Fast Signal Predictions of Noised Signals in Eddy Current Testing.

Huang, Haoyu; Fukutomi, Hisayuki; Takagi, Toshiyuki

doi:10.1299/kikaia.65.2024

Cited by 5 publications

(7 citation statements)

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“…The sensitivity formula has been derived earlier from the general form of Maxwell's equations and for the special case of inverse eddy-current problem of MIT [14], [16]. A sensitivity formula that reflects the high conductivity changes has been used for eddy-current NDT (see for example [4]).…”

Section: Sensitivity Analysismentioning

confidence: 99%

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A three-dimensional inverse finite-element method applied to experimental eddy-current imaging data

et al. 2006

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Eddy-current techniques can be used to create electrical conductivity mapping of an object. The eddy-current imaging system in this paper is a magnetic induction tomography (MIT) system. MIT images the electrical conductivity of the target based on impedance measurements from pairs of excitation and detection coils. The inverse problem here is ill-posed and nonlinear. Current state-of-the-art image reconstruction methods in MIT are generally based on linear algorithms. In this paper, a regularized Gauss-Newton scheme has been implemented based on an edge finite-element forward solver and an efficient formula for the Jacobian matrix. Applications of Tikhonov and total variation regularization have been studied. Results are presented from experimental data collected from a newly developed MIT system. The paper also presents further progress in using an MIT system for molten metal flow visualization in continuous casting by applying the proposed algorithm in a real experiment in a continuous casting pilot plant of Corus RD&T, Teesside Technology Centre.

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Section: Sensitivity Analysismentioning

confidence: 99%

“…M AGNETIC INDUCTION TOMOGRAPHY (MIT) is a new modality for medical, industrial, and geophysical imaging [1]- [3]. The problem of MIT image reconstruction is similar to the inverse eddy-current problem of nondestructive testing (NDT) [4]- [7]. The measurement data are the mutual inductances between pairs of coils.…”

Section: Introductionmentioning

confidence: 99%

A three-dimensional inverse finite-element method applied to experimental eddy-current imaging data

et al. 2006

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“…For each driven coil the forward problem must be solved for a perturbation in each unknown parameter used in modeling the unknown region. With the A, A-V formulation and using the edge FEM, the sensitivity to a change in the conductivity of the conducting region can be calculated using an adjoint field method as derived in this paper and discussed in [6], [8], [12] where the integral becomes the inner product of E fields and the Jacobian can be calculated by performing this integration for a chosen basis for the conductivity perturbation δσ. Using the shape function of edge elements {N e } and nodal elements of L e , the electric field E in each point inside each element can be expressed as follows…”

Section: Sensitivity Analysismentioning

confidence: 99%

“…A mathematically similar problem (forward and inverse eddy current problem) has been studied extensively for Non-Destructive Testing (NDT) applications. Forward problem formulations, approaches to sensitivity analysis and inverse problem techniques have been developed for NDT by [8], [16], [22], [34]. Because of the differences in conductivity range and contrast in medical MIT, many of those techniques used in NDT may not be directly applicable here.…”

Section: Introductionmentioning

confidence: 99%

Absolute Conductivity Reconstruction in Magnetic Induction Tomography Using a Nonlinear Method

Soleimani

Lionheart

2006

IEEE Trans. Med. Imaging

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Magnetic Induction Tomography attempts to image the electrical and magnetic characteristics of a target using impedance measurement data from pairs of excitation and detection coils. This inverse eddy current problem is nonlinear and also severely ill posed so regularization is required for a stable solution. A regularized Gauss-Newton algorithm has been implemented as a nonlinear, iterative inverse solver. In this algorithm one needs to solve the forward problem and recalculate the Jacobian matrix for each iteration. The forward problem has been solved using an edge based finite element method for magnetic vector potential A and electrical scalar potential V , a so called A, A-V formulation. A theoretical study of the general inverse eddy current problem and a derivation, paying special attention to the boundary conditions, of an adjoint field formula for the Jacobian is given. This efficient formula calculates the change in measured induced voltage due to a small perturbation of the conductivity in a region. This has the advantage that it involves only the inner product of the electric fields when two different coils are excited, and these are convenient computationally. This paper also shows that the sensitivity maps change significantly when the conductivity distribution changes, demonstrating the necessity for a nonlinear reconstruction algorithm. The performance of the inverse solver has been examined and results presented from simulated data with added noise.

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“…An overview of techniques for non destructive evaluations using eddy currents can be found in [7] and we also refer to [23], [20] and [26] for further engineering considerations. For other model based inversion methods related to eddy-currents we may refer, without being exhaustive, to [8,17,16,25,6]. In the medical context, several inverse source problems related to eddy-current models have been addressed: non-invasive applications for electroencephalography, magnetoencephalography [3] (see also [1]) and magnetic induction tomography [12,21].…”

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confidence: 99%

A Robust Inversion Method for Quantitative 3D Shape Reconstruction from Coaxial Eddy Current Measurements

2016

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Abstract. This work is motivated by the monitoring of conductive clogging deposits in steam generator at the level of support plates. One would like to use monoaxial coils measurements to obtain estimates on the clogging volume. We propose a 3D shape optimization technique based on simplified parametrization of the geometry adapted to the measurement nature and resolution. The direct problem is modeled by the eddy current approximation of time-harmonic Maxwell's equations in the low frequency regime. A potential formulation is adopted in order to easily handle the complex topology of the industrial problem setting. We first characterize the shape derivatives of the deposit impedance signal using an adjoint field technique. For the inversion procedure, the direct and adjoint problems have to be solved for each coil vertical position which is excessively time and memory consuming. To overcome this difficulty, we propose and discuss a steepest descent method based on a fixed and invariant triangulation. Numerical experiments are presented to illustrate the convergence and the efficiency of the method.

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Fast Signal Predictions of Noised Signals in Eddy Current Testing.

Cited by 5 publications

References 0 publications

A three-dimensional inverse finite-element method applied to experimental eddy-current imaging data

A three-dimensional inverse finite-element method applied to experimental eddy-current imaging data

Absolute Conductivity Reconstruction in Magnetic Induction Tomography Using a Nonlinear Method

A Robust Inversion Method for Quantitative 3D Shape Reconstruction from Coaxial Eddy Current Measurements

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