【摘要】 针对无测量模型的间接测量不确定度评定问题,以径向基函数神经网络模型为基础,提出了建立间接测量解析模型和利用该模型计算灵敏系数的方法,导出了间接测量模型的解析表达式和灵敏系数的计算公式。仿真结果表明:神经网络解析模型的建模方法及灵敏系数的计算方法具有较高的精度,从而保证了间接测量结果的估计精度及测量不确定度的评定精度。更多还原

【Abstract】 A new method is developed to solve the problem of evaluating the measurement uncertainty in indirect measurement with no given measurement model.An analytical model based on neural network using Radial Basis Function is set up.The expression of indirect measurement model and the calculation formula of the sensitivity coefficient are derived.The simulation results showed that the analytical model based on neural network and the method of sensitivity coefficient calculation has high precision,thus effectively guarantees the precision of measurement result and its uncertainty estimation in indirect measurement.更多还原