Reinforcing fuzzy rule-based diagnosis of turbomachines with case-based reasoning

This paper presents an integrated knowledge-based system, which combines fuzzy rule-based reasoning with case-based reasoning, for turbomachinery diagnosis. By incorporating a casebased reasoning sub-system in a fuzzy rule-based system, the integrated system allows past experience to be applied in a more direct way. This helps improve the diagnostic accuracy of the rulebased system. This approach has been implemented for the specific task of identifying possible causes of observed vibrations in rotating machines, based on the initial work presented in [18]. The ability that the case-based sub-system brings to the integrated system in improving the diagnostic efficacy of the original rule-based system is demonstrated with test results on real cases.