print

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
Journal metrics at Scopus
Article at Scopus
WOS
Journal metrics at WOS
Article at WOS
category (general)
Engineering
Computer science
category (sub)
Engineering. Control and systems engineering
Engineering. Electrical and electronic engineering
Computer science. Computer networks and communications
Computer science. Hardware and architecture
Computer science. Signal processing
kvartiil
Q2
TTÜ department
elektroenergeetika ja mehhatroonika instituut
language
inglise
Uurimisrühm
Electrical machines research group
Asad, B., Raja, H. A., Vaimann, T., Kallaste, A., Pomarnacki, R., Hyunh, V. K. A current spectrum-based algorithm for fault detection of electrical machines using low-power data acquisition devices // Electronics (2023) vol. 12, 7, art. 1746. https://doi.org/10.3390/electronics12071746