Depth sizing of partial-contact stress corrosion cracks from ECT signals

Cheng, Wei; Kanemoto, Shigeru; Kōmura, Ichirō; Shiwa, Mitsuharu

doi:10.1016/j.ndteint.2005.10.007

Cited by 24 publications

(7 citation statements)

References 5 publications

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“…Up to now, the sizing of SCC in key structural components is conducted using ultrasonic testing (UT) [5,6], eddy current testing (ECT), etc [7][8][9][10][11][12]. UT is the major NDT tool for SCC sizing in nuclear power plants.…”

Section: Introductionmentioning

confidence: 99%

Quantitative evaluation of electrical conductivity inside stress corrosion crack with electromagnetic NDE methods

Cai

Jomdecha

Zhao

et al. 2020

Phil. Trans. R. Soc. A.

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This paper presents a comparison of studies on the local distributed electrical conductivity in stress corrosion crack (SCC) from signals of eddy current testing (ECT) and direct current potential drop (DCPD) aiming to improve SCC sizing accuracy when using electromagnetic non-destructive testing (NDT) methods. Experimental setups of ECT and DCPD were established, respectively, to collect measurement signals due to artificial SCCs in a plate of austenitic stainless steel. The local conductivity in the SCC region was reconstructed from the feature parameters extracted from the measured ECT and DCPD signals through inverse analyses. The inversion strategies for ECT and DCPD, each including an efficient forward simulation and an optimization scheme, were introduced from the viewpoint of conductivity reconstruction. Inversion results obtained from the measured ECT and DCPD signals showed the consistent trend which proved the validity of the predicted electrical conductivity indirectly. It is clarified that the electrical conductivity in a SCC is relatively high at the crack tip area and may become as high as 17% of that of the base material. These results provide a good reference to enhance the sizing accuracy of SCC with an electromagnetic NDT method such as ECT by updating the conductive crack model based on the results of this work. This article is part of the theme issue ‘Advanced electromagnetic non-destructive evaluation and smart monitoring’.

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Section: Introductionmentioning

confidence: 99%

Quantitative evaluation of electrical conductivity inside stress corrosion crack with electromagnetic NDE methods

Cai

Jomdecha

Zhao

et al. 2020

Phil. Trans. R. Soc. A.

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“…However, in point of safety and economic efficiency assessment, there is not too much interest in electrical conductivity and magnetic permeability distributions. The defect dimensions (depth, length, width, and so on) are the main concerns [8]. In ECNDE, the dimensions of defects will be retrieved by inversion of the measured signals [9].…”

Section: Introductionmentioning

confidence: 99%

Eddy Current Inversion Models for Estimating Dimensions of Defects in Multilayered Structures

Dong

Qiu

et al. 2014

Mathematical Problems in Engineering

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In eddy current nondestructive evaluation, one of the principal challenges is to determine the dimensions of defects in multilayered structures from the measured signals. It is a typical inverse problem which is generally considered to be nonlinear and ill-posed. In the paper, two effective approaches have been proposed to estimate the defect dimensions. The first one is a partial least squares (PLS) regression method. The second one is a kernel partial least squares (KPLS) regression method. The experimental research is carried out. In experiments, the eddy current signals responding to magnetic field changes are detected by a giant magnetoresistive (GMR) sensor and preprocessed for noise elimination using a wavelet packet analysis (WPA) method. Then, the proposed two approaches are used to construct the inversion models of defect dimension estimation. Finally, the estimation results are analyzed. The performance comparison between the proposed two approaches and the artificial neural network (ANN) method is presented. The comparison results demonstrate the feasibility and validity of the proposed two methods. Between them, the KPLS regression method gives a better prediction performance than the PLS regression method at present.

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“…The estimation scheme is a hybrid scheme of the finite element and boundary element method; and H. Fukutomi [10] introduced a method for the identification algorithm of the crack profiles using edge based finite elements and the parameter estimation by the trust region method. Furthermore, Z. Chen et al and W. Chen et al [11,12] introduced an inversion scheme reconstructs crack profiles from eddy current signals, using fast forward solver and a first-order optimization algorithm.…”

Section: Introductionmentioning

confidence: 99%

Identification of Crack Profiles using Database and Greedy Search Inverse Analysis Arising in Eddy Current Testing

Nguyen

Kojima

2010

Transactions of ISCIE

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This paper is concerned with an optimization method to recover crack profiles from measurement signals obtained by eddy current testing. This inversion technique uses Greedy search algorithm to find the optimum of least-square error between measurement signals and simulation data. In creating simulation data, a database called ECT database is used. This database is constructed as a set of parameters-to-output mapping data, by using hybrid FEM-BEM simulator derived from Maxwell's equations. Numerical experimental results show the effectiveness and feasibility of this method.

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Depth sizing of partial-contact stress corrosion cracks from ECT signals

Cited by 24 publications

References 5 publications

Quantitative evaluation of electrical conductivity inside stress corrosion crack with electromagnetic NDE methods

Quantitative evaluation of electrical conductivity inside stress corrosion crack with electromagnetic NDE methods

Eddy Current Inversion Models for Estimating Dimensions of Defects in Multilayered Structures

Identification of Crack Profiles using Database and Greedy Search Inverse Analysis Arising in Eddy Current Testing

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