Design and Optimization of Graphene Film Micro Flow Sensor Based on Uncertainty Analysis

For a differential pressure micro flow sensor based on a graphene film, uncertainty analysis was conducted on the measurement results of the sensor sample, based on the measurement mechanism model established and validated. Traditional uncertainty analysis methods based on the Guide to the Uncertainty in Measurement (GUM) and uncertainty analysis methods based on the Monte Carlo method (MCM) were used to obtain the uncertainty of the measurement results of the micro flow sensor, and the analysis results were compared. On this basis, parameters with significant impact were obtained through the interquartile range (IQR) analysis and GUM method, and the MCM method was combined with the parameter optimization method to optimize the parameters for the goal of reducing the uncertainty of sensor measurement results. Based on the uncertainty analysis, the impact degree of different parameters and optimization results has been obtained, which could be used as a reference for the physical design of the micro flow sensor.