Research on turbine vibration fault diagnosis expert system based on rough set theory

Deli Zhang; Na Wang

doi:10.1117/12.2653304

27 September 2022 Research on turbine vibration fault diagnosis expert system based on rough set theory

Deli Zhang, Na Wang

Proceedings Volume 12346, 2nd International Conference on Information Technology and Intelligent Control (CITIC 2022); 123460F (2022) https://doi.org/10.1117/12.2653304
Event: 2nd International Conference on Information Technology and Intelligent Control (CITIC 2022), 2022, Kunming, China

Abstract

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.

Citation Download Citation

Deli Zhang and Na Wang "Research on turbine vibration fault diagnosis expert system based on rough set theory", Proc. SPIE 12346, 2nd International Conference on Information Technology and Intelligent Control (CITIC 2022), 123460F (27 September 2022); https://doi.org/10.1117/12.2653304

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