基于机器学习算法的超声流量计使用中检验

In-use Measurement of Ultrasonic Flowmeter Based on Machine Learning Algorithms

为保证使用中超声流量计的准确度,基于随机森林算法,建立了超声流量计使用中检验预测分析模型。研究了超声流量计使用中检验程序。首先,获取超声流量计的信号质量数据、流态指标数据、以及计量性能数据;其次,采用随机森林算法对使用中超声流量计的流量偏差进行预测,预测值与真实值的偏差在0.76%以内,分析了影响使用中超声流量计测量准确度的各数据对超声流量计性能的影响程度;最后,对预测模型的不确定度进行分析,其扩展不确定度U=0.92%~0.22%(k=2)。

Based on random forest algorithms,a prediction and analysis model of the in-use measurement of ultrasonic flowmeter is established to guarantee the accuracy of ultrasonic flowmeter.The study first establishes the in-use measurement procedure of the ultrasonic flowmeter.By obtaining data of the flowmeter signal index,flow rate characteristics,sound velocity and flow velocity etc.,the flow deviation of ultrasonic flow meter is predicted by random forest algorithm,and the difference between predicated value and true value is smaller than 0.76%.Furthermore,the degree of influence for different factors on the accuracy of ultrasonic flowmeter are analyzed.The uncertainty of the model is evaluated,with extended uncertainty U=0.92%~0.22%(k=2).