Applying Kalman filtering to unbalance estimation in rotating machinery (2018)
- Authors:
- USP affiliated authors: SOUZA, GILBERTO FRANCISCO MARTHA DE - EP ; MICHALSKI, MIGUEL ANGELO DE CARVALHO - EP
- Unidade: EP
- Subjects: USINAS HIDRELÉTRICAS; ELEMENTOS DE MÁQUINAS; FILTROS DE KALMAN; MÉTODO DE MONTE CARLO; MÉTODO DOS ELEMENTOS FINITOS
- Agências de fomento:
- Language: Inglês
- Imprenta:
- Publisher place: Rio de Janeiro
- Date published: 2018
- Source:
- Título: Proceedings
- Conference titles: International Conference on Vulnerability and Risk Analysis and Management - ICVRAM
-
ABNT
MICHALSKI, Miguel Angelo De Carvalho e SOUZA, Gilberto Francisco Martha de. Applying Kalman filtering to unbalance estimation in rotating machinery. 2018, Anais.. Rio de Janeiro: Escola Politécnica, Universidade de São Paulo, 2018. Disponível em: https://www.researchgate.net/publication/324495100_Applying_Kalman_Filtering_to_Unbalance_Estimation_in_Rotating_Machinery. Acesso em: 26 jan. 2026. -
APA
Michalski, M. A. D. C., & Souza, G. F. M. de. (2018). Applying Kalman filtering to unbalance estimation in rotating machinery. In Proceedings. Rio de Janeiro: Escola Politécnica, Universidade de São Paulo. Recuperado de https://www.researchgate.net/publication/324495100_Applying_Kalman_Filtering_to_Unbalance_Estimation_in_Rotating_Machinery -
NLM
Michalski MADC, Souza GFM de. Applying Kalman filtering to unbalance estimation in rotating machinery [Internet]. Proceedings. 2018 ;[citado 2026 jan. 26 ] Available from: https://www.researchgate.net/publication/324495100_Applying_Kalman_Filtering_to_Unbalance_Estimation_in_Rotating_Machinery -
Vancouver
Michalski MADC, Souza GFM de. Applying Kalman filtering to unbalance estimation in rotating machinery [Internet]. Proceedings. 2018 ;[citado 2026 jan. 26 ] Available from: https://www.researchgate.net/publication/324495100_Applying_Kalman_Filtering_to_Unbalance_Estimation_in_Rotating_Machinery - Comparing PCA-based fault detection methods for dynamic processes with correlated and non-Gaussian variables
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