Regular inspection of rail wear is very important to ensure the safety of railway transportation. Rail profile registration is a key step in rail wear measurement. However, the accuracy of rail profile registration cannot be guaranteed due to soil and corrosion on the rail waist. To solve this problem, a new rail profile registration method based on probability iterative closest point algorithm with normal vector direction (N-PICP) is proposed in this paper. First, rail profile data is obtained using a line structured light measurement system. Then, the rail profile data is divided into rail head and rail waist according to the distance between adjacent points. The data of the rail waist is used to register with the corresponding part of the standard profile data by N-PICP. Finally, the rail head data is also converted according to the calculated transformation matrix. The experimental results demonstrate that the proposed method can realize the registration of the rail profile with a high precision and strong robustness.

定期检查钢轨磨损对确保铁路运输安全非常重要。轨道轮廓配准是轨道磨损测量的关键步骤。但由于钢轨腰部有泥土和腐蚀，无法保证钢轨轮廓配准的准确性。针对这一问题，本文提出了一种基于法向量方向概率迭代最近点算法(N-PICP)的钢轨轮廓配准新方法。首先，使用线结构光测量系统获得轨道轮廓数据。然后，根据相邻点之间的距离将钢轨剖面数据分为轨头和轨腰。N-PICP 使用轨腰数据与标准型材数据的相应部分进行注册。最后，轨头数据也根据计算出的变换矩阵进行变换。实验结果表明，该方法能够实现轨道轮廓的配准精度高、鲁棒性强。