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Image Reconstruction Algorithm for Electrical Charge Tomography System

机译:电荷层析成像系统的图像重建算法

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摘要

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.
机译:问题陈述:科学计算中的许多问题可以表述为反问题。这些问题绝大多数是不适定的问题。在电荷断层扫描(EChT)中,通常由正向建模生成的灵敏度矩阵非常恶劣。这种情况给反问题解决方案带来了困难,特别是在重构图像的准确性和稳定性方面。这项研究的目的是在管道重力下降模式输送机中重建材料的图像横截面,并解决矩阵灵敏度的问题。方法:引入了带有正则化的最小二乘(LSR)方法来重建图像,并使用电动力学传感器来捕获安装在管道周围的数据。结果:使用数字成像技术和奇异值分解(SVD)方法验证了图像。结果表明,该方法重建的图像在准确性和稳定性方面都具有良好的前景。结论:这暗示着LSR方法在重建图像的准确性和稳定性方面提供了良好而有希望的结果。结果,已经引入了用于电荷断层摄影图像重建的有效方法。

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  • 来源
    《American journal of applied sciences 》 |2010年第9期| p.1254-1263| 共10页
  • 作者单位

    Department of Control and Instrumentation Engineering, Faculty of Electrical Engineering,University Technology Malaysia, 81310 Skudai, Johor Bahru, Johor, Malaysia;

    Department of Electrical Engineering, Politeknik Kota Bharu, Kok Lanas,16450 Ketereh, Kota Bharu Kelantan, Malaysia;

    Faculty of Forestry, University Putra Malaysia, 43400 Serdang, Selangor, Malaysia;

    Department of General Studies, Politeknik Kota Bharu,Kok Lanas, 16450 Ketereh, Kota Bharu Kelantan, Malaysia;

    Department of Control, Instrumentation and Automation, Faculty of Electrical Engineering,University Technical Malaysia Melaka, 76109 Durian Tunggal, Melaka, Malaysia;

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  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    tomography system; inverse problem; image reconstruction; least square with regularization;

    机译:断层扫描系统;反问题影像重建;带正则化的最小二乘;

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