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Electrical Resistance Tomography for Visualization of Moving Objects Using a Spatiotemporal Total Variation

Bo Chen1, Juan F P J Abascal2, Manuchehr Soleimani3

  • 1Engineering Tomography Lab (ETL), Department of Electronic and Electrical Engineering, University of Bath, Bath BA2 7AY, UK. B.Chen@bath.ac.uk.

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|May 26, 2018
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Summary
This summary is machine-generated.

This study presents a novel method for flow velocity measurement using a single Electrical Resistance Tomography (ERT) system. The technique accurately calculates velocity profiles and monitors fluid movement, improving industrial processing tomography applications.

Keywords:
4D image reconstructionelectrical resistance tomographyflow measurementstotal variation (TV) algorithm

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Area of Science:

  • Industrial Process Monitoring
  • Electrical Engineering
  • Fluid Dynamics

Background:

  • Electrical Resistance Tomography (ERT) is a non-invasive technique for multi-phase flow analysis, valued for its speed and low cost.
  • Total Variation (TV) algorithms enhance image reconstruction quality by handling discontinuous conductivity distributions.
  • Current methods for flow velocity profiling using ERT often require multiple systems, increasing complexity and cost.

Purpose of the Study:

  • To develop a flow velocity measurement method utilizing a single ERT system.
  • To improve the accuracy and efficiency of flow profile and movement monitoring in industrial processes.
  • To introduce a novel spatiotemporal total variation regularization approach for 4D data analysis.

Main Methods:

  • Implementation of a single Electrical Resistance Tomography (ERT) system.
  • Application of a novel spatiotemporal total variation regularization technique for 4D data.
  • Utilisation of a voxel-voxel cross-correlation method for flow profile measurement.

Main Results:

  • Successful calculation of velocity profiles using a single ERT system.
  • Demonstrated ability to monitor volume fraction and movement of fluids.
  • Achieved high accuracy: <1% error for in-plane velocity profiles (3D image) and 4% error for 3D velocity profiling (4D image).

Conclusions:

  • The proposed method enables accurate flow velocity measurement and monitoring with a single ERT system.
  • The spatiotemporal TV regularization and voxel-voxel cross-correlation are effective for flow analysis.
  • Experimental and simulation studies confirm the method's suitability for industrial applications.