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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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Vaimann, Toomas
Tallinn University of Technology
in Cooperation with on an Cooperation-Score of 37%
Topics
Publications (10/10 displayed)
- 2024Electrical and Thermal Anisotropy in Additively Manufactured AlSi10Mg and Fe-Si Samplescitations
- 2021Sliding Mean Value Subtraction-Based DC Drift Correction of B-H Curve for 3D-Printed Magnetic Materialscitations
- 2021Optimal Control of Automatic Manipulator for Elimination of Galvanic Line Load Oscillationcitations
- 2021Additive Manufacturing of Prototype Axial Flux Switched Reluctance Electrical Machinecitations
- 2020Hysteresis loss evaluation of additively manufactured soft magnetic corecitations
- 2020Hysteresis measurements and numerical losses segregation of additively manufactured silicon steel for 3D printing electrical machinescitations
- 2019Electrical resistivity of additively manufactured silicon steel for electrical machine fabricationcitations
- 2019Axial Synchronous Magnetic Coupling Modeling and Printing with Selective Laser Meltingcitations
- 2019Challenges of Additive Manufacturing of Electrical Machinescitations
- 2015Implementation of Different Magnetic Materials in Outer Rotor PM Generator
Places of action
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article
Sliding Mean Value Subtraction-Based DC Drift Correction of B-H Curve for 3D-Printed Magnetic Materials
Abstract
This paper presents an algorithm to remove the DC drift from the B-H curve of an additively manufactured soft ferromagnetic material. The removal of DC drift from the magnetization curve is crucial for the accurate estimation of iron losses. The algorithm is based on the sliding mean value subtraction from each cycle of calculated magnetic flux density (B) signal. The sliding mean values (SMVs) are calculated using the convolution theorem, where a DC kernel with a length equal to the size of one cycle is convolved with B to recover the drifting signal. The results are based on the toroid measurements made by selective laser melting (SLM)-based 3D printing mechanism. The measurements taken at different flux density values show the effectiveness of the method. ; Peer reviewed