The Identification Method of Gas-Liquid Two-Phase Flow Regime Based on EMD Complezity Feature
Gas-liquid two-phase flow widely exists in modern industry production. The accurate measurement of other parameters and the performance character of two-phase flow are influenced by the flow regimes. So the identification of different flow regimes has long been a signification topic in the parameter measurement of two-phase system. A Gas-liquid two-phase flow regime identification method based on EMD and LZC features and support vector machine was proposed. The support vector machine was trained using these eigenvectors as flow regime samples, and the flow regime intelligent identification was realized. The test results show that EMD and LZC features can excellently reflect the difference between the typical flow regimes, and successful training the support vector machine can quickly and accurately identify seven typical flow regimes of gas-liquid two-phase flow in the horizontal tube. The whole identification accuracy is 100％, and an estimation of the processing time for each image is 0.8s for online flow regime identification of a new and effective method.
flow regime identification image processing moment invariant support vector machine
SUN Bin LI Chao ZHOU Yunlong
School of Energy and Mechanical Engineering, Northeast Dianli University, Jilin, 132012, China
国际会议
第八届国际测试技术研讨会(8th International Symposium on Test and Measurement)
重庆
英文
2929-2933
2009-08-01（万方平台首次上网日期，不代表论文的发表时间）