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Orientador(es)
Resumo(s)
Fault diagnosis systems have an important role in industrial plants because the early fault detection and isolation (FDI) can minimize damages in the plants. The main aim of this work is to propose a two-stage neuro-fuzzy approach as a fault diagnosis system in dynamic processes. The first stage of the system is responsible for fault detection and is implemented using a neuro-fuzzy (N-F) model. The second stage of the system is responsible for fault isolation and is built using an hierarchical structure of fuzzy neural networks. The FDI system is applied to fault diagnosis in the actuators of one sugar factory.
Descrição
Palavras-chave
Fault diagnosis Neural network Fuzzy modelling Backpropagation algorithms Hierarchical structure Actuators
Contexto Educativo
Citação
MENDES, Mário J. G. C.; [et al] – Neuro-fuzzy structures in FDI systems. IFAC Proceedings Volumes. ISSN 2405-8963. Vol. 35, N.º 1 (2002), pp. 465-470
Editora
Elsevier