Insights and recommendations for the assessment and design of fault diagnosis methods applied to modern distribution systems (2025)
- Authors:
- USP affiliated authors: OLESKOVICZ, MARIO - EESC ; VIEIRA JÚNIOR, JOSÉ CARLOS DE MELO - EESC ; CUNHA, TALITA MITSUE ONOSE ARAUJO - EESC ; LESSA, LEONARDO DA SILVA - EESC ; DAVI, MOISÉS JUNIOR BATISTA BORGES - EESC
- Unidade: EESC
- DOI: 10.1109/ACCESS.2025.3583561
- Subjects: DISTRIBUIÇÃO DE ENERGIA ELÉTRICA; PROCESSAMENTO DE SINAIS; SISTEMAS ELÉTRICOS; PROTEÇÃO DE SISTEMAS ELÉTRICOS; ENGENHARIA ELÉTRICA
- Agências de fomento:
- Language: Inglês
- Imprenta:
- Publisher place: Piscataway, NJ, USA
- Date published: 2025
- Source:
- Título: IEEE Access
- ISSN: 2169-3536
- Volume/Número/Paginação/Ano: v. 13, p. 111847-111865, 2025
- Este periódico é de acesso aberto
- Este artigo NÃO é de acesso aberto
-
ABNT
CUNHA, Talita Mitsue Onose Araujo et al. Insights and recommendations for the assessment and design of fault diagnosis methods applied to modern distribution systems. IEEE Access, v. 13, p. 111847-111865, 2025Tradução . . Disponível em: http://dx.doi.org/10.1109/ACCESS.2025.3583561. Acesso em: 13 fev. 2026. -
APA
Cunha, T. M. O. A., Lopes, G. N., Lessa, L. da S., Davi, M. J. B. B., Oleskovicz, M., & Vieira Júnior, J. C. de M. (2025). Insights and recommendations for the assessment and design of fault diagnosis methods applied to modern distribution systems. IEEE Access, 13, 111847-111865. doi:10.1109/ACCESS.2025.3583561 -
NLM
Cunha TMOA, Lopes GN, Lessa L da S, Davi MJBB, Oleskovicz M, Vieira Júnior JC de M. Insights and recommendations for the assessment and design of fault diagnosis methods applied to modern distribution systems [Internet]. IEEE Access. 2025 ; 13 111847-111865.[citado 2026 fev. 13 ] Available from: http://dx.doi.org/10.1109/ACCESS.2025.3583561 -
Vancouver
Cunha TMOA, Lopes GN, Lessa L da S, Davi MJBB, Oleskovicz M, Vieira Júnior JC de M. Insights and recommendations for the assessment and design of fault diagnosis methods applied to modern distribution systems [Internet]. IEEE Access. 2025 ; 13 111847-111865.[citado 2026 fev. 13 ] Available from: http://dx.doi.org/10.1109/ACCESS.2025.3583561 - Enhancing power grid reliability: evaluating machine learning algorithms for fault classification in inverter-based generators interconnection lines
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Informações sobre o DOI: 10.1109/ACCESS.2025.3583561 (Fonte: oaDOI API)
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