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New Algorithms for the Evaluation of Discrete Point Measurement Data and for Sample Point Selection on Surfaces With Systematic Form Deviations

机译:用于评估离散点测量数据和选择具有系统形式偏差的曲面上的采样点的新算法

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The use of coordinate measuring machines (CMMs) and other discrete point sampling devices in dimensional metrology has raised questions regarding the proper interpretation of data which technically constrains a surface only at the points measured. Reconciling the intrinsic limitations of such inspection techniques with dimensioning and tolerancing standards which often make the implicit assumption that surfaces can be fully characterized has been an issue of major concern in the metrology community in recent years. In addition economic considerations argue for more efficient and reliable procedures for dimensional inspection. This has led to the desire to find sampling and data analysis methods by which the information available through discrete point sampling is maximized.
机译:在尺寸计量学中坐标测量机(CMM)和其他离散点采样设备的使用提出了有关数据的正确解释的问题,这些数据在技术上仅在所测量的点处约束表面。近年来,这种检测技术的固有局限性与尺寸和公差标准相一致,而尺寸和公差标准常常隐含着可以对表面进行充分表征的隐含假设,这已成为近年来计量界关注的主要问题。此外,出于经济考虑,还要求采用更有效,更可靠的尺寸检查程序。这导致人们希望找到一种采样和数据分析方法,以使通过离散点采样获得的信息最大化。

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