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Proceedings Paper

Evaluation of measurement uncertainty based on Bayesian information fusion
Author(s): Shan Wang; Xiaohuai Chen; Qiao Yang
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Paper Abstract

This paper raises a new method for evaluating uncertainty that taking count of both the record and the data. By using Bayesian Statistical Principle, the prior distribution and the posterior one, provided by the record and the data, were combined together. The statistical characteristics parameter estimation was descended from the posterior distribution, so that a formula of the uncertainty, which combined the advantages of type A and B, was acquired. By simulation and verification, this measurement shows great advantages compared with the others, especially to small size of data analysis.

Paper Details

Date Published: 10 October 2013
PDF: 8 pages
Proc. SPIE 8916, Sixth International Symposium on Precision Mechanical Measurements, 89160M (10 October 2013); doi: 10.1117/12.2035725
Show Author Affiliations
Shan Wang, Hefei Univ. of Technology (China)
Xiaohuai Chen, Hefei Univ. of Technology (China)
Qiao Yang, Hefei Univ. of Technology (China)


Published in SPIE Proceedings Vol. 8916:
Sixth International Symposium on Precision Mechanical Measurements
Shenghua Ye; Yetai Fei, Editor(s)

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