A comparison of non-linear optimisation algorithms for recovering the conductivity depth profile of an electrically conductive block using eddy current inspection

This paper compares 15 different non-linear optimisation algorithms for reconstructing the depth profile of electrical conductivity for a conductive block of material using multi-frequency measurements from an eddy current probe. Synthetic data was generated using a finite element model, where the u...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:NDT & E international : independent nondestructive testing and evaluation Jg. 125; S. 102571
Hauptverfasser: Hampton, Joel, Fletcher, Adam, Tesfalem, Henok, Peyton, Anthony, Brown, Matthew
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Elsevier Ltd 01.01.2022
Schlagworte:
Depth profiling
Eddy currents
Electrical conductivity
Electromagnetic tomography
Inductance Spectroscopy
Inversion algorithm
Non-linear optimisation
Electrical conductivity
Inductance Spectroscopy
Electromagnetic tomography
Non-linear optimisation
Depth profiling
Eddy currents
Inversion algorithm
ISSN:0963-8695, 1879-1174
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
Beschreibung
Zusammenfassung:This paper compares 15 different non-linear optimisation algorithms for reconstructing the depth profile of electrical conductivity for a conductive block of material using multi-frequency measurements from an eddy current probe. Synthetic data was generated using a finite element model, where the underlying conductivity profile was randomly generated and smoothed, noise was then superimposed on the synthetic data. The compared algorithms were designed such that optimal performance was achieved for each algorithm by using the knowledge of the true underlying conductivity profile used to generate the synthetic data. The most competitive algorithm after ten iterations was determined to be dependent on the a priori estimate and level of noise, where the Broyden–Fletcher–Goldfarb–Shanno, augmented Levenberg-Marquardt and Levenberg-Marquardt are each top of different case studies. The augmented Levenberg-Marquardt and Levenberg-Marquardt were then employed on measured data, where the algorithms used a novel update procedure (in the nuclear graphite application) for the regularisation parameter. The study considers the conductivity profile of graphite blocks of the type used in the nuclear industry. [Display omitted]
ISSN:0963-8695
1879-1174
DOI:10.1016/j.ndteint.2021.102571