钢轨探伤车车轴齿轮箱的优化设计

在对原有车轴齿轮箱的结构进行分析的基础上,对其关键零部件、密封系统及部分零件加工工艺进行了优化设计,并通过试验验证了优化设计的效果,提高了钢轨探伤车车轴齿轮箱的可靠性.     

Graph and hint based algorithm for machining feature automation recognition and mapping

Feature recognition is a process of extracting machining features which has engineering meaning from solid model, and it is a key technology of CAD/CAPP/CAM integration. This paper presents an effective and efficient methodology of recognizing machining feature. In this approach, features are classified into two categories: pocket feature and predefined feature. Different feature type adopts its special hint and heuristic rule, and is helpful to recognize intersection feature. Feature classification optimizes search algorithm and shortens search scope dramatically. Meanwhile, extension and split algorithm is used to handle intersecting feature. Moreover, feature mapping based on machining knowledge is introduced to support downstream application better. Finally, case studies with complex intersecting features prove that the developed approach has stronger recognizing ability.     

Curvature estimation of point set data based on the moving-least square surface

Curvature estimation is a basic step in many point relative applications such as feature recognition, segmentation, shape analysis and simplification. This paper proposes a moving-least square (MLS) surface based method to evaluate curvatures for unorganized point cloud data. First a variation of the projection based MLS surface is adopted as the underlying representation of the input points. A set of equations for geometric analysis are derived from the implicit definition of the MLS surface. These equations are then used to compute curvatures of the surface. Moreover, an empirical formula for determining the appropriate Gaussian factor is presented to improve the accuracy of curvature estimation. The proposed method is tested on several sets of synthetic and real data. The results demonstrate that the MLS surface based method can faithfully and efficiently estimate curvatures and reflect subtle curvature variations. The comparisons with other curvature computation algorithms also show that the presented method performs well when handling noisy data and dense points with complex shapes.