Custom Simplified Machine Learning Algorithms for Fault Diagnosis in Electrical Machines
No Thumbnail Available
Access rights
openAccess
acceptedVersion
URL
Journal Title
Journal ISSN
Volume Title
A4 Artikkeli konferenssijulkaisussa
This publication is imported from Aalto University research portal.
View publication in the Research portal (opens in new window)
View/Open full text file from the Research portal (opens in new window)
Other link related to publication (opens in new window)
View publication in the Research portal (opens in new window)
View/Open full text file from the Research portal (opens in new window)
Other link related to publication (opens in new window)
Date
2022
Major/Subject
Mcode
Degree programme
Language
en
Pages
4
Series
Diagnostika 2022 - 2022 International Conference on Diagnostics in Electrical Engineering, Proceedings, Diagnostika
Abstract
With advancements in science, machine learning and artificial intelligence integration with different fields have opened up new horizons. In this paper, some simplified custom machine learning algorithms are defined to train different faults for electrical machines. The industry has been moving towards predictive maintenance of machines rather than scheduled maintenance with the new industry 4.0 revolution. It has also paved the way for researchers to explore more in machine learning and have specific machine learning training algorithms catered to diagnose faults in electrical machines. Here, three different variations of a simplified machine learning algorithm are present for the training of faults of electrical machines. A comparison of the results is presented at the end, along with further studies carried out in this area.Description
Publisher Copyright: © 2022 IEEE.
Keywords
artificial intelligence, machine learning, neural network
Other note
Citation
Raja, H A, Asad, B, Vaimann, T, Kallaste, A, Rassolkin, A & Belahcen, A 2022, Custom Simplified Machine Learning Algorithms for Fault Diagnosis in Electrical Machines . in P Trnka (ed.), Diagnostika 2022 - 2022 International Conference on Diagnostics in Electrical Engineering, Proceedings . Diagnostika, IEEE, International Conference on Diagnostics in Electrical Engineering, Pilsen, Czech Republic, 06/09/2022 . https://doi.org/10.1109/Diagnostika55131.2022.9905174