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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来完成制造特征对所施加的几何公差的构象。为此,将几何特征安装在点云上,并评估结果,以了解拟合特征是否位于指定的公差范围内。坐标测量机(CMMS)使用具有最小二乘估计的特征拟合算法作为获得最小,最大和区域的基础。但是,不可用的全面综合算法,用于满足每个公差类的拟合程序(所有基准,目标)。因此,开发了一种算法库以帮助特征拟合的过程和公差验证。本文仅介绍了线性,平面,圆形和圆柱特征。这组算法描述了符合GD&T的国际标准。为了减少要分析的点数,并识别用于线性,圆形和平面特征的可能候选点,使用2D和3D凸壳。对于最小,最大和Chebyshev气缸,使用几何搜索算法。算法分为三个主要类别:最小二乘,不受约束和受约束的拟合。主要基准需要一个不同的不受约束适合其验证。辅助基准需要一个面向约束的验证。对于尺寸和其他公差验证,我们需要无疑和受限制的适合。

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