Huang族校正电容层析成像图像重建算法

A Huang Clan Correction Image Reconstruction Algorithm For Electrical Capacitance Tomography System

针对电容层析成像(ECT)技术中的"软场"效应和病态问题,提出了一种Huang族校正的电容层析成像图像重建算法。首先依据ECT系统的基本原理,推导出ECT问题中Huang族校正的校正公式,其次给出校正后用于ECT反问题求解仿真实验的迭代公式。最后,采用数字仿真模拟实验方式,验证提出方法的有效性。实验结果表明,Huang族校正方法对于极低位、低位、核心流而言,图像误差分别降到24. 39%、25. 81%和40. 91%,均低于LBP、Landweber、SD和CG方法;对于极低位、低位及柱状流而言,迭代次数分别为12、12、27次,比Landweber算法和SD法都要低,综合分析,可知Huang族校正方法实验效果良好。

To solve the‘soft-field’nature and the ill-posed problem in electrical capacitance tomography technology,a Huang clan correction image reconstruction algorithm for electrical capacitance tomography is presented.Firstly,according to the basic principles of the Electrical Capacitance Tomography system,the formula of Huang clan correction in the problem of capacitance tomography is derived.Secondly,the iterative formula for simulation experiment is given after the correction.Finally,the validity of the proposed method is verified by digital simulation.The simulation experiment results show that the error of the image for extremely low layer flow,low layer flow and core flow dropped to 24.39%,25.81%and 40.91%respectively.Results were lower than Linear Back Projection method,Landweber method,Steepest Descent method and Conjugate Gradient method.In addition,the number of iterations were maintained at 12,12 and 27times,also less than the Landweber method and the Steepest Descent method.The results of the analysis show that the effect of the Huang Clan Correction Image Reconstruction Algorithm are good.