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A LIBRARY OF FEATURE FITTING ALGORITHMS FOR GDT VERIFICATION OF PLANAR AND CYLINDRICAL FEATURES

机译:平面和圆柱特征GD&T验证的特征拟合算法库

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Conformation of a manufactured feature to the applied geometric tolerances is done by analyzing the point cloud that is measured on the feature. To that end, a geometric feature is fitted to the point cloud and the results are assessed to see whether the fitted features lies within the specified tolerance limits or not. Coordinate Measuring Machines (CMMs) use feature fitting algorithms that incorporate least square estimates as a basis for obtaining minimum, maximum, and zone fits. However, a comprehensive set of algorithms addressing the fitting procedure (all datums, targets) for every tolerance class is not available. Therefore, a Library of algorithms is developed to aid the process of feature fitting, and tolerance verification. This paper addresses linear, planar, circular, and cylindrical features only. This set of algorithms described conforms to the international Standards for GD&T. In order to reduce the number of points to be analyzed, and to identify the possible candidate points for linear, circular and planar features, 2D and 3D convex hulls are used. For minimum, maximum, and Chebyshev cylinders, geometric search algorithms are used. Algorithms are divided into three major categories: least square, unconstrained, and constrained fits. Primary datums require one sided unconstrained fits for their verification. Secondary datums require one sided constrained fits for their verification. For size and other tolerance verifications we require both unconstrained and constrained fits.
机译:通过分析在特征上测量的点云,可以使制造的特征与所应用的几何公差相一致。为此,将几何特征拟合到点云,并对结果进行评估,以查看所拟合的特征是否在指定的公差范围内。坐标测量机(CMM)使用特征拟合算法,该算法结合了最小二乘估计作为获取最小,最大和区域拟合的基础。但是,没有针对每种公差等级的适用于拟合过程(所有基准,目标)的全面算法集。因此,开发了一个算法库来辅助特征拟合和公差验证的过程。本文仅涉及线性,平面,圆形和圆柱特征。所描述的这套算法符合GD&T的国际标准。为了减少要分析的点的数量,并确定线性,圆形和平面特征的可能候选点,使用了2D和3D凸包。对于最小,最大和Chebyshev圆柱,使用几何搜索算法。算法分为三大类:最小二乘,无约束和约束拟合。主基准需要单侧无约束拟合进行验证。次要基准面需要使用一侧约束拟合进行验证。对于尺寸和其他公差检验,我们需要无约束和有约束的配合。

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