Nuclear power plant transient identification using a neuro-fuzzy inference system

• Autor(a) principal: Mol, Antonio Carlos de Abreu
• Data de Publicação: 2005
• Outros Autores: Oliveira, Mauro Vitor de, Santos, Isaac José Antônio Luquetti dos, Carvalho, Paulo Victor Rodrigues de, Grecco, Claudio Henrique dos Santos, Augusto, Silas Cordeiro, Instituto de Engenharia Nuclear
• Tipo de documento: Artigo de conferência
• Idioma: por
• Título da fonte: Repositório Institucional do IEN
• Texto Completo: http://carpedien.ien.gov.br:8080/handle/ien/2566
• topic: Nuclear power plant; Transients

In this work, a approach for the identification of transients in presented, aiming at helping the operator to make a decision relative to the procedure to be followed in situations of accidents/transients at nuclear power plants. In this way, a diagnostic strategy based on hierarchical use artificial neural networks (ANN) for a first level transient diagnose. After the ANN has done a preliminary transient type identification, a fuzzy-logic system analyzes the results emiting reliability degree of it. In order to validate the method, a Nuclear Power Plant transient identification problem, comprising postulated accidents, in proposed. Noisy data was used to evaluate the method robustness. The results obtained reveal the ability of the method in dealing with dynamic identification of transients and its reliability degree.