Novel uncertainty-evaluation method of virtual instrument small sample size

被引:0
作者
Leyi, Ge [1 ]
Zhongyu, Wang [1 ]
机构
[1] School of Instrument Science and Opto-Electronics Engineering, Beihang University, Beijing
基金
中国国家自然科学基金;
关键词
Grey system theory; RBF neural network; Small sample; Uncertainty-evaluation; Virtual instrument;
D O I
10.1520/jte101454
中图分类号
学科分类号
摘要
Owing to the complication of virtual instrument measurement process, the authors applied Guide to the expression of uncertainty in measurement to evaluate the final measurement-uncertainty. However there are three essential problems that should be solved first: establishing a measurement model, calculating all error sensitivity coefficients, and correlation-coefficient. In order to analyze all random errors of the virtual instrument (VI) measurement chain, in this paper the main structure of VI measurement systems was discussed first. To establish the model of VI small sample measurement, a radial basis function neural network was used, then, based on this model, all error sensitivity coefficients were calculated by some difference equations; to calculate all correlation-coefficient of these error sources, a special arithmetic based on grey system theory was used. In the end, according to a general measurement example, uncertainty-evaluation results of this new method and Monte Carlo method were consistent, and this new method was proved. Copyright © 2008 by ASTM International.
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页码:273 / 279
页数:6
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