Research on Fault Diagnosis of Turbine Based on Similarity Measures between Interval-Valued Intuitionistic Fuzzy Sets

This paper presents a novel fault diagnosis method of turbine based on interval-valued intuitionistic fussy sets (IVIFSs) theory. In this paper, the concept of IVIFS is introduced, and the distance between two IVIFSs is defined. Then, the similarity degree between the detecting sample and the knowledge of system fault is evaluated in the fault diagnosis of turbine vibration by means of the similarity measures among IVIFSs. The larger the value of similarity measure, the more the similarity between the detecting sample and a type of fault knowledge. The value of similarity measure is ranked and the most possible type of vibration fault is determined according to the similarity degree. The example of steam turbine generator setpsilas fault diagnosis demonstrates the validity and reasonability of the proposed method.