A Study of Fault Diagnostic based on Artifcial Immune Systems

Artificial Immune technology, a resource limited artificial immune classifier system,has performed well on elementary classification tasks. This paper presents one form of mapping Artificial Immune Systems (AIS) into Learning Classifier Systems for fault diagnosis. We propose a novel ideal to apply semantics in immune models. Similar to Learning Classifier Systems, a better understanding of AIS can be obtained when they are analysed under the perspective of complex Semantic system. One of the goals here is to determine complementary features of both systems (Semantic systemand AIS), aiming at providing a novel mapping conception for fault diagnosis.