Image Reconstruction Algorithm for Electrical Charge Tomography System

Abstract

Problem statement: Many problems in scientific computing can be formulated as inverse problem. A vast majority of these problems are ill-posed problems. In Electrical Charge Tomography (EChT), normally the sensitivity matrix generated from forward modeling is very ill-condition. This condition posts difficulties to the inverse problem solution especially in the accuracy and stability of the image being reconstructed. The objective of this study is to reconstruct the image cross-section of the material in pipeline gravity dropped mode conveyor as well to solve the ill-condition of matrix sensitivity. Approach: Least Square with Regularization (LSR) method had been introduced to reconstruct the image and the electrodynamics sensor was used to capture the data that installed around the pipe. Results: The images were validated using digital imaging technique and Singular Value Decomposition (SVD) method. The results showed that image reconstructed by this method produces a good promise in terms of accuracy and stability. Conclusion: This implied that LSR method provides good and promising result in terms of accuracy and stability of the image being reconstructed. As a result, an efficient method for electrical charge tomography image reconstruction has been introduced.

Determination of Concentration Profile for Flowing Solid Particles in Pipeline Using Electric Charge Tomography System

“…and coordinates of the th sensor, while and are the positive integers denoting sensors' and elements' numbers, respectively. Equations (9a)-(9d) were substituted into (8) and simplified to give (10). Equation 10is the expression for electric charges induced in the sensor due to the enclosed electrostatic charges in element of the domain.…”

“…However, the electrodynamic sensors are used to detect charges carried by the moving particles, such that, when the charged particles travel through the sensing area where the sensors are installed, an unpredictable electrostatic field is created by the charges on the particles, leading to induced charges on the sensors. Consequently, the flow parameters, such as velocity, mass flow rate, particle size, and concentration profile of the moving particles, can be obtained [7,8]. In the determination of the concentration profile of particles, tomographic technology is usually applied.…”

“…Several efforts have been made to improve the quality of the image as reported in [10,11] with no specific solution to the problem of particle distribution within the sensing zone. Concentration profile or the tomographic imaging is one of the inverse problems characterized by ill-posed and ill-conditioned phenomenon, where small changes in the data cause arbitrarily large changes in the solution making it unstable [8]. The purpose of this paper is to present an efficient method that produces a stable system by which concentration profile or tomography image of solid particles moving through a pipeline can be achieved.…”

Identification of Electrooculography Signals Frequency Energy Distribution Using Wavelet Algorithm

“…Experimental setup: This system setting includes the EEG Data Acquisition System (DAS) Rahmat et al (2010); Neuronal 9200 software ( Fig. 1-2) with EOG electrodes set ( Fig.…”

Wavelet Analysis and Orthogonal Moments based Classification of Microcalcification in Digital Mammograms

“…The watermarking algorithm which combines both merits of the algorithm based on Discrete Cosine Transform (DCT) and algorithm based on Singular Value Decomposition (SVD). An efficient method for electrical charge tomography image reconstruction has been introduced by Brahmat et al (2010).…”