Electrodynamics Sensor for the Image Reconstruction Process in an Electrical Charge Tomography System
AbstractElectrical charge tomography (EChT) is a non-invasive imaging technique that is aimed to reconstruct the image of materials being conveyed based on data measured by an electrodynamics sensor installed around the pipe. Image reconstruction in electrical charge tomography is vital and has not been widely studied before. Three methods have been introduced before, namely the linear back projection method, the filtered back projection method and the least square method. These methods normally face ill-posed problems and their solutions are unstable and inaccurate. In order to ensure the stability and accuracy, a special solution should be applied to obtain a meaningful image reconstruction result. In this paper, a new image reconstruction method – Least squares with regularization (LSR) will be introduced to reconstruct the image of material in a gravity mode conveyor pipeline for electrical charge tomography. Numerical analysis results based on simulation data indicated that this algorithm efficiently overcomes the numerical instability. The results show that the accuracy of the reconstruction images obtained using the proposed algorithm was enhanced and similar to the image captured by a CCD Camera. As a result, an efficient method for electrical charge tomography image qreconstruction has been introduced. View Full-Text
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Rahmat, M.F.; Isa, M.D.; Rahim, R.A.; Hussin, T.A.R. Electrodynamics Sensor for the Image Reconstruction Process in an Electrical Charge Tomography System. Sensors 2009, 9, 10291-10308.
Rahmat MF, Isa MD, Rahim RA, Hussin TAR. Electrodynamics Sensor for the Image Reconstruction Process in an Electrical Charge Tomography System. Sensors. 2009; 9(12):10291-10308.Chicago/Turabian Style
Rahmat, Mohd Fua’ad; Isa, Mohd Daud; Rahim, Ruzairi Abdul; Hussin, Tengku Ahmad Raja. 2009. "Electrodynamics Sensor for the Image Reconstruction Process in an Electrical Charge Tomography System." Sensors 9, no. 12: 10291-10308.