Development of ME-GI dual-fuel engine fault diagnosis expert system based on self-learning ontology

In order to meet intelligent requirement of the expert system in the process of fault diagnosis, a fault diagnosis system architecture which based on self-learning ontology was proposed in this paper. The fault diagnosis knowledge structure was defined; the relevant structure ontology and core fault ontology were constructed. Based on design of data warehouse of fault diagnosis, the decision tree in machine learning and Apriori algorithm were used to acquire fault knowledge to realize ontology self-learning. Taking the Hydraulic Control System of ME-GI dual-fuel engine as a prototype, the Hydraulic Control System diagnosis expert system was developed based on self-learning ontology.