基于高速摄像法的气液段塞流特性参数测量

CHARACTERISTIC PARAMETER MEASUREMENT OF GAS-LIQUID TWO-PHASE SLUG FLOW BASED ON HIGH-SPEED CAMERA METHOD

在气-液两相段塞流中,液膜段的湿壁分数和弹头倾角是研究气弹段持液率和气弹特性的关键.文章基于光学成像技术设计了高速摄像法的视觉传感器测试系统,实现了气液两相段塞流气弹特性参数测量.基于图像分析技术,优化边缘检测算子,精确定位边缘位置,高质量提取了轮廓分布,将机器学习模型作为预测多相流特征参数的一种新方法,对气弹弹头倾角进行数据建模研究,分析了适用于分层平滑流、波浪和环状流的表观粗糙表面(modified apparent rough surface,MARS)模型以及段塞流气弹区和液膜区流动状态机理,在MARS模型基础上进行了参数优化,使其适用于段塞流液膜处的湿壁分数和持液率求解.结果表明:通过数据拟合的多项式模型弹头倾角α的模型预测结果的平均绝对百分比误差(MAPE)为8.87%,94.6%预测结果处于相对误差±20%的范围内.通过修正MARS模型提出的水平管段塞流液膜处湿壁分数预测结果的MAPE为9.42%,96.1%预测结果处于相对误差±20%的范围内.液膜持液率预测模型结果的MAPE约为8.04%,93.4%预测结果处于相对误差±20%的范围内.

In the gas-liquid two-phase slug flow,the wet-wall fraction and the tilt Angle of the bullet are the key to study the liquid holdup and the elastic characteristics of the gas-elastic section.Based on the image analysis technology,the edge detection operator was optimized,accurately locate the edge position,extract the contour distribution of the gasliquid interface with high quality,in this paper,based on the optical imaging technology,a vision sensor test system with high-speed camera method is designed,and the gas elastic characteristic parameters of gas-liquid two-phase slug flow are measured.The machine learning model is used as a new method to predict the characteristic parameters of multiphase flow.The data modeling of the inclination,the angle of the aeroelastic head is studied,and the apparent rough surface(MARS)model applicable to stratified smooth flow,wave flow and annular flow as well as the flow state mechanism in the aeroelastic and liquid film region of slug flow are analyzed.The parameters are optimized based on the MARS model.The method can be applied to the solution of wet wall fraction and liquid holdup at slug film.The results show that the mean absolute percentage error(MAPE)of the model prediction result of the polynomial model of warhead inclinationαby data fitting is 8.87%,and the relative error of 94.6% is within the error range of ±20%.The MAPE of the prediction results of wet wall fraction at the liquid film of the horizontal pipe slug flow proposed by the modified MARS model is 9.42%,and the relative error of 96.1% of the prediction results is within the error range of ±20%.The MAPE of the prediction model is about 8.04%,and 93.4% of the predicted results are within the relative error range of±20%.