中文摘要：

从虚拟仪器测量系统组成机理出发,首先分析测量链的随机误差源,应用径向基函数（RBF）神经网络构建了虚拟仪器测量的数学模型,并使用差分方程计算误差传播系数;对于小样本虚拟仪器测量,应用灰色系统理论解决不适于用统计方法计算各误差源相关系数的计算问题,最后按GUM方法实现了虚拟仪器测量不确定度的评定。通过具体的虚拟仪器测量实例,按这种方法计算测量不确定度,并将评定结果与蒙特卡罗评定结果比较,达到了很好的一致性,从而验证了这种方法。

英文摘要：

There are three problems should be solved in the case of small sample virtual instrument measurement： establishing measurement model, calculating transfer coefficients and correlation coefficients. ISO GUM （Guide to the expression of uncertainty in measurement） method is used to evaluate the final uncertainty. To analyze the random errors of the virtual instrument measurement chain, composing mechanism of a general virtual instrument measurement system is discussed in the first. To establish the model of small sample virtual instrument measurement, a radial basis function （RBF） neural network is employed, and then the transfer coefficients are calculated by a difference equation for all error sources. To calculate the correlation coefficients for all error sources, a new method based on grey system theory is advanced. In the end; according to a special example analysis, the uncertainty evaluation results of the proposed method and Monte Carlo method are in good agreements with each other, and the validity of this method is also discribed.