Fonte: IFAC-PapersOnLine. Unidade: EESC
Assuntos: INTELIGÊNCIA ARTIFICIAL, MOTORES DE INDUÇÃO, FALHA, APRENDIZADO COMPUTACIONAL, ENGENHARIA ELÉTRICA
ABNT
MACIEJEWSKI, Narco Afonso Ravazzoli et al. Artificial intelligence-based recommendation system for detecting and diagnosing broken bars in induction motors under transient operation. IFAC-PapersOnLine. Laxenburg, Austria: Escola de Engenharia de São Carlos, Universidade de São Paulo. Disponível em: http://dx.doi.org/10.1016/j.ifacol.2024.09.107. Acesso em: 25 jun. 2025. , 2024APA
Maciejewski, N. A. R., Freire, R. Z., Szejka, A. L., Bazzo, T. P. M., Lopes, S. M. de A., & Flauzino, R. A. (2024). Artificial intelligence-based recommendation system for detecting and diagnosing broken bars in induction motors under transient operation. IFAC-PapersOnLine. Laxenburg, Austria: Escola de Engenharia de São Carlos, Universidade de São Paulo. doi:10.1016/j.ifacol.2024.09.107NLM
Maciejewski NAR, Freire RZ, Szejka AL, Bazzo TPM, Lopes SM de A, Flauzino RA. Artificial intelligence-based recommendation system for detecting and diagnosing broken bars in induction motors under transient operation [Internet]. IFAC-PapersOnLine. 2024 ; 58( 19): 1156-1161.[citado 2025 jun. 25 ] Available from: http://dx.doi.org/10.1016/j.ifacol.2024.09.107Vancouver
Maciejewski NAR, Freire RZ, Szejka AL, Bazzo TPM, Lopes SM de A, Flauzino RA. Artificial intelligence-based recommendation system for detecting and diagnosing broken bars in induction motors under transient operation [Internet]. IFAC-PapersOnLine. 2024 ; 58( 19): 1156-1161.[citado 2025 jun. 25 ] Available from: http://dx.doi.org/10.1016/j.ifacol.2024.09.107