Rail grinding profile prediction in different grinding patterns is important to improve the grinding quality for the rail grinding operation site. However, because of high-dimensional and strong nonlinearity between grinding amount and grinding parameters, the prediction error and computational cost is relatively high. As a result, the accuracy and efficiency of conventional methods cannot be guaranteed. In this article, an accurate and efficient rail grinding profile prediction method is proposed, in which an interval segmentation approach is proposed to improve the prediction efficiency based on the geometric characteristic of a rail profile. Then, the accurate area integral approach with cubic NURBS is used as the grinding area calculation approach to improve the prediction accuracy. Finally, the normal length index is introduced to evaluate the prediction accuracy. The accuracy and stability of the proposed method are verified by comparing a conventional approach based on a practical experiment. The results demonstrate that the proposed method can predict the rail grinding profile in any grinding pattern with high accuracy and efficiency. Meanwhile, its prediction stability basically agrees with the conventional approach.

不同磨削方式下的钢轨磨削轮廓预测对于提高钢轨磨削作业现场的磨削质量非常重要。然而，由于磨削量和磨削参数之间的高维和强非线性，预测误差和计算成本较高。结果，不能保证传统方法的准确性和效率。本文提出了一种准确有效的钢轨磨削轮廓预测方法，其中提出了一种基于钢轨轮廓几何特征的区间分割方法来提高预测效率。然后，采用立方NURBS的精确面积积分方法作为磨削面积计算方法，以提高预测精度。最后，引入正常长度指数以评估预测准确性。通过在实际实验的基础上比较传统方法，验证了所提方法的准确性和稳定性。结果表明，所提出的方法可以在任何磨削模式下以高精度和高效率预测钢轨的磨削轮廓。同时，其预测稳定性与传统方法基本吻合。