Contour matching method of groove track based on laser sensor

doi:10.3785/j.issn.1008-973X.2021.09.001

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 words： groove 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）

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	Chuan-hui WU
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	Bo ZHOU

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.

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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

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


[1]	赵昕, 顾保南 2018年中国城市轨道交通运营线路统计和分析[J]. 城市轨道交通研究, 2019, 22 (1): 1- 7 ZHAO Xin, GU Bao-nan Statistical analysis of urban rail transit lines in 2018 China[J]. Urban Mass Transit, 2019, 22 (1): 1- 7

[2]	张俊. 槽型轨磨耗检测研究[D]. 成都: 西南交通大学, 2016. ZHANG Jun. The study of channel rail wear detection[D]. Chengdu: Southwest Jiaotong University, 2016.

[3]	ALIPPI C, CASSGRANDE E, SCOTTIE F, et al Composite real-time processing for railways track profile measurement[J]. IEEE Transactions on Instrumentation and Measurement, 2000, 49 (3): 559- 564 doi: 10.1109/19.850395

[4]	POPOV D V, PYABICHENKO P B, KRIVOSHEINA E A. Calibration of the CCD photonic measuring system for railway inspection[C]// Proceeding of SPIE-The International Society for Optical Engineering. Bellingham: SPIE, 2005: 1-9.

[5]	LIU Z, SUN J H, WANG H, et al Simple and fast rail wear measurement method based on structured light[J]. Optics and Lasers in Engineering, 2011, 49 (11): 1343- 1351 doi: 10.1016/j.optlaseng.2011.05.014

[6]	SUN J H, LIU Z, ZHAO Y T, et al Motion deviation rectifying method of dynamically measuring rail wear based on multi-line structured-light vision[J]. Optics and Laser Technology, 2013, 50 (9): 25- 32

[7]	李艳福, 刘宏立, 马子骥, 等基于动态参考的钢轨轮廓失真校准方法[J]. 铁道学报, 2018, 40 (10): 119- 127 LI Yan-fu, LIU Hong-li, MA Zi-ji, et al A distortion calibration method of rail profile based on dynamic reference[J]. Journal of the China Railway Society, 2018, 40 (10): 119- 127 doi: 10.3969/j.issn.1001-8360.2018.10.017

[8]	LI Y F, ZHONG X Y, MA Z J, et al The outlier and integrity detection of rail profile based on profile registration[J]. IEEE Transactions on Intelligent Transportation Systems, 2020, 21 (3): 1074- 1085 doi: 10.1109/TITS.2019.2901633

[9]	冯凯, 于龙, 占栋, 等钢轨轮廓全断面检测中的快速高鲁棒性匹配方法研究[J]. 铁道学报, 2019, 41 (5): 162- 167 FENG Kai, YU Long, ZHAN Dong, et al Research on fast and robust matching algorithm in inspection of full cross-section rail profile[J]. Journal of the China Railway Society, 2019, 41 (5): 162- 167 doi: 10.3969/j.issn.1001-8360.2019.05.020

[10]	陆英杰, 朱洪涛基于动态时间规整的钢轨轨廓匹配方法[J]. 振动与冲击, 2019, 38 (20): 210- 215 LU Ying-jie, ZHU Hong-tao A rail profile matching method based on dynamic time warping[J]. Journal of Vibration and Shock, 2019, 38 (20): 210- 215

[11]	YANG Q, LIN J H. Track gauge dynamic measurement based on 2d laser displacement sensor[C]// International Conference on Mechanic Automation and Control Engineering. Hohhot: IEEE, 2011: 5473-5476.

[12]	史红梅, 许明, 余祖俊基于最小二乘法曲线拟合的轨距参数测量方法[J]. 铁道学报, 2019, 41 (12): 81- 88 SHI Hong-mei, XU Ming, YU Zu-jun Track gauge measurement method based on least-square curve fitting theory[J]. Journal of the China Railway Society, 2019, 41 (12): 81- 88 doi: 10.3969/j.issn.1001-8360.2019.12.011

[13]	熊仕勇, 陈春俊, 王锋, 等基于激光摄像式传感器的轨底坡动态检测方法研究[J]. 振动与冲击, 2018, 37 (18): 251- 256 XIONG Shi-yong, CHEN Chun-jun, WANG Feng, et al Dynamic detection method for rail cants based on laser camera transducers[J]. Journal of Vibration and Shock, 2018, 37 (18): 251- 256

[14]	杨新文, 刘小山, 沈剑罡, 等现代有轨电车线路轨底坡对槽型轨磨耗的影响[J]. 同济大学学报: 自然科学版, 2019, 47 (4): 528- 534 YANG Xin-wen, LIU Xiao-shan, SHEN Jian-gang, et al Effect of rail cant on groove shaped rail wear in modern tram line[J]. Journal of Tongji University: Natural Science, 2019, 47 (4): 528- 534

[15]	王晓嘉, 高隽, 王磊激光三角法综述[J]. 仪器仪表学报, 2004, 25 (Suppl. 2): 601- 604 WANG Xiao-jia, GAO Jun, WANG Lei Survey on the Laser tri- angulation[J]. Chinese Journal of Scientific Instrument, 2004, 25 (Suppl. 2): 601- 604

[16]	TANG W B, LONG Y H, XIE Y J, et al. A channel rail gauge detection system of modern tram[C]// International Conference on Networking, Sensing and Control (ICNSC). Zhuhai: IEEE, 2018: 1-5.

[17]	杨阳, 李芾, 张茂松, 等槽型轨磨耗演变过程数值模拟[J]. 铁道科学与工程学报, 2016, 13 (8): 1607- 1612 YANG Yang, LI Fu, ZHANG Mao-song, et al Numerical simulation of groove track wear evolution[J]. Journal of Railway Science and Engineering, 2016, 13 (8): 1607- 1612 doi: 10.3969/j.issn.1672-7029.2016.08.023

[18]	汤鹏. 槽型轨磨耗焊补修复关键技术研究[D]成都. 西南交通大学, 2018. TANG Peng. Research on key technologies of welding repair of groove rail[D]. Chengdu: Southwest Jiaotong University, 2018.

[19]	张兵舰, 沈钢槽型轨与车轮接触几何关系初步研究[J]. 铁道车辆, 2006, 44 (12): 1- 3 ZHANG Jun-jian, SHEN Gang Initial research on the geometrical relation of contact between channel rail and wheels[J]. Rolling Stock, 2006, 44 (12): 1- 3 doi: 10.3969/j.issn.1002-7602.2006.12.001

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