Paper Title:
Research on Measurement Uncertainty Evaluation Methods Based on Bayesian Principle
  Abstract

In current application of measurement uncertainty evaluation, dynamic uncertainty evaluation simply uses the static uncertainty methods. To change the situation, a new evaluation method of measurement uncertainty is investigated based on Bayesian principle in this paper. Bayesian evaluation method uses conjugate normal-inverted gamma distribution as the distribution function in uncertainty evaluation, which can be employed to evaluate both static and dynamic measurement uncertainty. The evaluation method put forward in this paper can achieve higher evaluation accuracy than the conventional methods, particularly in processing dynamic data with small samples. It has been proved in theory and by computer simulation.

  Info
Periodical
Key Engineering Materials (Volumes 381-382)
Edited by
Wei Gao, Yasuhiro Takaya, Yongsheng Gao and Michael Krystek
Pages
583-586
DOI
10.4028/www.scientific.net/KEM.381-382.583
Citation
X. H. Chen, Z.Y. Cheng, Y. T. Fei, "Research on Measurement Uncertainty Evaluation Methods Based on Bayesian Principle", Key Engineering Materials, Vols. 381-382, pp. 583-586, 2008
Online since
June 2008
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Price
$32.00
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