Case-based Reasoning Locomotive Fault Diagnosis Expert System Research

Expert system is a computer system which emulates the decision ability of experts in certain field. Aiming at developing a locomotive fault diagnosis system, the paper proposed a series of approaches to solve the problem encountered in intelligent locomotive fault diagnosis on the basis of artificial intelligence and fault diagnosis.Based on the research on fault diagnosis technology in common use and burgeoning Case-based reasoning method in artificial intelligence, a scheme and a prototype of Case-based reasoning locomotive fault diagnosis is accomplished. Substantive log of maintenance and the characteristics of the knowledge in locomotive fault diagnosis is analyzed and the key technology of Case-based reasoning fault diagnosis system, such as case-based knowledge engineer and case index technology, is discussed in the paper. The strategy of layered index mechanism after the classification of fault is put forward originally.In expression and management of case and the construction of knowledge base with case-based technology, the locomotive fault case is classified as case sets by characteristic and detail according to the demand of fault diagnosis expert system and the peculiarity of locomotive fault diagnosis on the foundation of characteristic-based case expression. The multi-layered structure of the knowledge base of the system is formed in accordance with the key characteristic abstracted from fault cases, which reduce the complexity of case expression and management and construction of knowledge base and enhance the index speed and efficiency dramatically.Based on research above, the conceptual model and physical model is founded and the prototype of the system is finished. The emulation test to the software with locomotive fault cases in field proved the reasonability of the design and the validity of the implementation.