Electrical resistance tomography for control applications: Quantitative study of the gas-liquid distribution inside a cyclone

Muhammad Awais Sattar, Matheus Martinez Garcia, Robert Banasiak, Luis M. Portela, Laurent Babout

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Abstract

Phase separation based centrifugal forces is effective, and thus widely explored by the process industry. In an inline swirl separator, a core of the light phase is formed in the center of the device and captured further downstream. Given the inlet conditions, this gas core created varies in shape and size. To predict the separation behavior and control the process in an optimal way, the gas core diameter should be measured with the minimum possible intrusiveness. Process tomography techniques such as electrical resistance tomography (ERT) allows us to measure the gas core diameter in a fast and non-intrusive way. Due to the soft-field nature and ill-posed problem in solving the inverse problem, especially in the area of low spatial resolution, the reconstructed images often overestimate the diameter of the object under consideration leading to unreliable measurements. To use ERT measurements as an input for the controller, the estimated diameters should be corrected based on secondary measurements, e.g., optical techniques such as high-speed cameras. In this context, image processing and image analysis techniques were adapted to compare the diameter calculated by an ERT system and a fast camera. In this paper, a correction method is introduced to correct the diameter obtained by ERT based on static measurements. The proposed method reduced the ERT error of dynamic measurements of the gas core size from over 300% to below 20%, making it a reliable sensing technique for controlled separation processes.

Original languageEnglish
Article number6069
Pages (from-to)1-24
JournalSensors (Switzerland)
Volume20
Issue number21
DOIs
Publication statusPublished - 2020

Keywords

  • Digital image processing
  • Electrical resistance tomography (ERT)
  • High-speed camera
  • Swirling two-phase flow

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