Failure Mode and Observability Analysis (FMOA): an FMEA-based method to support fault detection and diagnosis (2022)
- Authors:
- USP affiliated authors: SOUZA, GILBERTO FRANCISCO MARTHA DE - EP ; SILVA, RENAN FAVARÃO DA - EP ; MELANI, ARTHUR HENRIQUE DE ANDRADE - EP ; MICHALSKI, MIGUEL ANGELO DE CARVALHO - EP
- Unidade: EP
- DOI: 10.3850/978-981-18-5183-4_R22-03-072-cd
- Subjects: MANUTENÇÃO PREVENTIVA; USINAS HIDRELÉTRICAS; FALHA
- Agências de fomento:
- Language: Inglês
- Imprenta:
- Source:
- Título: Proceedings
- Conference titles: European Safety and Reliability Conference
- Este periódico é de acesso aberto
- Este artigo NÃO é de acesso aberto
-
ABNT
SILVA, Renan Favarão da et al. Failure Mode and Observability Analysis (FMOA): an FMEA-based method to support fault detection and diagnosis. 2022, Anais.. Singapore: Escola Politécnica, Universidade de São Paulo, 2022. Disponível em: https://www.rpsonline.com.sg/proceedings/esrel2022/html/R22-03-072.xml. Acesso em: 23 jan. 2026. -
APA
Silva, R. F. da, Melani, A. H. de A., Michalski, M. A. D. C., & Souza, G. F. M. de. (2022). Failure Mode and Observability Analysis (FMOA): an FMEA-based method to support fault detection and diagnosis. In Proceedings. Singapore: Escola Politécnica, Universidade de São Paulo. doi:10.3850/978-981-18-5183-4_R22-03-072-cd -
NLM
Silva RF da, Melani AH de A, Michalski MADC, Souza GFM de. Failure Mode and Observability Analysis (FMOA): an FMEA-based method to support fault detection and diagnosis [Internet]. Proceedings. 2022 ;[citado 2026 jan. 23 ] Available from: https://www.rpsonline.com.sg/proceedings/esrel2022/html/R22-03-072.xml -
Vancouver
Silva RF da, Melani AH de A, Michalski MADC, Souza GFM de. Failure Mode and Observability Analysis (FMOA): an FMEA-based method to support fault detection and diagnosis [Internet]. Proceedings. 2022 ;[citado 2026 jan. 23 ] Available from: https://www.rpsonline.com.sg/proceedings/esrel2022/html/R22-03-072.xml - A framework to automate fault detection and diagnosis based on moving window principal component analysis and Bayesian network
- A framework for in-service life extension of hydroelectric generation assets
- Applying an unsupervised machine learning method for defining maintenance significant items
- Remaining useful life estimation based on an adaptive approach of Autoregressive Integrated Moving Average (ARIMA)
- Applying principal component analysis for multi-parameter failure prognosis and determination of remaining useful life
- Fault detection and diagnosis based on unsupervised machine learning methods: a Kaplan turbine case study
- Identifying changes in degradation stages for an unsupervised fault prognosis method for engineering systems
- Reliability and risk centered maintenance: a novel method for supporting maintenance management
- A fault detection framework based on data-driven digital shadows
- Applying cluster analysis to support failure management policy selection in asset management: a hydropower plant case study
Informações sobre o DOI: 10.3850/978-981-18-5183-4_R22-03-072-cd (Fonte: oaDOI API)
Download do texto completo
| Tipo | Nome | Link | |
|---|---|---|---|
 |
R22-03-072.pdf |
How to cite
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
