An Artificial Immune System Model Based on Semantics

With the development of artificial immune technology, People set more and more focus on the diagnosis problem in such complex distribution systems based on artificial immunity. This paper presents an intelligent methodology for diagnosing incipient faults in mine hoist. In this fault diagnosis system, In order to enhance the fault diagnosis performance, we propose a novel ideal of semantic-centered fault diagnosis based on artificial immunity for mine hoist. Concerning with the disadvantage negative selection algorithm can not effectively capture the semantic information in some complex spaces, in the given definition of model-based fault diagnosis, this paper proposes a logic-based semantic model. The model represents lymphocytes and antigens as logic-operator, which can express complex semantics and gain the minimal diagnosis by the theorem provers of first order logic. Finally, in the background of process-based abnormal detection, we designed a systematic framework which tries to exploit semantic information. It proves that this model can effectively solve the semantic problem of diagnosis for mine hoist.