Fault isolation approach using a PROFIBUS network: a case study

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...

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Detalhes bibliográficos
Autor principal: Mendes, Mário J. G. C. (author)
Outros Autores: Kowal, Marek (author), Calado, João Manuel Ferreira (author), Korbicz, Józef (author), Costa, J. M. G. Sá da (author)
Formato: conferenceObject
Idioma:eng
Publicado em: 2020
Assuntos:
Texto completo:http://hdl.handle.net/10400.21/10976
País:Portugal
Oai:oai:repositorio.ipl.pt:10400.21/10976
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.