基于聚类及霍夫变换的轮对廓形提取算法研究

王洪峥; 从光涛; 邢宗义; 张永

基于聚类及霍夫变换的轮对廓形提取算法研究

1. 广州地铁集团有限公司运营事业总部, 广州 510335;
2. 南京理工大学自动化学院, 南京 210094

基金项目:

国家重点研发计划课题(2017YFB1201201)

详细信息

作者简介:
王洪峥,工程师;从光涛,研究员。

中图分类号: U270.331.1;TP39
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出版历程
- 收稿日期: 2020-01-02

Research on algorithm of wheelset profile extraction based on clustering and Huff transform

1. Operation Headquarters, Guangzhou Metro Group Co. Ltd., Guangzhou 510335, China;
2. School of Auotomation, Nanjing University of Science&Technology, Nanjing 210094, China

摘要

摘要: 针对轮对尺寸在线检测中廓形计算复杂的问题,提出一种新的轮对廓形提取算法。总结在线检测系统中的6种典型轮对廓形,采用DBSCAN算法对廓形数据进行聚类,并采用改进霍夫变换确定廓形有效区域;采用曲率熵与最小二乘法进行曲线拟合,获取轮缘基准点;通过坐标旋转与平移等操作实现完整的轮对廓形提取,为轮对尺寸计算提供支持。通过现场试验验证算法可行性,并与人工检测结果进行对比,结果表明:在线检测系统精度优于人工检测,验证该算法能够有效地实现轮对廓形提取。
- 轮对廓形 /
- 霍夫变换 /
- 密度聚类
Abstract: Aiming at the problem that it is complex to determine the wheelset profile in the online wheelset profiles detection system, a novle algorithm on wheelset profile extraction is proposed. Firstly, six types of typical wheelset profiles are analyzed. Then, the DBSCAN method is used to culster the profile data and an improved Huff transform is employed to determine the effective area of the profile. Secondly, a curve fit is performed to obtain the reference point of wheelset rim based on the curvature entropy and the least square methods. Thirdly, the complete wheel profile can be acquired after the operations of coordinate rotation and translation. Finally, the feasibility of the proposed algorithm is verified through field experiments. The results indicate that the precision of wheel profiles acquired from the online detection system is higher than that of the geometrical profiles measured manually and the proposed algorithm can satisfy the requirement of profile calculation of the online detection system.
- wheelset profile /
- Huff transform /
- density clustering

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参考文献(13)

[1]	W liu, Henrik Lund, Brian VadMathiesen. Modelling the transport system in China and evaluating the current strategies towards the sustainable transport development[J]. Energy Policy, 2013(58):347-357.
[2]	杨恒. 广州地铁14号线一期快慢车及Y型交路运行模式研究[J]. 现代城市轨道交通, 2019(1):50-54.
[3]	Bin Liu, Tingzhang Liu, Fanqin Meng.Research on Morlet Wavelet Based Lamb Wave Spatial Sampling Signal Optimization Method[J].Journal of Shanghai Jiaotong University(Science), 2018, 23(S1):62-69.
[4]	王国顺,唐立波. 八心圆弧拟合椭圆误差的理论解析及最优解[J]. 图学学报, 2014, 35(5):697-703.
[5]	王长庚,邢宗义,黄文. 一种新的地铁车辆轮对尺寸在线检测系统[J]. 铁路计算机应用, 2016, 25(5):62-65.
[6]	An Zhang,Fei Gao,M i Yang,Wenhao Bi. A new rule reduction and training method for extended belief rule base based on DBSCAN algorithm[J]. International Journal of Approximate Reasoning, 2020(119):20-39.
[7]	Martin. Ester, Hans-Peter. Kriegel, Jorg. Sander, and Xiaowei. Xu. A density-based algorithm for discovering clusters in large spatial databases with noise[A]. Proc. of the Second International Conference on Knowledge Discovery and Data MiningAugust[C].AAAI Press, 1996:226-231.
[8]	Silviu Octavian Medianu, Gimi Aurelian Rimbu,Daniel Lipcinski, et al. System for diagnosis of rolling profiles of the railway vehicles[J]. Mechanical Systems & Signal Processing, 2014, 48(1-2):153-161.
[9]	Naumann H J. Wheelset sensing system:U.S. Patent 5,936,737[P]. 1999-8-10.
[10]	汪小东,梁洪涛. 基于局部区块加权曲率熵的多尺度网格显著性[J]. 系统仿真学报, 2017, 29(9):1976-1983.
[11]	Bryce E. Harrop,Jian Lu,L. Ruby Leung. Sub-cloud moist entropy curvature as a predictor for changes in the seasonal cycle of tropical precipitation[J]. Climate Dynamics,2019(53):3463-3479.
[12]	Ayse Gul Kaplan,Yusuf Alper Kaplan. Developing of the new models in solar radiation estimation with curve fitting based on moving least-squares approximation[J]. Renewable Energy,2020(146):2462-2471.
[13]	蹇制京. 基于线结构光的轮对踏面几何参数测量技术的研究[D]. 北京:北京交通大学, 2017.