光学 精密工程, 2013, 21 (6): 1621, 网络出版: 2013-07-01
图像式无砟轨道表面沉降在线监测系统
Online surface settlement monitoring system of image-based ballastless track
无砟轨道 表面沉降 图像检测 激光准直 在线监测 ballastless track surface settlement image detection laser alignment online monitoring
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.
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. MIN Yong-zhi, DANG Jian-wu, ZHANG Zhen-hai. Online surface settlement monitoring system of image-based ballastless track[J]. Optics and Precision Engineering, 2013, 21(6): 1621.