结合决策树分类和区域生长的轨道扣件检测方法

Track fastener detection method based on decision tree classification and region growth

轨道扣件数据量大、体积小,轨道扣件病害的检测工作繁重、效率低下,因此亟须改进轨道扣件检测技术。线结构激光技术发展迅速,其具有高分辨率、高精度、高响应等特点。本文采用线结构激光测量技术快速获取轨道扣件精细三维点云,利用决策树分类和区域生长算法对精细扣件三维点云进行分析,实现扣件病害快速检测和扣件几何参数计算。利用该技术对广州18号线轨道交通扣件进行检测,由检测结果可知,该方法检测效率高、检测结果精准。

Due to the large amount of data and small size of rail fasteners,the detection of rail fastener diseases is heavy and inefficient.Therefore,a fast rail fastener detection technology is urgently needed.The rapid development of line structure laser technology has the characteristics of high resolution,high precision and high response.In this paper,the line structure laser measurement technology is used to quickly obtain the fine 3D point cloud of rail fasteners,and the decision tree classification and regional growing algorithm are used to analyze the 3D point cloud of the fine fasteners,so as to realize the fast detection of fastener diseases and the calculation of fastener geometric parameters.Using this technology to detect the rail transit fasteners of Guangzhou Line 18,the detection results show that the method has high detection efficiency and accurate detection results.