Publicação
Fault isolation based on HSFNN applied to DAMADICS benchmark problem
| Resumo: | The present paper is concemed with the application of a hierarchical structure of fuzzy newal networks (HSFNN) to fault isolation on a pneumatic servo-motor actuated valve that is the benchmark considered for all the DAMADICS (Development and Application of Methods for Actuator Diagnosis in IndusIrial Control Systems) project partners. The adoption of a hierarchical structure of fuzzy newal netwoIks for fault isolation pwposes aims the development of an architecture that can localise abrupt and incipient single and multiple faults correctly or at least with a minimum misclassification rate and be easily trained, ftom only single abrupt fault symptoms. |
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| Autores principais: | Calado, João Manuel Ferreira |
| Outros Autores: | Louro, R.; Mendes, Mário J. G. C.; Costa, J. M. G. Sá da; Kowal, M. |
| Assunto: | Fault isolation Hierarchical structures Neural networks Fuzzy systems Actuators |
| Ano: | 2003 |
| País: | Portugal |
| Tipo de documento: | artigo |
| Tipo de acesso: | acesso restrito |
| Instituição associada: | Universidade Politécnica de Lisboa |
| Idioma: | inglês |
| Origem: | Repositório Científico da Universidade Politécnica de Lisboa |
| Resumo: | The present paper is concemed with the application of a hierarchical structure of fuzzy newal networks (HSFNN) to fault isolation on a pneumatic servo-motor actuated valve that is the benchmark considered for all the DAMADICS (Development and Application of Methods for Actuator Diagnosis in IndusIrial Control Systems) project partners. The adoption of a hierarchical structure of fuzzy newal netwoIks for fault isolation pwposes aims the development of an architecture that can localise abrupt and incipient single and multiple faults correctly or at least with a minimum misclassification rate and be easily trained, ftom only single abrupt fault symptoms. |
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