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Naji, M. |
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Motta, Antonella |
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Aletan, Dirar |
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Mohamed, Tarek |
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Ertürk, Emre |
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Taccardi, Nicola |
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Kononenko, Denys |
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Petrov, R. H. | Madrid |
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Alshaaer, Mazen | Brussels |
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Bih, L. |
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Casati, R. |
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Muller, Hermance |
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Kočí, Jan | Prague |
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Šuljagić, Marija |
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Kalteremidou, Kalliopi-Artemi | Brussels |
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Azam, Siraj |
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Ospanova, Alyiya |
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Blanpain, Bart |
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Ali, M. A. |
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Popa, V. |
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Rančić, M. |
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Ollier, Nadège |
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Azevedo, Nuno Monteiro |
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Landes, Michael |
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Rignanese, Gian-Marco |
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Peyton, Antony J.
in Cooperation with on an Cooperation-Score of 37%
Topics
Publications (19/19 displayed)
- 2024Classification of Wrought and Cast Aluminium using Magnetic Induction Spectroscopy and Machine Vision
- 2023Computations and measurements of the magnetic polarizability tensor characterisation of highly conducting and magnetic objectscitations
- 2023A review of the classification of non-ferrous metals using magnetic induction for recyclingcitations
- 2023Scrap metal classification using magnetic induction spectroscopy and machine visioncitations
- 2019Classification of Non-ferrous Scrap Metal using Two Component Magnetic Induction Spectroscopy
- 2019Magnetic characterisation of grain size and precipitate distribution by major and minor BH loop measurementscitations
- 2017Classification of Non-ferrous Metals using Magnetic Induction Spectroscopycitations
- 2017Detection of creep degradation during pressure vessel testing using electromagnetic sensor technologycitations
- 2017Optimized setup and protocol for magnetic domain imaging with in Situ hysteresis measurementcitations
- 2017Electromagnetic tensor spectroscopy for sorting of shredded metallic scrapcitations
- 2017Selective recovery of metallic scraps using electromagnetic tensor spectroscopy
- 2016Defect representation using the electromagnetic tensor formulation for eddy current NDT
- 2015Electromagnetic evaluation of the microstructure of grade 91 tubes/pipescitations
- 2015Rapid Non-Contact Relative Permittivity Measurement of Fruits and Vegetables using Magnetic Induction Spectroscopycitations
- 2014Differential permeability behaviour of P9 and T22 power station Steelscitations
- 2013Magnetic sensing for microstructural assessment of power station steels: Differential permeability and magnetic hysteresiscitations
- 2006Electromagnetic visualisation of steel flow in continuous casting nozzlescitations
- 2006A three-dimensional inverse finite-element method applied to experimental eddy-current imaging datacitations
- 2003Development of a sensor for visualization of steel flow in the continuous casting nozzlecitations
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document
Defect representation using the electromagnetic tensor formulation for eddy current NDT
Abstract
<p>A difficulty for eddy current inspection is in the interpretation of data from either individual detectors or arrays. For individual detectors, it is common to monitor signal variations in the impedance plane and then detect signal variations outside a pre-defined envelope. For eddy current arrays (ECA), the data is often displayed as an image as the array is passed over the test piece. The image often has a qualitative grey / colour scale selected to emphasise anomalies caused by defects. Quantitative information such as crack sizing is often either based on calibrations of empirical responses from test pieces or relationships derived from much simplified analytic models. Quantitative eddy current inspection relies on an accurate model of the sensor system. This requires a solution to the full 3D eddy current problem describing the particular application. Unfortunately, standard techniques to solve eddy current problems, such as the finite element method (FEM) or boundary element method (BEM) or the method of auxiliary sources (MAS) are numerically intensive; and therefore, are typically used for off-line studies. This research aims to improve modelling techniques for eddy current inspection and inversion, and illustrate a different approach to modelling which is highly computationally efficient. This is achieved by representing the defect by its eddy current signature in the form of an equivalent tensor (a 3 by 3 matrix representing the X Y Z responses of the defect to each of the X Y Z components of the applied field) allowing the sensor response to be determined on-line with relatively modest computing hardware. These results will be used as a basis for the further development of an eddy current inspection system which can supply online quantitative information about defect depth and orientation using real time tensor calculations.</p>