Digital twin of wind generator to simulate different turbine characteristics using IoT
author
Raja, Hadi Ashraf
Kudelina, Karolina
Rjabtšikov, Viktor
Vaimann, Toomas
Kallaste, Ants
Pomarnacki, Raimondas
Hyunh, Van Khang
statement of authorship
Hadi Ashraf Raja, Karolina Kudelina, Viktor Rjabtšikov, Toomas Vaimann, Ants Kallaste, Raimondas Pomarnacki, Van Khang Hyunh
source
Proceedings of the Future Technologies Conference (FTC) 2023. Vol. 1
location of publication
Cham
publisher
Springer Nature
year of publication
2023
pages
p. 123-132
series
Lecture Notes in Networks and Systems ; 813
conference name, date
8th Future Technologies Conference, FTC 2023, 2-3 November, 2023
conference location
San Francisco, USA
url
https://doi.org/10.1007/978-3-031-47454-5_9
subject term
veaavastus
diagnostika (tehnika)
prognoosmudelid
elektrituulikud
Scopus
https://www.scopus.com/sourceid/21100901469
https://www.scopus.com/record/display.uri?eid=2-s2.0-85177082761&origin=inward&txGid=621055302a55f922c6ff6284da3baa51
quartile
Q4
category (general)
Computer science
Arvutiteadus
Engineering
Tehnika
category (sub)
Computer science. Signal processing
Arvutiteadus. Signaalitöötlus
Engineering. Control and systems engineering
Tehnika. Juhtimis- ja süsteemitehnika
Computer science. Computer networks and communications
Arvutiteadus. Arvutivõrgud ja side
TalTech subject term
digikaksikud
keyword
digital twin
fault diagnosis
predictive models
servomotors
wind energy generation
ISSN
2367-3370
ISBN
978-303147453-8
notes
Bibliogr.: 11 ref
scientific publication
teaduspublikatsioon
classifier
3.1
TalTech department
elektroenergeetika ja mehhatroonika instituut
language
inglise
Reserch Group
Electrical machines research group