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PDF(2686 KB)
PDF(2686 KB)
基于蒙特卡洛法的压力传感器测量模型不确定度评定
Uncertainty Evaluation of Measurement Model of Pressure Sensor Based on Monte Carlo Method
利用蒙特卡洛法对压力传感器测量模型进行不确定度评定。首先设定压力传感器校准数据输入输出关系为一阶线性模型,利用最小二乘法得到模型参数估计值;而后结合实际测量过程中采集的电压与被测压力的关系,综合得到反映被测压力与校准数据关系的测量模型,并以此模型为基础利用蒙特卡洛法进行压力不确定度评定,与GUM等评定方法进行比较,同时分析不确定度影响因素。实验结果表明,蒙特卡洛法能充分考虑输入量信息,更简洁易行,评定结果更准确。校准时检定点的均值、标准差、数量以及误差源会影响压力测量不确定度曲线的最小值及最小值点,数字多用表准确度比压力校准器准确度对压力测量不确定度影响更大。
Monte Carlo method (MCM) was used to evaluate the uncertainty of pressure sensor measurement model. Firstly, the relationship between input and output of pressure sensor calibration data was set as a first-order linear model, and the parameter estimates of the model were obtained by least square method. Then, combined with the relationship between voltage and measured pressure collected in the actual measurement process, a measurement model reflecting the relationship between measured pressure and calibration data was established. Based on this model, MCM was used to evaluate the pressure uncertainty, compared with GUM and fitted standard deviation theory methods, and the influencing factors of uncertainty were analyzed. The experimental results show that the MCM evaluation process can fully consider the input information and is more simple and easy. In pressure calibration, the mean value, standard deviation, quantity of sampling points and error source can affect the uncertainty curve of pressure measurement, especially in the characteristics of the minimum point and minimum value of the curve. The precision of digital multimeter has greater influence on the uncertainty of pressure measurement than that of pressure calibrator.
力学计量 / 压力传感器 / 测量不确定度 / 蒙特卡洛法 / 最小二乘法
mechanical metrology / pressure sensor / measurement uncertainty / Monte Carlo method / least square method
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