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Filtros : "Michalski, Miguel Angelo De Carvalho" Limpar

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  • Tese (Doutorado)

    Rotating machinery fault identification using model-based and data-based techniques integration. (2021)

    Michalski, Miguel Angelo De Carvalho; Souza, Gilberto Francisco Martha de (Orientador)

    Unidade: EP

    Subjects: ENGENHARIA, INTELIGÊNCIA ARTIFICIAL, MÉTODO DOS ELEMENTOS FINITOS

    Acesso à fonteHow to cite
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    • ABNT

      MICHALSKI, Miguel Angelo De Carvalho. Rotating machinery fault identification using model-based and data-based techniques integration. 2021. Tese (Doutorado) – Universidade de São Paulo, São Paulo, 2021. Disponível em: https://www.teses.usp.br/teses/disponiveis/3/3151/tde-04062021-173315/. Acesso em: 01 jun. 2024.

    • APA

      Michalski, M. A. D. C. (2021). Rotating machinery fault identification using model-based and data-based techniques integration. (Tese (Doutorado). Universidade de São Paulo, São Paulo. Recuperado de https://www.teses.usp.br/teses/disponiveis/3/3151/tde-04062021-173315/

    • NLM

      Michalski MADC. Rotating machinery fault identification using model-based and data-based techniques integration. [Internet]. 2021 ;[citado 2024 jun. 01 ] Available from: https://www.teses.usp.br/teses/disponiveis/3/3151/tde-04062021-173315/

    • Vancouver

      Michalski MADC. Rotating machinery fault identification using model-based and data-based techniques integration. [Internet]. 2021 ;[citado 2024 jun. 01 ] Available from: https://www.teses.usp.br/teses/disponiveis/3/3151/tde-04062021-173315/

  • Artigo de periodico

    Fuzzy-FMSA: evaluating Fault Monitoring and Detection Strategies Based on Failure Mode and Symptom Analysis and Fuzzy Logic (2020)

    Murad, Carlos Alberto; Melani, Arthur Henrique de Andrade ; Michalski, Miguel Angelo De Carvalho ; Caminada Netto, Adherbal; Souza, Gilberto Francisco Martha de ; Nabeta, Silvio Ikuyo

    Source: ASCE-ASME journal of risk and uncertainty in engineering systems. Part B. Mechanical engineering. Unidade: EP

    Subjects: FALHAS COMPUTACIONAIS, LÓGICA FUZZY

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    • ABNT

      MURAD, Carlos Alberto et al. Fuzzy-FMSA: evaluating Fault Monitoring and Detection Strategies Based on Failure Mode and Symptom Analysis and Fuzzy Logic. ASCE-ASME journal of risk and uncertainty in engineering systems. Part B. Mechanical engineering, v. 6, n. 3, p. se 2020, 2020Tradução . . Disponível em: https://doi.org/10.1115/1.4045974. Acesso em: 01 jun. 2024.

    • APA

      Murad, C. A., Melani, A. H. de A., Michalski, M. A. D. C., Caminada Netto, A., Souza, G. F. M. de, & Nabeta, S. I. (2020). Fuzzy-FMSA: evaluating Fault Monitoring and Detection Strategies Based on Failure Mode and Symptom Analysis and Fuzzy Logic. ASCE-ASME journal of risk and uncertainty in engineering systems. Part B. Mechanical engineering, 6( 3), se 2020. doi:10.1115/1.4045974

    • NLM

      Murad CA, Melani AH de A, Michalski MADC, Caminada Netto A, Souza GFM de, Nabeta SI. Fuzzy-FMSA: evaluating Fault Monitoring and Detection Strategies Based on Failure Mode and Symptom Analysis and Fuzzy Logic [Internet]. ASCE-ASME journal of risk and uncertainty in engineering systems. Part B. Mechanical engineering. 2020 ;6( 3): se 2020.[citado 2024 jun. 01 ] Available from: https://doi.org/10.1115/1.4045974

    • Vancouver

      Murad CA, Melani AH de A, Michalski MADC, Caminada Netto A, Souza GFM de, Nabeta SI. Fuzzy-FMSA: evaluating Fault Monitoring and Detection Strategies Based on Failure Mode and Symptom Analysis and Fuzzy Logic [Internet]. ASCE-ASME journal of risk and uncertainty in engineering systems. Part B. Mechanical engineering. 2020 ;6( 3): se 2020.[citado 2024 jun. 01 ] Available from: https://doi.org/10.1115/1.4045974
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