基于局部平均的钢轨轮廓点云精简方法  

The rail profile point cloud simplification method based on local averaging

作　　者：马伯瑞 杨明来 曹振丰 Ma Borui;Yang Minglai;Cao Zhenfeng(Faculty of Railway Transportation,Shanghai Institute of Technology,Shanghai 201418,China;School of Information Technology,Jilin Agricultural University,Changchun 130118,China)

机构地区：[1]上海应用技术大学轨道交通学院,上海201418 [2]吉林农业大学信息技术学院,长春130118

出　　处：《电子测量与仪器学报》2025年第2期205-212,共8页Journal of Electronic Measurement and Instrumentation

摘　　要：针对以结构光技术为主的钢轨磨耗测量中,因铁路运行环境干扰、钢轨表面的高光区、设备问题等因素造成的获取到的钢轨实际点云数据中包含了大量噪声点,严重影响后续钢轨磨耗计算的精度和效率问题,因此,本研究提出了一种基于局部平均的点云简化方法。该方法通过遍历点云中的每个点,利用一个指定半径的包围圆来计算圆内所有点的平均位置,从而生成一个简化后的点云。实验结果表明,点云简化方法在降噪与钢轨轮廓细节保留方面显著优于传统的统计滤波和半径滤波算法,平均降噪率达0.8320,较统计滤波提高约4.3倍,较半径滤波提高15倍。同时,在钢轨磨损计算实验中,平均误差仅为0.02501 mm,相较于统计滤波降低约95.7%,较半径滤波降低85.1%。在处理效率上,方法的平均耗时仅为0.0065 ms,明显优于其他方法。此方法能够有效地减少点云数据量,最大程度保留钢轨轮廓特征,能够满足钢轨磨耗的测量需求。This paper proposes a point cloud simplification method based on local averaging to address the problem of a large number of noise points in the actual point cloud data obtained from rail wear measurement using structured light technology,which are caused by factors such as railway operation environment interference,high gloss areas on the rail surface,and equipment problems,and seriously affect the accuracy and efficiency of subsequent rail wear calculations,therefore,a point cloud simplification method based on local averaging is proposed.The method generates a simplified point cloud by traversing each point in the point cloud and calculating the average position of all points within the circle using an enclosing circle of specified radius.The experimental results show that the proposed method is significantly superior to traditional statistical filtering and radius filtering algorithms in terms of noise reduction and preservation of rail profile details.The average noise reduction rate reaches 0.8320,which is about 4.3 times higher than statistical filtering and 15 times higher than radius filtering.Meanwhile,the average error of wear calculation is only 0.02501 mm,which is about 95.7%lower than statistical filtering and 85.1%lower than radius filtering.In terms of processing efficiency,the average time consumption of this method is only 0.0065 ms,which is significantly better than other methods.This method can effectively reduce the amount of point cloud data,preserve the rail profile features to the maximum extent,and meet the measurement needs of rail wear.

关 键 词：钢轨磨耗测量 局部平均 点云去噪 点云精简 

分 类 号：TN249[电子电信—物理电子学] TP391.41[自动化与计算机技术—计算机应用技术]