【摘要】 高速列车车头曲面的制造精度对于列车的空气动力性有着重要的影响，对其形状误差进行评定是车头质量监测中的重要部分。随着测量技术的提高，通过光学测量技术得到高密度的点云数据可以详细表示车头曲面的三维信息。但同时，大量的测量点会带来空间相关性问题。为克服空间相关性对形状误差评定的影响，提出了一种基于高斯相关性的三维曲面形状误差模型，并通过T~2控制图对三维曲面的形状误差进行监控。通过对自由曲面的仿真验证了所提出的方法可以有效地提高三维曲面形状误差的监控效果，通过高速列车车头曲面实际案例的研究验证了方法的有效性和实用性。更多还原

【Abstract】 The manufacturing accuracy of the locomotive surface of a high-speed train has an important influence on the aerodynamics of the train. The evaluation of form error is an important issue of the train quality monitoring. With the improvement of measurement technology, the high-density point cloud data obtained by optical measurement technology can represent the three-dimensional(3D) information of locomotive surface in detail, but at the same time, a large number of measurement points will bring about the problem of spatial correlations. In order to overcome the influence of spatial correlation on form error evaluation, an error model of 3D surface based on Gaussian correlation is proposed, and the form error is monitored through T~2 control chart. A simulation of free-form surfaces verifies that the proposed method can effectively improve the monitoring performance of the form error of 3D surfaces. The effectiveness and practicability of the method are verified through a case study of locomotive surface.更多还原