Sensitivity analysis of inverse problems in EM non-destructive testing

被引:5
作者
Bilicz, Sandor [1 ]
机构
[1] Budapest Univ Technol & Econ, Dept Broadband Infocommun & Electromagnet Theory, H-1111 Egry, Hungary
关键词
polynomials; sensitivity analysis; eddy current testing; nondestructive testing; inverse problems; chaos; stochastic processes; Sobol indices; polynomial chaos expansion surrogate model; entire inversion scheme; eddy-current NdT; inverse problem; EM-NdT; electromagnetic nondestructive testing; material defect parameters; EM field measurements; reconstructed defect parameters; model-based inversion; EM simulation; computational complexity; configuration uncertainties; MODEL;
D O I
10.1049/iet-smt.2019.0370
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
The inverse problem of electromagnetic (EM) non-destructive testing (NdT) consists of reconstructing material defect parameters invoking EM field measurements. Uncertainties of the configuration (e.g. imprecise constitutive and geometrical parameters) are inevitably present; hence, the reconstructed defect parameters are also uncertain. In this study, the different sources of uncertainty are ranked by means of sensitivity analysis. The model-based inversion (involving EM simulation) is computationally demanding; moreover, sensitivity analysis usually requires a vast number of repeated runs of the inversion. To overcome the computational complexity, surrogate models are applied at different levels. Interpolation on a sparse grid is used as a surrogate model of the EM simulation. The sensitivity of the reconstructed defect parameters concerning configuration uncertainties is characterised by means of Sobol indices. The Sobol indices are obtained from a polynomial chaos expansion surrogate model of the entire inversion scheme. A numerical example drawn from eddy-current NdT is thoroughly analysed to illustrate the proposed methodology and to demonstrate its performance.
引用
收藏
页码:543 / 551
页数:9
相关论文
共 28 条
[1]  
Bellman R., 1961, Adaptive Control Processes: a Guided Tour, DOI [DOI 10.1515/9781400874668, 10.1515/9781400874668]
[2]   Low-Rank Approximations in Sensitivity Analysis Applied to Electromagnetic Nondestructive Evaluation [J].
Bilicz, Sandor ;
Bingler, Arnold .
ELECTROMAGNETIC NONDESTRUCTIVE EVALUATION XXII, 2019, 44 :62-67
[3]   Sparse Grid Surrogate Models for Electromagnetic Problems With Many Parameters [J].
Bilicz, Sandor .
IEEE TRANSACTIONS ON MAGNETICS, 2016, 52 (03)
[4]   Characterization of a 3D defect using the expected improvement algorithm [J].
Bilicz, Sandor ;
Vazquez, Emmanuel ;
Lambert, Marc ;
Gyimothy, Szabolcs ;
Pavo, Jozsef .
COMPEL-THE INTERNATIONAL JOURNAL FOR COMPUTATION AND MATHEMATICS IN ELECTRICAL AND ELECTRONIC ENGINEERING, 2009, 28 (04) :851-864
[5]  
Bingler A., 2018, STUDIES APPL ELECTRO, P152
[6]  
Blitz J., 1991, ELECT MAGNETIC METHO
[7]   Robust optimisation formulations for the design of an electric machine [J].
Bontinck, Zeger ;
Lass, Oliver ;
Schoeps, Sebastian ;
De Gersem, Herbert ;
Ulbrich, Stefan ;
Rain, Oliver .
IET SCIENCE MEASUREMENT & TECHNOLOGY, 2018, 12 (08) :939-948
[8]  
Bungartz HJ, 2004, ACT NUMERIC, V13, P147, DOI 10.1017/S0962492904000182
[9]   Metamodel-Based Nested Sampling for Model Selection in Eddy-Current Testing [J].
Cai, Caifang ;
Bilicz, Sandor ;
Rodet, Thomas ;
Lambert, Marc ;
Lesselier, Dominique .
IEEE TRANSACTIONS ON MAGNETICS, 2017, 53 (04)
[10]   Adaptive Metamodels for Crack Characterization in Eddy-Current Testing [J].
Douvenot, Remi ;
Lambert, Marc ;
Lesselier, Dominique .
IEEE TRANSACTIONS ON MAGNETICS, 2011, 47 (04) :746-755