Inverse Transformation in Eddy Current Tomography with Continuous Optimization of Reference Defect Parameters.

Paweł Nowak,Anna Ostaszewska-Liżewska,Roman Szewczyk

doi:10.3390/ma14174778

Abstract

This paper presents a methodology of inverse tomography transformation in eddy current tomography with the use of continuous optimization of reference defect parameters. Ferromagnetic steel samples with rectangular air inclusion defects of known dimensions were prepared and measured using an eddy current tomography setup. FEM-based (Finite Element Method based) forward tomography transformation was developed and utilized in inverse tomography transformation. The presented method of inverse tomography transformation is based on the continuous optimization of parameters that can describe the sample, such as the diameter and dimensions of the reference defect. The obtained results of inverse tomography transformation were in high accordance with the real parameters of the samples. Additionally, the presented method had acceptable repeatability. The obtained values of the sample parameters fit within the range of expanded uncertainty when compared to the real parameters of the sample.

Highlights

IntroductionEddy current tomography (or magnetic induction tomography) is a non-destructive, contactless method for evaluating discontinuities in a conductive material [1]
The reference defect parameters obtained by inverse tomography transformation provide satisfactory compliance with the real parameters
Proposed method, the parameters the object model are optimized with the270 continuous optimization

Summary

Introduction

Eddy current tomography (or magnetic induction tomography) is a non-destructive, contactless method for evaluating discontinuities in a conductive material [1]. It is based on the standard eddy current non-destructive evaluation method [2,3,4,5], where the tested object influences the coupling of at least two coils. The parameters of the measurand are the signal amplitude and phase shift with respect to the excitation signal. The variation of these parameters is an implicit function, the value of which varies on the signal frequency, the electromagnetic properties of the tested material, and its spatial distribution in the tomograph region of interest

Results

Discussion

Conclusion