ISSN: 0090-3973
Page Count: 7

Novel Uncertainty-Evaluation Method of Virtual Instrument Small Sample Size
Leyi, Ge
School of Instrument Science and Opto-Electronics Engineering, Beihang University,

Zhongyu, Wang

Abstract

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.

Keywords:
virtual instrument, uncertainty-evaluation, small sample, RBF neural network, grey system theory

Paper ID: JTE101454
DOI: 10.1520/JTE101454
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