Paper
12 March 2008 Estimation of the measurement uncertainty based on quasi Monte-Carlo method in optical measurement
Hui Jing, Mei-fa Huang, Yan-ru Zhong, Bing Kuang, Xiang-qian Jiang
Author Affiliations +
Proceedings Volume 6624, International Symposium on Photoelectronic Detection and Imaging 2007: Optoelectronic System Design, Manufacturing, and Testing; 66240Q (2008) https://doi.org/10.1117/12.791087
Event: International Symposium on Photoelectronic Detection and Imaging: Technology and Applications 2007, 2007, Beijing, China
Abstract
Because measurement uncertainty is an important parameter to evaluate the reliability of measurement results, it is essential to present reliable methods to evaluate the measurement uncertainty especially in precise optical measurement. Though Monte-Carlo (MC) method has been applied to estimate the measurement uncertainty in recent years, this method, however, has some shortcomings such as low convergence and unstable results. Therefore its application is limited. To evaluate the measurement uncertainty in a fast and robust way, Quasi Monte-Carlo (QMC) method is adopted in this paper. In the estimating process, more homogeneous random numbers (quasi random numbers) are generated based on Halton's sequence, and then these random numbers are transformed into the desired distribution random numbers. An experiment of cylinder measurement is given. The results show that the Quasi Monte-Carlo method has higher convergence rate and more stable evaluation results than that of Monte-Carlo method. Therefore, the quasi Monte-Carlo method can be applied efficiently to evaluate the measurement uncertainty.
© (2008) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Hui Jing, Mei-fa Huang, Yan-ru Zhong, Bing Kuang, and Xiang-qian Jiang "Estimation of the measurement uncertainty based on quasi Monte-Carlo method in optical measurement", Proc. SPIE 6624, International Symposium on Photoelectronic Detection and Imaging 2007: Optoelectronic System Design, Manufacturing, and Testing, 66240Q (12 March 2008); https://doi.org/10.1117/12.791087
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Cited by 6 scholarly publications.
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KEYWORDS
Monte Carlo methods

Optical testing

Statistical analysis

Computer simulations

Reliability

Imaging systems

Probability theory

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