首页> 外文会议>ASME international manufacturing science and engineering conference 2011 >A VERTEX TRANSLATION ALGORITHM FOR ADAPTIVE MODIFICATION OF STL FILE IN LAYERED MANUFACTURING
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A VERTEX TRANSLATION ALGORITHM FOR ADAPTIVE MODIFICATION OF STL FILE IN LAYERED MANUFACTURING

机译:分层制造中STL文件自适应修改的顶点翻译算法

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摘要

Rapid Prototyping (RP)/Layered Manufacturing (LM) machines typically use a Stereolithography (STL) file as a basis to manufacture parts. However, the conversion of the part CAD file to STL results in the distortion of the part geometry, particularly if the part consists of freeform curved surfaces. Existing algorithms and software tend to reduce this distortion globally, which increases the size and memory requirements of the STL file. This paper presents a new approach for reducing the CAD to STL translation error locally, using chordal error as the criteria. The algorithm presented here compares the STL file to the design surface of the part, expressed as a NURBS surface, and computes the chordal error for multiple points on the STL facets. The point within each STL facet having the largest chordal error is modified to coincide with its corresponding point on the design surface. This replaces the original facet of the STL file with three new facets with significantly lower chordal error than that of the original facet. This Vertex Translation Algorithm (VTA), reduces the chordal error in areas with high curvature and areas having tighter profile tolerance specifications and provides the user the flexibility to selectively modify the STL file according to the tolerance requirements. The algorithm has been validated with the help of a test case.
机译:快速成型(RP)/分层制造(LM)机器通常使用立体光刻(STL)文件作为制造零件的基础。但是,将零件CAD文件转换为STL会导致零件几何形状变形,尤其是在零件由自由曲面构成的情况下。现有的算法和软件趋向于在全球范围内减少这种失真,从而增加了STL文件的大小和内存要求。本文提出了一种新的方法,以弦误差为准则,减少CAD到STL的局部翻译误差。此处介绍的算法将STL文件与零件的设计图面(表示为NURBS曲面)进行比较,并计算STL面上多个点的弦误差。修改每个STL小平面中弦误差最大的点,使其与设计图面上的相应点重合。这将用三个新的切面替换STL文件的原始切面,并且弦的误差明显低于原始切面。此顶点转换算法(VTA)可以减少曲率较高的区域和轮廓公差规格更严格的区域的弦误差,并为用户提供了根据公差要求有选择地修改STL文件的灵活性。该算法已通过测试案例进行了验证。

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