Detecção de falhas em sistemas dinâmicos: abordagens imunoinspiradas.

Detalhes bibliográficos
Ano de defesa: 2010
Autor(a) principal: Carlos Alexandre Laurentys de Almeida
Orientador(a): Não Informado pela instituição
Banca de defesa: Não Informado pela instituição
Tipo de documento: Tese
Tipo de acesso: Acesso aberto
Idioma: por
Instituição de defesa: Universidade Federal de Minas Gerais
UFMG
Programa de Pós-Graduação: Não Informado pela instituição
Departamento: Não Informado pela instituição
País: Não Informado pela instituição
Palavras-chave em Português:
Link de acesso: http://hdl.handle.net/1843/BUOS-8CKJ4W
Resumo: This thesis has proposed, implemented and discussed immune-inspired approaches for dynamic systems fault detection. The fault detection is becoming increasingly challenging due to processes complexity and the agility need to prevent malfunction or even accidents. The challenge lies in diferentiating between normal operation and potential fault. Promising solutions to this problem has emerged through immune-inspired approaches. This thesis has contributed through three approaches: DF-NKC (fault detection inspired on natural killer cell's mechanisms), DF-DM (fault detection inspired on danger model) and DF-Multioperacional (fault detection based on improvements of negative selection algorithms). Firstly, DF-NKC approach has used concepts inspired on natural killer cells biological mechanisms of activation and maturation. Secondly, DF-DM approach has used danger model inspiration and a mathematical model of immune system. Finally, the DF-Multioperational approach was based on existing negative selection algorithms. The DF-NKC and DF-DM were applied in a valve actuator system benchmark provided by DAMADICS (Development and Application of Methods for Actuator Diagnosis in Industrial Control Systems) while DF-Multioperacional was applied to fault detection in a direct current motor system benchmark. The algorithms results show that the approaches are promising for fault detection.