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Research on the uncertainties from different form error evaluation methods by CMM sampling

机译:基于三坐标测量机的不同形式误差评估方法的不确定性研究

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As a part of the new measurement uncertainty system proposed in the new generation of Geometrical Product Specifications and Verification, the evaluation methods of uncertainties to form errors have been researched in mechanical engineering, which are calculated based on the error propagation principle and statistical concept under certain conditions. In this paper, the evaluation datum is obtained by using both the least squares method and the genetic optimization algorithm. Their computation uncertainties to flatness and roundness were compared with each other using the sample data from a coordinate measurement machine (CMM). The results show that the uncertainties obtained from the genetic algorithm-based method are similar to those from the least squares method according to their evaluation parameters. The evaluation uncertainties from different methods become a little smaller with more sample points. A more significant conclusion is that the evaluation uncertainties from two methods are so small that they almost do not affect the measurement uncertainties to form error, which, in fact, mainly comes from the CMM sampling. Therefore, for the efficiency and simplification of calculation, especially for the cylintricity with more parameters, the uncertainties from evaluation methods can be neglected where the precision is not so strict.
机译:作为新一代几何产品规格与验证中提出的新测量不确定性系统的一部分,机械工程学中研究了形成误差的不确定性评估方法,该方法是根据误差传播原理和统计概念在一定条件下计算得出的条件。本文采用最小二乘法和遗传优化算法共同获得评价数据。使用来自坐标测量机(CMM)的样本数据,比较了它们对平面度和圆度的计算不确定性。结果表明,根据遗传算法的评估参数,其不确定性与最小二乘法相似。来自更多方法的评估不确定性会随着采样点的增加而变小。一个更有意义的结论是,两种方法的评估不确定性非常小,以至于它们几乎不会影响测量不确定性而形成误差,这实际上主要来自于CMM采样。因此,为了提高效率和简化计算,特别是对于具有更多参数的圆柱度,可以在精度不太严格的情况下忽略评估方法的不确定性。

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