A current spectrum-based algorithm for fault detection of electrical machines using low-power data acquisition devices
author
Asad, Bilal
Raja, Hadi Ashraf
Vaimann, Toomas
Kallaste, Ants
Pomarnacki, Raimondas
Hyunh, Van Khang
statement of authorship
Bilal Asad, Hadi Ashraf Raja, Toomas Vaimann, Ants Kallaste, Raimondas Pomarnacki and Van Khang Hyunh
source
Electronics
publisher
MDPI
journal volume number month
vol. 12, 7
year of publication
2023
pages
art. 1746
url
https://doi.org/10.3390/electronics12071746
subject term
elektrimasinad
tehisõpe
andmevalmendus
signaalitöötlus
tehisintellekt
lõplike elementide meetod
keyword
electrical machine
machine learning (ML)
data acquisition
finite element method (FEM)
signal processing
Arduino
artificial intelligence (AI)
ISSN
2079-9292
notes
Advanced fault detection, diagnosis and prognosis in a context of renewable power generation
Bibliogr.: 76 ref
Open Access
Open Access
scientific publication
teaduspublikatsioon
classifier
1.1
Scopus
https://www.scopus.com/sourceid/21100829272
https://www.scopus.com/record/display.uri?eid=2-s2.0-85152917029&origin=inward&txGid=5ab917f24786ab0f8c4172972c89df76
WOS
https://jcr.clarivate.com/jcr-jp/journal-profile?journal=ELECTRONICS-SWITZ&year=2023
https://www.webofscience.com/wos/woscc/full-record/WOS:000971825900001
category (general)
Engineering
Tehnika
Computer science
Arvutiteadus
category (sub)
Engineering. Control and systems engineering
Tehnika. Juhtimis- ja süsteemitehnika
Engineering. Electrical and electronic engineering
Tehnika. Elektri- ja elektroonikatehnika
Computer science. Computer networks and communications
Arvutiteadus. Arvutivõrgud ja side
Computer science. Hardware and architecture
Arvutiteadus. Riistvara ja arhitektuur
Computer science. Signal processing
Arvutiteadus. Signaalitöötlus
quartile
Q2
TalTech department
elektroenergeetika ja mehhatroonika instituut
language
inglise
Reserch Group
Electrical machines research group