Research on turbine vibration fault diagnosis expert system based on rough set theory
Deli Zhang, Na Wang · 2022
Based on the traditional turbine vibration fault diagnosis expert system, the rough set theory is introduced to solve the bottleneck problem that the expert system is difficult to obtain complete knowledge. The system starts from the decision table formed by historical fault data, uses rough set theory to reduce, and constructs an expert system knowledge base model. The confidence level of the diagnostic rule is expressed by calculating the membership roughness of the rule. Using inference engine and fault case base, the dynamic maintenance of knowledge base is realized.