variant structuring elements. Finally

the center position of laser spot was accurately determined by a gray distribution curve fitting algorithm based on the center of gravity. The experimental results show that the combined uncertainty tested in a settlement laboratory is up to 0.198 mm and the maximum cumulate error under the field test for 10 months is less than 1 mm. The system has met the requirements of online surface settlement monitoring of ballastless track for high stabilization

reliability

precision

and capacity of resisting disturbance.

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references

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