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Effectiveness Analysis of Rolling Bearing Fault Detectors Based On Self-Organising Kohonen Neural Network – A Case Study of PMSM Drive

Kamila Jankowska

Kamila Jankowska

Department of Electrical Machines, Drives and Measurements, Wroclaw University of Science and TechnologyPoland
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Jankowska, Kamila
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Pawel Ewert

Pawel Ewert

Department of Electrical Machines, Drives and Measurements, Wroclaw University of Science and TechnologyPoland
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Ewert, Pawel
  
23 lug 2021
Effectiveness Analysis of Rolling Bearing Fault Detectors Based On Self-Organising Kohonen Neural Network – A Case Study of PMSM Drive's Cover Image
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Pubblicato online: 23 lug 2021
Pagine: 100 - 112
Ricevuto: 14 mag 2021
Accettato: 01 lug 2021
DOI: https://doi.org/10.2478/pead-2021-0008
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© 2021 Kamila Jankowska et al., published by Sciendo
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
Jankowska, Kamila
Department of Electrical Machines, Drives and Measurements, Wroclaw University of Science and TechnologyPoland
Ewert, Pawel
Department of Electrical Machines, Drives and Measurements, Wroclaw University of Science and TechnologyPoland
Lingua:
Inglese
Frequenza di pubblicazione:
1 volte all'anno
Argomenti della rivista:
Informatica, Intelligenza artificiale, Ingegneria, Elettrotecnica, Elettronica
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