Study on the Evaluation of Measurement Uncertainty of Ultrasonic Evaporation Sensor

Abstract

In order to effectively improve the accuracy of measurement data from the ultrasonic evaporation sensor (UES), research is conducted on evaluating the measurement uncertainty of the UES.The UES calibration results for the AG2.0 model are used as an example and are looked at using the Monte Carlo method (MCM), the adaptive Monte Carlo method (AMCM), and the guide to the expression uncertainty in measurement (GUM). This is done to see how well the different evaluation methods work in this area. Firstly, the basic principles of MCM, AMCM, and GUM are introduced, respectively. Then, the UES's working principle and calibration process are looked at. A measurement model that fits is made, and the 60 mm calibration point is used to get calibration results. Finally, MCM, AMCM, and GUM are used to carry out measurement uncertainty on the calibration results, respectively. The results show that those evaluated by MCM and AMCM are basically similar; however, AMCM requires much fewer simulations than MCM (only 3% of those required by MCM). The GUM's applicability has not been verified. Therefore, in uncertainty evaluation in this field, both AMMC and MCM have similar effects, but AMCM's ability to save program running resources and improve evaluation efficiency is significantly better than that offered by MCM. It is recommended to use AMCM, as GUM is no longer applicable for evaluating measurement uncertainty in this field.