Abstract
Electrical charge tomography (EChT) is a non-invasive imaging technique that is aimed to reconstruct the image ofmaterial being conveyed based on data measured by electrodynamics sensor installed around the pipe. The method toensure the stability and accuracy of the image reconstruction should be applied to obtain a meaningful imagereconstruction results. In this paper, Least square with regularization (LSR) method was introduced to reconstruct thecross-section image of material in gravity mode conveyor pipeline. Numerical analysis result based on data measuredby sensor indicates that the algorithm is efficient to overcome the numerical instability. Instead of image reconstructionprocess, validation of the images is very important. It would be parts of verification process to the new imagereconstruction method. In this system, digital imaging technique was used to interrogate the flow in pipeline aroundsensing area using CCD camera. It was found out that there is a good match between LSR method of imagereconstruction and image capture by CCD camera due to the similarity of both images. This study implies that LSRmethod produced images that are stable and accurate as well as applicable for industrial use. It is suggested that anothervalidation process should be conducted using duty ratio, signal to noise ration and structure correlation to validate thequality of image produced by LSR method.
Highlights
Electrical charge tomography (EChT) is a non-invasive imaging technique that is aimed to reconstruct the image of material being conveyed in pipeline
This section focuses on the digital image processing from the video data captured by CCD camera and image reconstruction processes based on linear back projection (LBP), filter back projection (FBP) and Least square with regularization (LSR) methods
Based on the data measured by the electrodynamics sensor, image reconstruction is performed using the LBP, FBP and LSR methods
Summary
Electrical charge tomography (EChT) is a non-invasive imaging technique that is aimed to reconstruct the image of material being conveyed in pipeline. Many image reconstruction techniques have been extensively developed over the last two decades as reliable tools for electrical tomography. Examples are system linear back projection (Dyakowski, et al, 1997), filter back projection (Isa et al, 2008), singular value decomposition (SVD) (Hua, et al 2004). There are numbers of work been done applying electrostatic charge carried by particles in solid/powder conveyor pipeline to tomographic imaging, only three methods were introduced - namely linear back projection (LBP), filter back projection (FBP) and least square method (Bidin et al, 1995; Machida et al 200; Green et al.,1997)
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