Evaluation of Electrical Impedance Tomography System in an Innovative Sensing Strategy for Two-phase Solid-liquid Fluid Monitoring

Document Type : Research Paper

Authors

Department of Agricultural Machinery Engineering, Faculty of Agricultural Engineering and Technology, College of Agriculture and Natural Resources, University of Tehran, Karaj, Iran

Abstract

Abstract: Electrical impedance tomography (EIT) is a non-invasive imaging technique that measures properties of multiphase fluids such as particles distribution and volume concentration by injecting a current into a set of electrodes and reading voltages from the electrodes. A strategy of injection and signal measurement has an important role in the image reconstruction quality and measurement accuracy. In large phantoms with high-conductivity, conventional strategies such as adjacent are not able to measure the signal with suitable quality. Therefore, the purpose of this study is to construct and evaluate the EIT system under an innovative strategy for online determination of particles distribution and concentration of solid-liquid fluid in large phantoms. The sensors of this instrument consist of 16 circular electrodes. The liquid phase was water with known conductivity and solid phase was the bottle in different sizes and in three different situations. The results showed that the innovative strategy has the ability to recognize and differentiate the target in different dimensions and different positions. The signal-to-noise rate was 1.05 dB and the dynamic range of boundary potentials was 1600 mV. The sensitivity to the sides and near the electrodes was more than the sensitivity to the middle. In positions close to the electrodes, size error decreases in medium and large target. In the three sizes of the target, ringing has no negative effect on the reconstructed image quality. Therefore, it can be concluded that the innovative strategy has a desirable performance for determining the distribution of materials in the large phantom.

Keywords

References

Bera, T. K. & Nagaraju, J. (2012). Studying the resistivity imaging of chicken tissue phantoms with different current patterns in Electrical Impedance Tomography (EIT). Measurement. 45(4). 663-682.
Haingartner, M., Gschoßmann, S., Cichocki, M. & Schagerl, M. (2020). Improved current injection pattern for the detection of delaminations in carbon fiber reinforced polymer plates using electrical impedance tomography. Structural Health Monitoring. 25. 147-158.
Humplík, P., Cermák, P. & Zid, T. (2016). Electrical impedance tomography for decay diagnostics of Norway spruce (Picea abies): possibilities and opportunities. Silva Fennica. 50(1). 1341-1357.
Kotze, R., Adler, A., Sutherland, A. & Deba, C. N. (2019). Evaluation of Electrical Resistance Tomography imaging algorithms to monitor settling slurry pipe flow. Flow Measurement and Instrumentation. 68. 101572.
Lesparre, N., Robert, T., Nguyen, F., Boyle, A. & Hermans, T. (2019). 4D electrical resistivity tomography (ERT) for aquifer thermal energy storage monitoring. Geothermics. 77. 368-382.
Liu, L., Fang, Z. Y., Wu, Y. P., Lai, X. P., Wang, P. & Song, K. I. (2018). Experimental investigation of solid-liquid two-phase flow in cemented rock-tailings backfill using Electrical Resistance Tomography. Construction and Building Materials. 175. 267-276.
Malik, D. & Pakzad, L. (2018). Experimental investigation on an aerated mixing vessel through electrical resistance tomography (ERT) and response surface methodology (RSM). Chemical Engineering Research and Design. 129. 327-343.
Marefatallah, M., Breakey, D. & Sanders, R. S. (2021). Experimental study of local solid volume fraction fluctuations in a liquid fluidized bed: Particles with a wide range of stokes numbers. International Journal of Multiphase Flow. 135. 103348.
Ma, G., Hao, Z., Wu, X. & Wang, X. (2020). An optimal Electrical Impedance Tomography drive pattern for human-computer interaction applications. IEEE Transactions on Biomedical Circuits and Systems. 14(3). 402-411.
Mary, B., Peruzzo, L., Boaga, J., Cenni, N., Schmutz, M., Wu, Y. & Cassiani, G. (2020). Time-lapse monitoring of root water uptake using electrical resistivity tomography and mise-à-la-masse: a vineyard infiltration experiment. Soil. 6(1). 95-114.
 Porzuczek, J. (2019). Assessment of the Spatial Distribution of Moisture Content in Granular Material Using Electrical Impedance Tomography. Sensors. 19(12). 2807.
Russo, S., Nefti-Meziani, S., Carbonaro, N. & Tognetti, A. (2017). A quantitative evaluation of drive pattern selection for optimizing EIT-based stretchable sensors. Sensors. 17(9). 1999.
Salucci, M., Oliveri, G. & Massa, A. (2019). Real-time electrical impedance tomography of the human chest by means of a learning-by-examples method. IEEE Journal of Electromagnetics, RF and Microwaves in Medicine and Biology. 3(2). 88-96.
Sharifi, M. & Young, B. (2013). Towards an online milk concentration sensor using ERT: Correlation of conductivity, temperature and composition. Journal of Food Engineering. 116(1). 86-96.
 Silva, R., Faia, P. M., Garcia, F. A. P. & Rasteiro, M. G. (2016). Characterization of solid–liquid settling suspensions using Electrical Impedance Tomography: A comparison between numerical, experimental and visual information. Chemical Engineering Research and Design. 111. 223-242.
 Sun, J. & Yang, W. (2015). A dual-modality electrical tomography sensor for measurement of gas–oil–water stratified flows. Measurement. 66. 150-160.
 Thomas, A. J., Kim, J. J., Tallman, T. N. & Bakis, C. E. (2019). Damage detection in self-sensing composite tubes via electrical impedance tomography. Composites Part B: Engineering. 177. 107276.
 Wahab, Y. A., Rahim, R. A., Rahiman, M. H. F., Aw, S. R., Yunus, F. R. M., Goh, C. L. & Ling, L. P. (2015). Non-invasive process tomography in chemical mixtures–A review. Sensors and Actuators B: Chemical. 210. 602-617.
Wang, M. (2015). Industrial tomography. UK: Elsevier.
Wei, K., Qiu, C. H. & Primrose, K. (2016). Super-sensing technology: Industrial applications and future challenges of electrical tomography. Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences. 374(1). 201-218.
Weigand, M. & Kemna, A. (2019). Imaging and functional characterization of crop root systems using spectroscopic electrical impedance measurements. Plant and Soil. 435(1). 201-224.
 Xu, C., Dong, X., Shi, X., Fu, F., Shuai, W., Liu, R. & You, F. (2008). Comparison of drive patterns for single current source EIT in computational phantom. In: 2nd International Conference on Bioinformatics and Biomedical Engineering. pp. 1500-1503.
Zhang, L. & Wang, H. (2010). Single source current drive patterns for electrical impedance tomography. In: 2010 IEEE Instrumentation & Measurement Technology Conference Proceedings. pp. 1477-1480.
Zhao, X., Zhuang, H., Yoon, S. C., Dong, Y., Wang, W. & Zhao, W. (2017). Electrical impedance spectroscopy for quality assessment of meat and fish: A review on basic principles, measurement methods, and recent advances. Journal of Food Quality. 207. 637-653.
Iranian Journal of Biosystems Engineering
Volume 53, Issue 1
April 2022
Pages 77-90

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History

  • Receive Date: 15 October 2021
  • Revise Date: 16 February 2022
  • Accept Date: 07 March 2022

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