A Semantic Centric Fault Diagnostic Model Compiling Approach Based Artificial Immune System

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. However, the current research on the diagnosis problem about the large-scale systems often has not fully taken into account an important factor the semantics in the systems. This paper presents a novel ideal of semantic centered fault diagnosis based on artificial immunity for mine hoist. The system semantics are composed of the structure and behavior information under the normal or abnormal conditions. In the given definition of model-based fault diagnosis, we propose a novel model compiling approach by providing the rule of cause and effect information in the sentential function, which can express complex semantics and gain the minimal diagnosis by the theorem provers of first order logic. In addition, this new model compiling method is set forth by the fault diagnosis problem for mine hoist. Diagnosis consists of the diagnosis engine, diagnosis agents and diagnosis callback interfaces. It proves that this model compiling method can effectively solve the semantic problem of diagnosis for mine hoist.