Publicação

Fault isolation approach using a PROFIBUS network: a case study

Detalhes bibliográficos
Resumo:	This paper presents the second stage, of a two-stage neuro-fuzzy system, used for fault isolation (FI) in dynamic processes and it`s built using a hierarchical structure of fuzzy neural networks. The current approach is tested under a hardware bench constructed with componentes commonly used in the industry and consists on a pilot plant under supervision, a supervision unit, a fault detection and isolation unit and a fault simulation unit. All the elements are connected to a PROFIBUS network, which acts as the communication system for exchanging information between the automation system and the distributed field devices.
Autores principais:	Mendes, Mário J. G. C.
Outros Autores:	Kowal, Marek; Calado, João Manuel Ferreira; Korbicz, Józef; Costa, J. M. G. Sá da
Assunto:	Fault diagnosis Fault isolation Neural network Fuzzy logic Hierarchical structure Benchmark exemples
Ano:	2002
País:	Portugal
Tipo de documento:	documento de conferência
Tipo de acesso:	acesso restrito
Instituição associada:	Universidade Politécnica de Lisboa
Idioma:	inglês
Origem:	Repositório Científico da Universidade Politécnica de Lisboa

Descrição
Resumo:	This paper presents the second stage, of a two-stage neuro-fuzzy system, used for fault isolation (FI) in dynamic processes and it`s built using a hierarchical structure of fuzzy neural networks. The current approach is tested under a hardware bench constructed with componentes commonly used in the industry and consists on a pilot plant under supervision, a supervision unit, a fault detection and isolation unit and a fault simulation unit. All the elements are connected to a PROFIBUS network, which acts as the communication system for exchanging information between the automation system and the distributed field devices.

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