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Toomas Vaimann
Toomas Vaimann
Research Professor at Tallinn University of Technology
Verified email at taltech.ee - Homepage
Title
Cited by
Cited by
Year
Trends and challenges in intelligent condition monitoring of electrical machines using machine learning
K Kudelina, T Vaimann, B Asad, A Rassõlkin, A Kallaste, G Demidova
Applied Sciences 11 (6), 2761, 2021
772021
A review of synchronous reluctance motor-drive advancements
H Heidari, A Rassõlkin, A Kallaste, T Vaimann, E Andriushchenko, ...
Sustainability 13 (2), 729, 2021
762021
Digital twin for propulsion drive of autonomous electric vehicle
A Rassõlkin, T Vaimann, A Kallaste, V Kuts
2019 IEEE 60th International Scientific Conference on Power and Electrical …, 2019
732019
Direct Liquid Cooling in Low-Power Electrical Machines–Proof-of-Concept
PM Lindh, I Petrov, RS Semken, M Niemelä, JJ Pyrhönen, L Aarniovuori, ...
IEEE Transactions on Energy Conversion, 2016
632016
A review on additive manufacturing possibilities for electrical machines
MU Naseer, A Kallaste, B Asad, T Vaimann, A Rassõlkin
Energies 14 (7), 1940, 2021
622021
Opportunities and challenges of utilizing additive manufacturing approaches in thermal management of electrical machines
PS Ghahfarokhi, A Podgornovs, A Kallaste, AJM Cardoso, A Belahcen, ...
Ieee Access 9, 36368-36381, 2021
562021
Broken rotor bar fault detection of the grid and inverter‐fed induction motor by effective attenuation of the fundamental component
B Asad, T Vaimann, A Belahcen, A Kallaste, A Rassõlkin, MN Iqbal
IET Electric Power Applications 13 (12), 2005-2014, 2019
562019
State of the art of additively manufactured electromagnetic materials for topology optimized electrical machines
H Tiismus, A Kallaste, T Vaimann, A Rassõlkin
Additive Manufacturing 55, 102778, 2022
542022
Induction machine fault detection using smartphone recorded audible noise
T Vaimann, J Sobra, A Belahcen, A Rassõlkin, M Rolak, A Kallaste
IET Science, Measurement & Technology 12 (4), 554-560, 2018
472018
Overview on digital twin for autonomous electrical vehicles propulsion drive system
M Ibrahim, A Rassõlkin, T Vaimann, A Kallaste
Sustainability 14 (2), 601, 2022
452022
Implementation of digital twins for electrical energy conversion systems in selected case studies
A Rassölkin, T Orosz, GL Demidova, V Kuts, V Rjabtšikov, T Vaimann, ...
Estonian Academy Publishers, 2021
452021
Lifecycle analysis of different motors from the standpoint of environmental impact
S Orlova, A Rassõlkin, A Kallaste, T Vaimann, A Belahcen
Latvian Journal of Physics and Technical Sciences 53 (6), 37-46, 2016
452016
AC magnetic loss reduction of SLM processed Fe-Si for additive manufacturing of electrical machines
H Tiismus, A Kallaste, A Belahcen, M Tarraste, T Vaimann, A Rassõlkin, ...
Energies 14 (5), 1241, 2021
422021
Hysteresis measurements and numerical losses segregation of additively manufactured silicon steel for 3D printing electrical machines
H Tiismus, A Kallaste, A Belahcen, T Vaimann, A Rassõlkin, D Lukichev
Applied Sciences 10 (18), 6515, 2020
422020
Magnetic properties of reduced Dy NdFeB permanent magnets and their usage in electrical machines
T Vaimann, A Kallaste, A Kilk, A Belahcen
2013 Africon, 1-5, 2013
402013
Challenges of additive manufacturing of electrical machines
H Tiismus, A Kallaste, A Belahcen, A Rassõlkin, T Vaimann
2019 IEEE 12th International Symposium on Diagnostics for Electrical …, 2019
362019
Additive design possibilities of electrical machines
A Kallaste, T Vaimann, A Rassãlkin
2018 IEEE 59th International Scientific Conference on Power and Electrical …, 2018
362018
Broken rotor bar fault diagnostic of inverter fed induction motor using FFT, Hilbert and Park's vector approach
B Asad, T Vaimann, A Belahcen, A Kallaste
2018 XIII International Conference on Electrical Machines (ICEM), 2352-2358, 2018
362018
Digital twin of an electrical motor based on empirical performance model
A Rassõlkin, V Rjabtšikov, T Vaimann, A Kallaste, V Kuts, A Partyshev
2020 XI International Conference on Electrical Power Drive Systems (ICEPDS), 1-4, 2020
352020
Modified winding function‐based model of squirrel cage induction motor for fault diagnostics
B Asad, T Vaimann, A Belahcen, A Kallaste, A Rassõlkin, MN Iqbal
IET Electric Power Applications 14 (9), 1722-1734, 2020
352020
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