Pregled bibliografske jedinice broj: 1210783
WAVELET TRANSFORM NEURAL NETWORK CLASSIFIER FOR ELECTRICAL FERRY POWER DISTURBANCE CLASSIFICATION
WAVELET TRANSFORM NEURAL NETWORK CLASSIFIER FOR ELECTRICAL FERRY POWER DISTURBANCE CLASSIFICATION // 15th Baška GNSS Conference: Technologies, Techniques and Applications Across PNT and The 2nd Workshop on Smart, Blue and Green Maritime Technologies BOOK OF EXTENDED ABSTRACTS / Brčić, David ; Valčić, Marko ; Kos, Sergio ; Vuković, Josip (ur.).
Zagreb: Pomorski fakultet Sveučilišta u Rijeci, 2022. str. 131-134 (predavanje, međunarodna recenzija, prošireni sažetak, znanstveni)
CROSBI ID: 1210783 Za ispravke kontaktirajte CROSBI podršku putem web obrasca
Naslov
WAVELET TRANSFORM NEURAL
NETWORK CLASSIFIER FOR
ELECTRICAL FERRY POWER
DISTURBANCE CLASSIFICATION
Autori
Draščić, Luka ; Cuculić, Aleksandar ; Panić, Ivan ; Ćelić, Jasmin
Vrsta, podvrsta i kategorija rada
Sažeci sa skupova, prošireni sažetak, znanstveni
Izvornik
15th Baška GNSS Conference: Technologies, Techniques and Applications Across PNT and The 2nd Workshop on Smart, Blue and Green Maritime Technologies BOOK OF EXTENDED ABSTRACTS
/ Brčić, David ; Valčić, Marko ; Kos, Sergio ; Vuković, Josip - Zagreb : Pomorski fakultet Sveučilišta u Rijeci, 2022, 131-134
Skup
15th Annual Baška GNSS Conference ; The 2nd Workshop on Smart, Blue and Green Maritime Technologies
Mjesto i datum
Baška, Hrvatska, 08.05.2022. - 13.05.2022
Vrsta sudjelovanja
Predavanje
Vrsta recenzije
Međunarodna recenzija
Ključne riječi
electrical ferry ; fault classification ; neural network ; wavelet transform
Sažetak
Hybridization and electrification of ferry-based transport aims to reduce environmental impact caused by conventional power generation methods used on conventional ferries. Diversification of ship’s power generation and distribution systems, use of alternative power sources, energy storage solutions and voltage and frequency converters can have a negative impact on electrical power quality and complicate detection and identification of electrical faults. This paper proposes the method for identification and classification of such faults based on wavelet transform decomposition and neural network classifier.
Izvorni jezik
Engleski
Znanstvena područja
Elektrotehnika, Tehnologija prometa i transport
POVEZANOST RADA
Ustanove:
Pomorski fakultet, Rijeka
