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Measurement uncertainty distributions and uncertainty propagation by the simulation approach

机译:仿真方法测量不确定度分布和不确定度传播

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摘要

A complete and accurate evaluation of measurement uncertainty requires the knowledge of the uncertainty distributions. The latter are rarely determined or verified experimentally, and hence up to now only crude estimates or assumptions based on intuition have been used. The simulation of experimental results is readily accessible and provides a more reliable solution to this problem. When using an appropriate model of measurement and after determination of input value parameters by present state-of-the-art techniques, simulation data supply reliable information about the distribution of the output results of a complex measurement. The method permits simple variation of preposition and therefore ready analysis of various features influencing the measurement of uncertainty intervals. In the paper we described examples of such evaluations related to the preparation of certified reference materials, where there is excellent agreement between the traditional and simulation approaches. And evaluation of more complex measurements of diffusion coefficients by the open capillary method, where uncertainty of the simulated result is more realistic than the result from the traditional error method due to non-linearity and probably Cauchy distribution in some steps.
机译:完整而准确的测量不确定度评估需要了解不确定度分布。后者很少通过实验确定或验证,因此到目前为止,仅使用了基于直觉的粗略估计或假设。实验结果的模拟很容易获得,并为该问题提供了更可靠的解决方案。当使用适当的测量模型并通过当前的最新技术确定输入值参数后,模拟数据可提供有关复杂测量输出结果分布的可靠信息。该方法允许介词的简单变化,因此可以方便地分析影响不确定性区间测量的各种特征。在本文中,我们描述了与经认证的参考材料的制备有关的此类评估的示例,这些方法在传统方法与模拟方法之间有着很好的一致性。并通过开放毛细管法评估更复杂的扩散系数测量值,由于非线性和某些步骤中的柯西分布,模拟结果的不确定性比传统误差方法的结果更为现实。

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