A novel Artificial Immune System for fault behavior detection

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This paper presents an error detection methodology to enable fault detection inspired on recent immune theory. The fault detection problem is a challenging problem due to processes increasing complexity and agility necessary to avoid malfunction or accidents. The key challenge is determining the difference between normal and potential harmful activities. A promising solution is emerging in the form of Artificial Immune System (AIS). In this article, Natural Killer (NK) immune cells mechanisms inspired an AIS. The AIS proposed uses recent biological mechanism such as: NK activation and education machinery. DAMADICS benchmark was applied to compare the proposed AIS performance to others fault detection algorithms. The results show that the novel approach developed provides better detection rate and false alarms tradeoff when compared to other methods in literature.

论文关键词:Artificial intelligence,Artificial Immune System,Fault detection,Immune system,Model-based fault diagnosis

论文评审过程:Available online 21 December 2010.

论文官网地址:https://doi.org/10.1016/j.eswa.2010.12.019