Damage Detection on Turbomachinery with Machine Learning Algortihms
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Tarih
2024
Yazarlar
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Springer Science and Business Media Deutschland GmbH
Erişim Hakkı
info:eu-repo/semantics/closedAccess
Özet
This study uses machine learning methods to find deterioration in turbomachine parts. In turbomachines, damage control procedures are carried out at specific times. Even though these checks take a while, if there is no damage, the components won’t be replaced, and it is not anticipated that they will be rechecked until the following control or an unforeseen incident. For this situation, a machine learning algorithm has been developed and 96% accuracy was obtained for overall components. © 2024, The Author(s), under exclusive license to Springer Nature Switzerland AG.
Açıklama
2nd International Conference on Advanced Engineering, Technology and Applications, ICAETA 2023 -- 10 March 2023 through 11 March 2023 -- Istanbul -- 305999
Anahtar Kelimeler
Machine Learning; Predictive Maintenance; Turbo Machinery
Kaynak
Communications in Computer and Information Science
WoS Q Değeri
Scopus Q Değeri
Q4
Cilt
1983 CCIS
