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Journal of ZheJiang University (Engineering Science)  2021, Vol. 55 Issue (9): 1607-1614    DOI: 10.3785/j.issn.1008-973X.2021.09.001
    
Contour matching method of groove track based on laser sensor
Chuan-hui WU1(),Jia LIAO1,Shi-yong XIONG1,Ying-jie NIU1,Bo ZHOU2
1. School of Mechanical Engineering, Southwest Jiaotong University, Chengdu 610031, China
2. CRRC Changchun Railway Vehicles Limited Company, Changchun 130062, China
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Abstract  

Aiming at the difficulty of matching the special track structure and installation mode of the tram, a contour matching algorithm for embedded trough track was presented, in order to grasp the track status of tram lines in real time, and guide the line operation and maintenance more effectively. By analyzing the wear law and structural characteristics of the track, the matching reference area of the slotted rail was defined, and a automatic segmentation method of the region was presented. In order to solve the problem of the matching region locating, a two-step iterative closest point (ICP) matching algorithm was designed, which realized the exact matching of contour. The Kalman filter was used to predict the rotation and translation parameters to solve the problem of abnormal matching in special cases. The reliability of the algorithm was verified by actual line experiments. Experimental results show that the algorithm is fast, accurate and robust, and it can effectively overcome the matching difficulties caused by the special structure and embedded installation of groove rail.



Key wordsgroove rail profile      dynamic matching      matched reference region      iterative closest point (ICP)      Kalman filter     
Received: 23 July 2020      Published: 20 October 2021
CLC:  U 213.2  
Fund:  国家重点研发计划资助项目(2018YFB1201605);四川省科技计划资助项目(2019JDRC0024)
Cite this article:

Chuan-hui WU,Jia LIAO,Shi-yong XIONG,Ying-jie NIU,Bo ZHOU. Contour matching method of groove track based on laser sensor. Journal of ZheJiang University (Engineering Science), 2021, 55(9): 1607-1614.

URL:

https://www.zjujournals.com/eng/10.3785/j.issn.1008-973X.2021.09.001     OR     https://www.zjujournals.com/eng/Y2021/V55/I9/1607


基于激光传感器的槽型轨轮廓匹配方法

为了实时掌握有轨电车线路的轨道状态,以期更有效地指导线路运营维护,针对有轨电车特殊的轨道结构和安装方式带来的轨道轮廓匹配困难问题,提出适用于槽型轨的轮廓匹配算法. 通过分析轨道的磨损规律及结构特征,定义槽型轨的匹配基准区域,给出区域的自动分割方法. 为了解决匹配区域定位困难的问题,设计两段式最近点迭代(ICP)匹配算法,实现轮廓的精确匹配;通过卡尔曼滤波器对匹配得到的旋转平移参数进行连续预测,解决在特殊情况下的异常匹配问题;通过实际线路实验,验证算法的可靠性. 实验结果表明:所提匹配算法具有快速、高精度和高鲁棒性的特点,能有效克服槽型轨的特殊结构和嵌入式安装方式带来的匹配困难问题.


关键词: 槽型轨断面轮廓,  动态匹配,  匹配基准区域,  最近点迭代(ICP),  卡尔曼滤波器 
Fig.1 Schematic diagram of internal structure for laser displacement sensor
Fig.2 Schematic diagram of track profile detection method
Fig.3 Track geometry parameter detection system structure diagram
Fig.4 Raw profiled point cloud data
Fig.5 Relative positions of sensor coordinate system and orbital reference coordinate system
Fig.6 Structure of groove rail and installation of embedded groove rail
Fig.7 Actual measured point cloud data and its segmentation
Fig.8 Rough matching result and segmentation of reference area
Fig.9 Comparison of CE slope curves for normal profile and sundry profile
Fig.10 Wear profile data and its rough matching results
Fig.11 Segmentation results of reference region
Fig.12 Schematic diagram of approximate curvature parameters
Fig.13 Result of final match
Fig.14 Installation position of track geometry parameter detection system
Fig.15 Dynamic test results of gauge deviation value
$K$/m ${d_{\rm{m}}}$/mm ${d_{\rm{d}}}$/mm $\varepsilon $/mm
K23+225 0.7 0.603 7 ?0.096 4
K23+250 0.3 0.329 6 0.029 6
K23+275 ?0.1 ?0.156 4 ?0.056 4
K23+300 0.5 0.395 5 ?0.104 5
K23+325 ?0.2 ?0.160 3 0.039 7
K23+350 0.3 0.465 5 0.165 5
K23+375 ?0.1 ?0.161 4 ?0.061 4
K23+400 ?0.3 ?0.335 5 ?0.035 5
K23+425 0.1 0.161 3 0.061 3
K23+450 0.2 0.302 2 0.102 2
Tab.1 Comparison of dynamic test results and manual test results
Fig.16 Kalman filtering effect of wheel-rail contact end points
Fig.17 Correction effect of Kalman filter in abnormal matching
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