scholarly journals A Simultaneous and Continuous Excitation Method for High-Speed Electrical Impedance Tomography with Reduced Transients and Noise Sensitivity

Sensors ◽  
2018 ◽  
Vol 18 (4) ◽  
pp. 1013 ◽  
Author(s):  
Antoine Dupré ◽  
Saba Mylvaganam
Sensors ◽  
2019 ◽  
Vol 19 (17) ◽  
pp. 3679 ◽  
Author(s):  
Mathieu Darnajou ◽  
Antoine Dupré ◽  
Chunhui Dang ◽  
Guillaume Ricciardi ◽  
Salah Bourennane ◽  
...  

The investigation of quickly-evolving flow patterns in high-pressure and high-temperature flow rigs requires the use of a high-speed and non-intrusive imaging technique. Electrical Impedance Tomography (EIT) allows reconstructing the admittivity distribution characterizing a flow from the knowledge of currents and voltages on its periphery. The need for images at high frame rates leads to the strategy of simultaneous multi-frequency voltage excitations and simultaneous current measurements, which are discriminated using fast Fourier transforms. The present study introduces the theory for a 16-electrode simultaneous EIT system, which is then built based on a field programmable gate array data acquisition system. An analysis of the propagation of uncertainties through the measurement process is investigated, and experimental results with fifteen simultaneous signals are presented. It is shown that the signals are successfully retrieved experimentally at a rate of 1953 frames per second. The associated signal-to-noise ratio varies from 59.6–69.1 dB, depending on the generated frequency. These preliminary results confirm the relevance and the feasibility of simultaneous multi-frequency excitations and measurements in EIT as a means to significantly increase the imaging rate.


Author(s):  
Tomasz Rymarczyk ◽  
Edward Kozłowski ◽  
Paweł Tchórzewski ◽  
Grzegorz Kłosowski ◽  
Przemysław Adamkiewicz

The article presents machine learning methods in the field of reconstruction of tomographic images. The presented research results show that electric tomography makes it possible to analyze objects without interfering with them. The work focused mainly on electrical impedance tomography and image reconstruction using deterministic methods and machine learning, reconstruction results were compared and various numerical models were used. The main advantage of the presented solution is the ability to analyze spatial data and high speed of processing. The implemented algorithm based on logistic regression is promising in image reconstruction. In addition, the elastic net method was used to solve the problem of selecting input variables in the regression model.


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