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Classification of Electrical Power Disturbances on Hybrid-Electric Ferries Using Wavelet Transform and Neural Network
Journal of marine science and engineering, 10 (2022), 9; 1190. https://doi.org/10.3390/jmse10091190
Cuculić, Aleksandar; Draščić, Luka; Panić, Ivan; Ćelić, Jasmin

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Cuculić, A., Draščić, L., Panić, I. i Ćelić, J. (2022). Classification of Electrical Power Disturbances on Hybrid-Electric Ferries Using Wavelet Transform and Neural Network. Journal of marine science and engineering, 10. (9). doi: 10.3390/jmse10091190

Cuculić, Aleksandar, et al. "Classification of Electrical Power Disturbances on Hybrid-Electric Ferries Using Wavelet Transform and Neural Network." Journal of marine science and engineering, vol. 10, br. 9, 2022. https://doi.org/10.3390/jmse10091190

Cuculić, Aleksandar, Luka Draščić, Ivan Panić i Jasmin Ćelić. "Classification of Electrical Power Disturbances on Hybrid-Electric Ferries Using Wavelet Transform and Neural Network." Journal of marine science and engineering 10, br. 9 (2022). https://doi.org/10.3390/jmse10091190

Cuculić, A., et al. (2022) 'Classification of Electrical Power Disturbances on Hybrid-Electric Ferries Using Wavelet Transform and Neural Network', Journal of marine science and engineering, 10(9). doi: 10.3390/jmse10091190

Cuculić A, Draščić L, Panić I, Ćelić J. Classification of Electrical Power Disturbances on Hybrid-Electric Ferries Using Wavelet Transform and Neural Network. Journal of marine science and engineering [Internet]. 2022. [pristupljeno 12.05.2024.];10(9). doi: 10.3390/jmse10091190

A. Cuculić, L. Draščić, I. Panić i J. Ćelić, "Classification of Electrical Power Disturbances on Hybrid-Electric Ferries Using Wavelet Transform and Neural Network", Journal of marine science and engineering, vol. 10, br. 9, 2022. [Online]. Dostupno na: https://urn.nsk.hr/urn:nbn:hr:187:044577. [Citirano: 12.05.2024.]

Za citiranje koristite ovu mrežnu adresu: https://urn.nsk.hr/urn:nbn:hr:187:044577
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Naslov (engleski)Classification of Electrical Power Disturbances on Hybrid-Electric Ferries Using Wavelet Transform and Neural Network
AutorAleksandar Cuculić
MBZ: 325051
AutorLuka Draščić
AutorIvan Panić
MBZ: 371280
AutorJasmin Ćelić
Autorova ustanovaSveučilište u Rijeci
Pomorski fakultet
Znanstveno / umjetničko
područje, polje i grana		TEHNIČKE ZNANOSTI
Tehnologija prometa i transport
Sažetak (engleski)
Electrical power systems on hybrid-electric ferries are characterized by the intensive use of power electronics and a complex usage profile with the often-limited power of battery storage. It is extremely important to detect faults in a timely manner, which can lead to system malfunctions that can directly affect the safety and economic performance of the vessel. In this paper, a power disturbance classification method for hybrid- electric ferries is developed based on a wavelet transform and a neural network classifier. For each of the observed power disturbance categories, 200 signals were artificially generated. A discrete wavelet transform was applied to these signals, allowing different time-frequency resolutions to be used for different frequencies. Three statistical parameters are calculated for each coefficient: Standard deviation, entropy and asymmetry of the signal, providing a total of 18 variables for a signal. A neural network with 18 input neurons, 3 hidden neurons, and 6 output neurons was used to detect the aforementioned perturbations. The classification models with different wavelets were analyzed based on accuracy, confusion matrices, and other parameters. The analysis showed that the proposed model can be successfully used for the detection and classification of disturbances in the considered vessels, which allows the implementation of better and more efficient algorithms for energy management.
Ključne riječi (engleski)
Jezikengleski
Vrsta publikacijeZnanstveni rad - Izvorni znanstveni rad
Status objaveObjavljen
Vrsta recenzijeRecenziran - međunarodna recenzija
Verzija publikacijeObjavljena verzija rada (izdavačev PDF)
Naslov časopisaJournal of marine science and engineering
Brojčani podacivol. 10, br. 9, 1190
e-ISSN2077-1312
DOIhttps://doi.org/10.3390/jmse10091190
URN:NBNurn:nbn:hr:187:044577
Datum objave publikacije2022
URL dokumentahttp://bib.irb.hr/1210787
Vrsta resursaTekst
Prava pristupaOtvoreni pristup
Uvjeti korištenjaIkona licence Zaštićeno autorskim pravom.
Datum i vrijeme pohrane2022-12-12 14:00:04