AECVT sensors with reconfigurable capabilities for industrial imaging applications

Different synthetic electrode configurations are investigated for use in adaptive electrical capacitance volume tomography (AECVT). We evaluate in particular the spectrum of singular values of the sensitivity matrix as a function of the set of activated electrode to seek optimal arrangements that maximize the information content provided by a fixed number of measurement acquisitions (or acquisition speed). We also briefly discuss the impact of these factors on the resolution of the reconstructed images. Since field singularities near the sensing electrodes exacerbate the ill-conditioning of the reconstruction problem as number of measurements increases, spectral methods based on singular value decomposition (SVD) can be used as a means of regularization of the problem. The use of spectral analysis of the sensitivity matrix SVD is also suggested to provide design rules for the choice of optimal excitation strategies in AECVT.

[1]  Fernando L. Teixeira,et al.  Dual imaging modality of granular flow based on ECT sensors , 2008 .

[2]  F. Teixeira,et al.  Applications of capacitance tomography in gas–solid fluidized bed systems , 2015 .

[3]  F. Teixeira,et al.  Sensitivity matrix calculation for fast 3-D electrical capacitance tomography (ECT) of flow systems , 2004, IEEE Transactions on Magnetics.

[4]  William R B Lionheart,et al.  Reconstruction Algorithms for Permittivity and Conductivity Imaging , 2001 .

[5]  F. Teixeira,et al.  A nonlinear image reconstruction technique for ECT using a combined neural network approach , 2006 .

[6]  F. L. Teixeira,et al.  Bayesian compressive sensing for ultrawideband inverse scattering in random media , 2013, 1401.1092.

[7]  Daniel J. Holland,et al.  Fast and robust 3D electrical capacitance tomography , 2013 .

[8]  Fernando L. Teixeira,et al.  Electrical Capacitance Volume Tomography: a Comparison Between 12- and 24-Channels Sensor Systems , 2015 .

[9]  Maurice Beck,et al.  Design of sensor electronics for electrical capacitance tomography , 1992 .

[10]  Fernando L. Teixeira,et al.  Space–Frequency Ultrawideband Time-Reversal Imaging , 2008, IEEE Transactions on Geoscience and Remote Sensing.

[11]  Wuqiang Yang,et al.  New AC-based capacitance tomography system , 1999 .

[12]  D Chaffer,et al.  New system. , 1997, Nursing standard (Royal College of Nursing (Great Britain) : 1987).

[13]  Liang-Shih Fan,et al.  Electrical capacitance tomography , 2015 .

[14]  Liang-Shih Fan,et al.  A Multimodal Tomography System Based on ECT Sensors , 2007, IEEE Sensors Journal.

[15]  Lynn F. Gladden,et al.  Comparison of ECVT and MR Measurements of Voidage in a Gas-Fluidized Bed , 2009 .

[16]  Q. Marashdeh,et al.  Nonlinear forward problem solution for electrical capacitance tomography using feed-forward neural network , 2006, IEEE Sensors Journal.

[17]  M. E. Yavuz,et al.  Full time-domain DORT for ultrawideband electromagnetic fields in dispersive, random inhomogeneous media , 2006, IEEE Transactions on Antennas and Propagation.

[18]  Fernando L. Teixeira,et al.  Sensitivity map computation in adaptive electrical capacitance volume tomography with multielectrode excitations , 2015 .

[19]  Fernando L. Teixeira,et al.  Adaptive Electrical Capacitance Volume Tomography , 2014, IEEE Sensors Journal.

[20]  Stephan Mohr,et al.  Miniature electrical tomography for Micro-fluidic systems , 2010 .