Title :
Gas/liquid two-phase flow regime identification in horizontal pipe using support vector machines
Author :
Qi, Guo-Hua ; Dong, Feng ; Xu, Yan-Bin ; Wu, Meng-Meng ; Hu, Jun
Author_Institution :
Sch. of Electr. & Autom. Eng., Tianjin Univ., China
Abstract :
Flow regime is one of the fundamental parameters with important engineering significance in two-phase flow systems, and has always been an important aspect of two-phase flow research. In this paper, the support vector machine (SVM) method in statistics theories was adopted to analyze the measured data of electrical resistance tomography (ERT) system so that the flow regime identification of gas/liquid two-phase in horizontal pipe was carried out. The analysis result of experiment data indicates that this method can obtain an inspiring result.
Keywords :
data analysis; electric resistance; support vector machines; tomography; two-phase flow; electrical resistance tomography; gas/liquid two-phase flow regime identification; horizontal pipe; support vector machine; Capacitance measurement; Chemical industry; Conductivity measurement; Electric resistance; Electric variables measurement; Electrical resistance measurement; Fluid flow; Fluid flow measurement; Support vector machines; Tomography; Electrical Resistance Tomography; Flow Regime Identification; Support Vector Machine; Two-Phase Flow;
Conference_Titel :
Machine Learning and Cybernetics, 2005. Proceedings of 2005 International Conference on
Conference_Location :
Guangzhou, China
Print_ISBN :
0-7803-9091-1
DOI :
10.1109/ICMLC.2005.1527227
