Fault Diagnosis System for Large-Scale Equipments Based on Hybrid Reasoning

Abstract

Because of their complex structures, diverse functions, and cross-correlation among subsystems, the fault of large-scale equipments occurs easily, but its trouble shooting is difficult. Firstly, a hybrid reasoning method is proposed, and the framework of fault diagnosis system is constructed according to characteristics of case based reasoning (CBR) and rule based reasoning (RBR). Secondly, CBR and RBR applied to fault diagnosis for large-scale NC equipments are analyzed. In RBR process, the fault tree was obtained by reachability matrix, and the rules knowledge is automatically generated by fault tree, so the bottleneck of acquiring rules knowledge is solved. Lastly, this method is used in the fault diagnosis of certain large-scale NC equipment, which verifies the validity of the method.