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Pregled bibliografske jedinice broj: 1210787

Classification of Electrical Power Disturbances on Hybrid-Electric Ferries Using Wavelet Transform and Neural Network


Cuculić, Aleksandar; Draščić, Luka; Panić, Ivan; Ćelić, Jasmin
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, 21 doi:10.3390/jmse10091190 (međunarodna recenzija, članak, znanstveni)


CROSBI ID: 1210787 Za ispravke kontaktirajte CROSBI podršku putem web obrasca

Naslov
Classification of Electrical Power Disturbances on Hybrid-Electric Ferries Using Wavelet Transform and Neural Network

Autori
Cuculić, Aleksandar ; Draščić, Luka ; Panić, Ivan ; Ćelić, Jasmin

Izvornik
Journal of marine science and engineering (2077-1312) 10 (2022), 9; 1190, 21

Vrsta, podvrsta i kategorija rada
Radovi u časopisima, članak, znanstveni

Ključne riječi
hybrid-electric ferry ; maritime transport ; marine electrical systems ; electrical power disturbances ; wavelet transform ; neural network

Sažetak
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.

Izvorni jezik
Engleski

Znanstvena područja
Elektrotehnika, Tehnologija prometa i transport



POVEZANOST RADA


Ustanove:
Pomorski fakultet, Rijeka

Profili:

Avatar Url Ivan Panić (autor)

Avatar Url Jasmin Ćelić (autor)

Avatar Url Aleksandar Cuculić (autor)

Poveznice na cjeloviti tekst rada:

doi

Citiraj ovu publikaciju:

Cuculić, Aleksandar; Draščić, Luka; Panić, Ivan; Ćelić, Jasmin
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, 21 doi:10.3390/jmse10091190 (međunarodna recenzija, članak, znanstveni)
Cuculić, A., Draščić, L., Panić, 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), 1190, 21 doi:10.3390/jmse10091190.
@article{article, author = {Cuculi\'{c}, Aleksandar and Dra\v{s}\v{c}i\'{c}, Luka and Pani\'{c}, Ivan and \'{C}eli\'{c}, Jasmin}, year = {2022}, pages = {21}, DOI = {10.3390/jmse10091190}, chapter = {1190}, keywords = {hybrid-electric ferry, maritime transport, marine electrical systems, electrical power disturbances, wavelet transform, neural network}, journal = {Journal of marine science and engineering}, doi = {10.3390/jmse10091190}, volume = {10}, number = {9}, issn = {2077-1312}, title = {Classification of Electrical Power Disturbances on Hybrid-Electric Ferries Using Wavelet Transform and Neural Network}, keyword = {hybrid-electric ferry, maritime transport, marine electrical systems, electrical power disturbances, wavelet transform, neural network}, chapternumber = {1190} }
@article{article, author = {Cuculi\'{c}, Aleksandar and Dra\v{s}\v{c}i\'{c}, Luka and Pani\'{c}, Ivan and \'{C}eli\'{c}, Jasmin}, year = {2022}, pages = {21}, DOI = {10.3390/jmse10091190}, chapter = {1190}, keywords = {hybrid-electric ferry, maritime transport, marine electrical systems, electrical power disturbances, wavelet transform, neural network}, journal = {Journal of marine science and engineering}, doi = {10.3390/jmse10091190}, volume = {10}, number = {9}, issn = {2077-1312}, title = {Classification of Electrical Power Disturbances on Hybrid-Electric Ferries Using Wavelet Transform and Neural Network}, keyword = {hybrid-electric ferry, maritime transport, marine electrical systems, electrical power disturbances, wavelet transform, neural network}, chapternumber = {1190} }

Časopis indeksira:


  • Current Contents Connect (CCC)
  • Web of Science Core Collection (WoSCC)
    • Science Citation Index Expanded (SCI-EXP)
    • SCI-EXP, SSCI i/ili A&HCI
  • Scopus


Uključenost u ostale bibliografske baze podataka::


  • GeoRef
  • INSPEC


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