Computer Engineering and Applications ›› 2009, Vol. 45 ›› Issue (32): 19-21.DOI: 10.3778/j.issn.1002-8331.2009.32.006
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ZHANG Yan-jun,CHEN De-yun
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张彦俊,陈德运
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Abstract: Two-phase fluid has complex flow characteristic and the accurate identification of flow regime is the basis of the accurate measurement of two-phase flow’s parameter.There are still many defects such as low reconstruction quality and low reconstruction speed in image reconstruction algorithm because of soft field characteristic,strong nonlinear and ill-posedness of electrical resistance tomography.This paper puts forward a new image reconstruction algorithm for ERT based on algebraic neural network.This algorithm transforms image reconstruction into a problem of solving strictly diagonal-dominant linear equations.Through the simulation experiment analysis,this method has characteristics such as fast convergence,low cost and small error.
Key words: Electrical Resistance Tomography(ERT), two phase flow, image reconstruction algorithm, algebraic neural network
摘要: 两相流体具有复杂性的流动特性,图像重建的精度是两相流参数准确测量的基础。针对电阻层析成像系统存在的软场特性、强非线性和不适定性,使得重建的图像质量差、计算时间长等问题,基于代数运算的神经网络,给出了一种基于代数神经网络电阻层析成像图像重建算法。该算法通过建立代数神经网络,以测量的边界电压值作为神经网络的输入,将图像重建转变为一个严格对角占优的线性方程组的求解问题,以达到图像快速、准确的重建目的。通过实验仿真分析,该方法具有收敛速度快、代价低和误差小等特点。
关键词: 电阻层析成像, 两相流, 图像重建算法, 代数神经网络
CLC Number:
TP391.4
TP18
ZHANG Yan-jun,CHEN De-yun. Algebraic neural network image reconstruction algorithm for electrical resistance tomography[J]. Computer Engineering and Applications, 2009, 45(32): 19-21.
张彦俊,陈德运. 代数神经网络电阻层析成像图像重建算法[J]. 计算机工程与应用, 2009, 45(32): 19-21.
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URL: http://cea.ceaj.org/EN/10.3778/j.issn.1002-8331.2009.32.006
http://cea.ceaj.org/EN/Y2009/V45/I32/19