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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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article
A review of the classification of non-ferrous metals using magnetic induction for recycling
Abstract
Magnetic induction is widely used as a non-destructive technique to detect and classify metal objects over a range of applications. This paper applies magnetic induction spectroscopy (MIS) as a technique to classify non-ferrous metals within shredded metal waste streams on a moving conveyor. The magnetic response of the metal piece as it passes over the sensor is used to predict the metal, where the measured complex impedance components are used as features for the machine learning models. MIS performs well, even when surface contaminants are present, compared to other techniques that require the metal pieces to be cleaned; this saves time and reduces cost when large amounts of surface contamination are present in a waste stream, such as biomass incinerator metals. MIS allows for a lower cost system when compared to X-ray and sink-float methods with a high throughput, which makes it an economical approach.