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Detection of Fault Electrode In EIT For Two-phase Flow

机译:两相流动EIT中故障电极的检测

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It is important to get reliable measurement data in Electrical impedance tomography (EIT) for getting satisfactory reconstruction result. Because EIT inverse problem is non-linear and ill-posed, incorrect data such as measured data through fault electrode can effect the estimation of resistivity distribution. So, EIT measurement system with methods for checking reliability has been developed. However, most existing methods require extra cost to evaluate reliability of EIT system. This paper presents modified Gauss-Newton (GN) method based on random sample consensus (RANSAC) algorithm for finding fault electrodes and getting good reconstructed image with faulty data for two-phase flow application. Also, suitable residual equation is proposed for determining the threshold to use RANSAC algorithm. Numerical simulations are performed to validate the performance of the proposed method. The results show that the proposed method has a good reconstruction performance compared to the conventional GN method.
机译:在电阻断层扫描(EIT)中获得可靠的测量数据,以获得令人满意的重建结果。由于EIT逆问题是非线性和不良的,因此通过故障电极的测量数据等不正确的数据可以实现电阻率分布的估计。因此,开发了具有用于检查可靠性方法的EIT测量系统。但是,大多数现有方法需要额外的成本来评估EIT系统的可靠性。本文介绍了基于随机采样共识(RANSAC)算法的改进的高斯 - 牛顿(GN)方法,用于查找故障电极,并为两相流应用有故障数据获得良好的重建图像。此外,提出了合适的剩余方程来确定使用RANSAC算法的阈值。执行数值模拟以验证所提出的方法的性能。结果表明,与传统的GN方法相比,该方法具有良好的重建性能。

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