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State-of-the-Art techniques for fault diagnosis in electrical machines: Advancements and future directions

author
Akbar, Siddique
Vaimann, Toomas
Asad, Bilal
Kallaste, Ants
Sardar, Muhammad Usman
Kudelina, Karolina
statement of authorship
Siddique Akbar, Toomas Vaimann, Bilal Asad, Ants Kallaste, Muhammad Usman Sardar and Karolina Kudelina
source
Energies
publisher
MDPI
journal volume number month
Vol. 16, 17
year of publication
2023
pages
Art. 6345
url
https://doi.org/10.3390/en16176345
subject term
elektrimasinad
diagnostika (tehnika)
vead
tehisintellekt
keyword
electrical machines
condition monitoring
fault diagnosis
artificial intelligence (AI)
conventional techniques
ISSN
1996-1073
notes
Special Issue: Novel Approaches to Electrical Machine Fault Diagnosis: Volume II
Bibliogr.: 270 ref
Open Access
Open Access
scientific publication
teaduspublikatsioon
classifier
1.1
Scopus
Journal metrics at Scopus
Article at Scopus
WOS
Journal metrics at WOS
Article at WOS
category (general)
Mathematics
Engineering
Energy
category (sub)
Mathematics. Control and optimization
Engineering. Engineering (miscellaneous)
Engineering. Electrical and electronic engineering
Energy. Energy engineering and power technology
Energy. Fuel technology
Energy. Energy (miscellaneous)
Energy. Renewable energy, sustainability and the environment
kvartiil
Q2
TTÜ department
elektroenergeetika ja mehhatroonika instituut
language
inglise
Uurimisrühm
Electrical machines research group
Akbar, S., Vaimann, T., Asad, B., Kallaste, A., Sardar, M. U., Kudelina, K. State-of-the-Art techniques for fault diagnosis in electrical machines: Advancements and future directions // Energies (2023) Vol. 16, 17, Art. 6345. https://doi.org/10.3390/en16176345