Projektiniai pranešimai mokslo žurnaluose ir konferencijų pranešimų medžiaga

Khan, M.A.; Asad, B.; Vaimann, T.; Kallaste, A.; Pomarnacki, R.; Hyunh, V.K. (2023). Improved Fault Classification and Localization in Power Transmission Networks Using VAE-Generated Synthetic Data and Machine Learning Algorithms. Machines, 11 (10), 963.

Kudelina, K.; Vaimann, T.; Asad, B.; Rassõlkin, A.; Kallaste, A.; Demidova, G. (2021). Trends and Challenges in Intelligent Condition Monitoring of Electrical Machines Using Machine Learning. Applied Sciences, 11 (6), #2761.

Asad, B.; Vaimann, T.; Belahcen, A.; Kallaste, A.; Rassõlkin, A.; Ghafarokhi, P. S.; Kudelina, K. (2021). Transient Modeling and Recovery of Non-Stationary Fault Signature for Condition Monitoring of Induction Motors. Applied Sciences, 11 (6), 2806−2823.

Immanuel N. Jiya; Ahmed Salem; Huynh Van Khang. (2023). Integrated Multiport DC-DC and Multilevel Converters for Multiple Renewable Energy Source Integration. 2022 IEEE Industry Applications Society Annual Meeting (IAS)

Jankauskas, M.; Serackis, A.; Šapurov, M.; Pomarnacki, R.; Baskys, A.; Hyunh, V.K.; Vaimann, T.; Zakis, J. (2023). The study presents a novel approach using recurrent neural networks for early anomaly detection in wind turbine maintenance, significantly extending the lead time for fault intervention. Sensors, 23, 5695.