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Research on Uncertainty Evaluation Methods of Straightness of Straight Edge Based on Monte Carlo Method |
LI Yuan-feng1,MENG Ling-chuan1,HUANG Yao2,YANG Hao-tian3 |
1. Beijing Jiaotong University, Beijing 100044, China
2. National Institute of Metrology, Beijing 100029, China
3. University College London, London, WC1E 6BT, UK |
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Abstract The straightness uncertainty of straight edge in least-square rule and in minimum-zone rule have been evaluated by Monte Carlo method (MCM). Comparing with the straightness uncertainty evaluated by guide to the expression of uncertainty in measurement (GUM), it's been found that the straightness uncertainty in least-square rule evaluated by MCM is 0.028 μm less than that by GUM and the straightness uncertainty in minimum-zone rule evaluated by MCM is 0.026 μm less than that by GUM. It has been confirmed that both the methods are valid for evaluating the straightness uncertainty of straight edge at a certain numerical tolerance of 0.05 μm. Kolmogorov-smirnov test, jarque-bera test, normal probability plot, skewness and kurtosis test were employed as the statistic testing methods. By employing specific statistic testing method on measurand, it's been found that the kurtosis deviation of measurand distribution from normal distribution is responsible for the uncertainty difference.
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Received: 03 December 2021
Published: 18 April 2023
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