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Detection of fault electrode in EIT for two-phase flow

机译:EIT中两相流故障电极的检测

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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:为了获得令人满意的重建结果,在电阻抗断层扫描(EIT)中获取可靠的测量数据很重要。由于EIT反问题是非线性且不适定的,因此错误数据(例如通过故障电极的测量数据)可能会影响电阻率分布的估算。因此,已经开发了具有用于检查可靠性的方法的EIT测量系统。然而,大多数现有方法需要额外的成本来评估EIT系统的可靠性。提出了一种基于随机样本一致性(RANSAC)算法的改进高斯牛顿法(GN),用于寻找故障电极并获得具有故障数据的良好重建图像,用于两相流应用。此外,提出了适合的残差方程式,用于确定使用RANSAC算法的阈值。进行数值模拟以验证所提出方法的性能。结果表明,与常规的GN方法相比,该方法具有良好的重构性能。

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