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    8-Electrode data collection system for electrical capacitance tomography
    (2006-12-01)
    Rerkratn, Apinai
    ;
    Lertpakdee, Thanakorn
    ;
    Chitsakul, Kitiphol
    ;
    Sangworasil, Manas
    ;
    Petchmaneelumka, Wandee
    8-electrode data collection system for electrical capacitance tomography is presented. The system mainly consists of a signal generator, 8×2 multiplexer, detector, amplifier, band-pass filter, rms-to-dc converter, A/D converter circuit and control computer. Experimental results with a circular sensor show that the proposed system is able to collect data with satisfy sensitivities, linearity, resolution and also being insensitive to noise. Reconstructed images from collected data are shown. © 2006 ICASE.
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    Electrical capacitance tomography system for industrial applications
    (2006-12-01)
    Rerkratn, Apinai
    ;
    Yossontiku, Chanrit
    ;
    Lertpakdee, Thanakorn
    ;
    Chitsakul, Kitiphol
    ;
    Sangworasil, Manas
    An electrical capacitance tomography system (ECT) has been developed. The system consists of a circular sensor with 8 electrodes. A charge generator injects charges into the sensor filled with objects different dielectric constants. The charges, in the form of potential dropped, on another electrode are measured and acquired digitally to a PC for calculating the capacitance and estimating the dielectric distribution. Linear back-projection algorithm (LBP) with iterations is applied for reconstructing cross sectional images of the sensor. Some experiments as the sensor filled with vegetable oil and a Teflon bar placed on a specified area was carried on. We have found that the minimum and maximum capacitance between the electrode pairs is about 0.1245 pF and 2.6760 pF respectively. These very low capacitance values suggested that the measuring circuit being implemented should have high sensitivity and also be insensitive to noise. The reconstructed images of the object closely resemble the cross-section of the specific test phantom. The low gray level artifacts, however often present in the reconstructed image because of the limitation of the LBP algorithm. This may be improved by using image thresholding or using suitable number of iterations.