›› 2012, Vol. 20 ›› Issue (2): 380-388.

• SELECTED PAPERS FROM THE 6TH WORLD CONGRESS ON INDUSTRIAL PROCESS TOMOGRA-PHY (WCIPT6) • Previous Articles     Next Articles

Dynamic visualization approach of the multiphase flow using electrical capacitance tomography

  

  1. 1 State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources, North China Electric Power University, Beijing 102206, China 2 School of Mechanical Electric and Control Engineering, Beijing Jiaotong University, Beijing 100049, China 3 Key Laboratory of Advanced Energy and Power, Institute of Engineering Thermophysics, Chinese Academy of Sciences, Beijing 100190, China
  • Received:2011-11-18 Online:2011-01-16 Published:2012-04-28
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Key words: electrical capacitance tomography, visualization, flow pattern identification, dynamic reconstruction algorithm

摘要: Identifying the flow patterns is vital for understanding the complicated physical mechanisms in multiphase flows. For this purpose, electrical capacitance tomography (ECT) technique is considered as a promising visualization method for the flow pattern identification, in which image reconstruction algorithms play an important role. In this paper, a generalized dynamic reconstruction model, which integrates ECT measurement information and physical evolution information of the objects of interest, was presented. A generalized objective functional that simultaneously considers the spatial constraints, temporal constraints and dynamic evolution information of the ob-jects of interest was proposed. Numerical simulations and experiments were implemented to evaluate the feasibility and efficiency of the proposed algorithm. For the cases considered in this paper, the proposed algorithm can well reconstruct the flow patterns, and the quality of the reconstructed images is improved, which indicates that the pro-posed algorithm is competent to reconstruct the flow patterns in the visualization of multiphase flows.

关键词: electrical capacitance tomography, visualization, flow pattern identification, dynamic reconstruction algorithm