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Master's Dissertation
DOI
https://doi.org/10.11606/D.3.2016.tde-15062016-154821
Document
Author
Full name
Arthur Henrique de Andrade Melani
E-mail
Institute/School/College
Knowledge Area
Date of Defense
Published
São Paulo, 2015
Supervisor
Committee
Souza, Gilberto Francisco Martha de (President)
Martins, Marcelo Ramos
Sagrilo, Luis Volnei Sudati
Title in Portuguese
Desenvolvimento de um método para diagnose de falhas na operação de navios transportadores de gás natural liquefeito através de redes bayesianas.
Keywords in Portuguese
Análise de confiabilidade
Gás natural líquido
Redes bayesianas
Abstract in Portuguese
O Gás Natural Liquefeito (GNL) tem, aos poucos, se tornado uma importante opção para a diversificação da matriz energética brasileira. Os navios metaneiros são os responsáveis pelo transporte do GNL desde as plantas de liquefação até as de regaseificação. Dada a importância, bem como a periculosidade, das operações de transporte e de carga e descarga de navios metaneiros, torna-se necessário não só um bom plano de manutenção como também um sistema de detecção de falhas que podem ocorrer durante estes processos. Este trabalho apresenta um método de diagnose de falhas para a operação de carga e descarga de navios transportadores de GNL através da utilização de Redes Bayesianas em conjunto com técnicas de análise de confiabilidade, como a Análise de Modos e Efeitos de Falhas (FMEA) e a Análise de Árvores de Falhas (FTA). O método proposto indica, através da leitura de sensores presentes no sistema de carga e descarga, quais os componentes que mais provavelmente estão em falha. O método fornece uma abordagem bem estruturada para a construção das Redes Bayesianas utilizadas na diagnose de falhas do sistema.
Title in English
Development of a method for fault diagnosis in liquefied natural gas carrier ships using bayesian networks.
Keywords in English
Bayesian networks
Liquefied natural gas
Reability analysis
Abstract in English
Liquefied Natural Gas (LNG) has gradually become an important option for the diversification of the Brazilian energy matrix. LNG carriers are responsible for LNG transportation from the liquefaction plant to the regaseification plant. Given the importance, as well as the risk, of transportation and loading/unloading operations of LNG carriers, not only a good maintenance plan is needed, but also a failure detection system that localizes the origin of a failure that may occur during these processes. This research presents a fault diagnosis method for the loading and unloading operations of LNG carriers through the use of Bayesian networks together with reliability analysis techniques, such as Failure Modes and Effects Analysis (FMEA ) and Fault Tree Analysis (FTA). The proposed method indicates, by reading sensors present in the loading and unloading system, which components are most likely faulty. The method provides a well-structured approach for the development of Bayesian networks used in the diagnosis of system failures.
 
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Publishing Date
2016-06-17
 
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