段塞流是气液两相流中典型流型,准确测量其分相流量有利于实时监控生产过程,优化工艺控制,确保系统在安全、经济的工况下运行.本文在改进长喉文丘里管的基础上,设计了一种集近红外(NIR)、声发射(AE)技术于一体的水平气液流量智能多传感系统.利用AE传感器和NIR传感器检测气液两相的流动噪声信息和截面信息,采用经验模态分解法(EMD)提取气体体积分数的特征变量.通过集成学习算法进行特征级融合,融合后的段塞流体积含气率预测模型平均绝对百分比误差(MAPE)为4.11%,92.45%的预测结果偏差在±10%以内.在Collins模型的基础上,提出了基于梯度提升决策树(GBDT)的段塞流质量流量预测模型,其MAPE值为0.96%,全部预测结果的偏差在±20%以内.本研究为气液两相流段塞流参数混合不分离测量提供了一种新方法,为气液两相流动机理研究奠定了基础.
Plug flow is a typical flow pattern in gas-liquid two-phase flow, and accurate measurement of plug flow is conducive to real-time monitoring and optimizing process of production process, ensuring safe and economical operation of the system. Based on the improved Venturi tube with long throat diameter, an intelligent multi-sensor system for horizontal gas-liquid flow is designed, which integrates near infrared(NIR)and acoustic emission(AE)technology. AE sensor and NIR sensor were used to detect the gas-liquid phase interaction and disturbance information, and empirical mode decomposition(EMD)was used to extract the characteristic variables of gas volume fraction. The integrated learning algorithm was used- DOI:10.3969/j.issn.1000-1565.2024.05.011基于集成学习和信息融合的段塞流分相流量测量温佳祺1,2,杨叙宁1,2,李金硕1,丁振君1,3,董芳1,3(1.河北大学 质量技术监督学院,河北 保定 071002;2.零碳能源建筑与计量技术教育部工程研究中心,河北 保定 071002;3.计量仪器与系统国家地方联合工程研究中心,河北 保定 071002)摘 要:段塞流是气液两相流中典型流型,准确测量其分相流量有利于实时监控生产过程,优化工艺控制,确保系统在安全、经济的工况下运行.本文在改进长喉文丘里管的基础上,设计了一种集近红外(NIR)、声发射(AE)技术于一体的水平气液流量智能多传感系统.利用AE传感器和NIR传感器检测气液两相的流动噪声信息和截面信息,采用经验模态分解法(EMD)提取气体体积分数的特征变量.通过集成学习算法进行特征级融合,融合后的段塞流体积含气率预测模型平均绝对百分比误差(MAPE)为4.11%,92.45%的预测结果偏差在±10%以内.在Collins模型的基础上,提出了基于梯度提升决策树(GBDT)的段塞流质量流量预测模型,其MAPE值为0.96%,全部预测结果的偏差在±20%以内.本研究为气液两相流段塞流参数混合不分离测量提供了一种新方法,为气液两相流动机理研究奠定了基础.关键词:气液两相流;数据融合;段塞流;多传感器;集成学习算法中图分类号:TH814 文献标志码:A 文章编号:1000-1565(2024)05-0541-10Phase separation flow measurement of plug flow based on ensemble learning and information fusionWEN Jiaqi1,2,YANG Xuning1,2,LI Jinshuo1, DING Zhenjun1,3, DONG Fang1,3(1. School of Quality and Technical Supervision, Hebei University, Baoding 071002, China; 2. Engineering Research Center of Zero-carbon Energy Bulidings and Measurement Techniques,Ministry of Education,Baoding 071002,China;3. National and Local Joint Engineering Research Center for Measuring Instruments and Systems, Baoding 071002, China)Abstract: Plug flow is a typical flow pattern in gas-liquid two-phase flow, and accurate measurement of plug flow is conducive to real-time monitoring and optimizing process of production process, ensuring safe and economical operation of the system. Based on the improved Venturi tube with long throat diameter, an intelligent multi-sensor system for horizontal gas-liquid flow is designed, which integrates near infrared(NIR)and acoustic emission(AE)technology. AE sensor and NIR sensor were used to detect the gas-liquid phase interaction and disturbance information, and empirical mode decomposition(EMD)was used to extract the characteristic variables of gas volume fraction. The integrated learning algorithm was used- 收稿日期:2024-03-06;修回日期:2024-05-02 基金项目:国家自然科学基金资助项目(62173122);河北省自然科学基金资助项目(F2022201034) 第一作者:温佳祺(2000—),女,河北大学在读硕士研究生,主要从事多相流理论及参数检测技术研究.E-mail:benben93657@163.com 通信作者:董芳(1980—),女,河北大学讲师,主要从事多相流参数检测及信息处理技术研究.E-mail:dongfang1023@163.com第5期温佳祺等:基于集成学习和信息融合的段塞流分相流量测量河北大学学报(自然科学版) 第44卷for feature-level fusion. The mean absolute percentage error(MAPE)of the fused plug flow volume gas content prediction model was 4.11%, and the deviation of 92.45% of the predicted results was within ±10%. On the basis of Collins model, a mass flow prediction model of plug flow based on gradient lifting decision tree(GBDT)is proposed. The MAPE value of GBDT is 0.96%, and the deviation of all prediction results is within ±20%. This study provides a new method for measuring the parameters of gas-liquid two-phase plug flow, which provides a research basis for sensing mechanism and measurement of multiphase flow.
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