An Algorithm to Image Individual Phase Fractions of Multiphase Flows Using Electrical Capacitance Tomography

被引:10
作者
Hossain, Md. Sazzad [1 ]
Abir, Md. Towsif [1 ]
Alam, M. Shah [1 ]
Volakis, John L. [2 ]
Islam, Md. Asiful [1 ]
机构
[1] Bangladesh Univ Engn & Technol, Elect & Elect Engn Dept, Dhaka 1000, Bangladesh
[2] Florida Int Univ, Coll Engn & Comp, Miami, FL 33174 USA
关键词
Permittivity; Image reconstruction; Probes; Electrodes; Sensors; Tomography; Inverse problems; electrical capacitance tomography; Landweber method; multiphase flow; industrial process tomography; RECONSTRUCTION;
D O I
10.1109/JSEN.2020.3009673
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
In this paper, an algorithm using electrical capacitance tomography has been proposed to image and continuously monitor individual phases of a multiphase flow components. Instead of directly reconstructing the permittivity of the imaging domain, the proposed method presents successful reconstruction of fractional area/volume of each phase of a multiphase flow using only single frequency measurements. The permittivity image can then be calculated from the reconstructed fraction parameters. For the fraction reconstruction, the conventional cost function is reformulated and solved employing the well-known Landweber method typically used in ECT. Several three and two phase flow scenarios, including gas-oil-water process, have been analyzed and successful fraction parameter reconstructions are demonstrated. Apart from yielding successful reconstruction of individual phases, the proposed method also increases the overall accuracy of permittivity recovery consistently for all the explored cases. Hence, the proposed fraction imaging algorithm can potentially serve as a tool to decompose individual phases of a multiphase flow along with increased image accuracy.
引用
收藏
页码:14924 / 14931
页数:8
相关论文
共 50 条
  • [21] Image Reconstruction in Electrical Capacitance Tomography Based on Deep Neural Networks
    Deabes, Wael
    Khayyat, Khalid M. Jamil
    IEEE SENSORS JOURNAL, 2021, 21 (22) : 25818 - 25830
  • [22] Image Reconstruction Algorithm Based on Kalman Filter for Electrical Capacitance Tomography
    Wang Lili
    Chen Deyun
    Yu Xiaoyang
    Shen Yue
    2014 FOURTH INTERNATIONAL CONFERENCE ON INSTRUMENTATION AND MEASUREMENT, COMPUTER, COMMUNICATION AND CONTROL (IMCCC), 2014, : 468 - 472
  • [23] Relevance Vector Machine Image Reconstruction Algorithm for Electrical Capacitance Tomography With Explicit Uncertainty Estimates
    Ospina-Acero, Daniel
    Marashdeh, Qussai M.
    Teixeira, Fernando L.
    IEEE SENSORS JOURNAL, 2020, 20 (09) : 4925 - 4939
  • [24] Electrical Capacitance Tomography Reconstruction Algorithm using Kalman Filter
    Zhang, Lifeng
    Li, Jia
    Tian, Pei
    2015 8TH INTERNATIONAL CONGRESS ON IMAGE AND SIGNAL PROCESSING (CISP), 2015, : 919 - 923
  • [25] Split Bregman iteration based image reconstruction algorithm for electrical capacitance tomography
    Tong, Guowei
    Liu, Shi
    Guo, Hongbo
    Chen, Hongyan
    FLOW MEASUREMENT AND INSTRUMENTATION, 2019, 66 : 119 - 127
  • [26] An Image Reconstruction Algorithm Based on the Regularized Minimax Estimation for Electrical Capacitance Tomography
    Lei, Jing
    Liu, Shi
    JOURNAL OF MATHEMATICAL IMAGING AND VISION, 2011, 39 (03) : 269 - 291
  • [27] A PCG-PSO Image Reconstruction Algorithm For Electrical Capacitance Tomography System
    Chen, Yu
    Cao, Jun
    Chen, Deyun
    PRZEGLAD ELEKTROTECHNICZNY, 2012, 88 (9B): : 37 - 41
  • [28] Image reconstruction algorithm for electrical capacitance tomography based on data correlation analysis
    Kang, Yiqun
    Liu, Shi
    Liu, Jing
    FLOW MEASUREMENT AND INSTRUMENTATION, 2018, 62 : 113 - 122
  • [29] Computationally efficient image reconstruction algorithm for electrical capacitance tomography
    Tong, Guowei
    Liu, Shi
    Liu, Sha
    TRANSACTIONS OF THE INSTITUTE OF MEASUREMENT AND CONTROL, 2019, 41 (03) : 631 - 646
  • [30] An Image Reconstruction Algorithm Based on the Regularized Minimax Estimation for Electrical Capacitance Tomography
    Jing Lei
    Shi Liu
    Journal of Mathematical Imaging and Vision, 2011, 39 : 269 - 291