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文章基本信息

  • 标题:Evaluation of Measurement Uncertainty Based on Monte Carlo Method
  • 本地全文:下载
  • 作者:X M Wang ; J L Xiong ; J Z Xie
  • 期刊名称:MATEC Web of Conferences
  • 电子版ISSN:2261-236X
  • 出版年度:2018
  • 卷号:206
  • DOI:10.1051/matecconf/201820604004
  • 语种:English
  • 出版社:EDP Sciences
  • 摘要:The developments of scientific technology are inseparable from various measurement methods. Measurement uncertainty is an indication that evaluates the credibility of the measurement results directly, and it affects the development of technology and economy indirectly. Monte Carlo method (MCM) is an effective method to evaluate the measurement uncertainty, because it can evaluate the measurement uncertainty in the complex model and environment. The application range of MCM is large than the traditional method that recommended in the “Guide to the Uncertainty in Measurement (GUM)”. Based on the study of Monte Carlo method, this paper establishes a model for MCM to evaluate the uncertainty of measurement. Finally, as an example, we use the MCM to evaluate the measurement uncertainty of the six-and-a-half digital multimeter (DMM), which verifies the validity of MCM for evaluating the measurement uncertainty.
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