一种在线评估超声波气体流量计性能的新方法OA北大核心CSTPCD

A new method for online performance evaluation of ultrasonic gas flowmeters is proposed,based on a Bayesian information fusion approach to establish a change point detection model.This method captures the trend of measurement data changes to achieve real-time performance assessment of the flowmeter.The implementation involves combining prior information with real-time sample data,iteratively updating to obtain the posterior distribution,with the posterior standard deviation representing the instrument's real-time uncertainty.Compared to traditional uncertainty assessment methods,this approach integrates real-time measurement data,allowing for continuous evaluation of the instrument's uncertainty and monitoring of the entire measurement system's operation.It can promptly detect abnormal working conditions,thereby enabling online performance evaluation of the flowmeter.At a low flow rate point of Q=10 m3/h,the relative expanded uncertainty is 1.52％,meeting the metrological accuracy requirements.