A Neutrosophic Set Based Fault Diagnosis Method Based on Power Average Operator (Poster)

Fault diagnosis is an extensively applied issue for checking and identifying the faults of objects, which comes from the combination of various theories and technologies. The contributing factors of a fault are complex owing to the uncertainty of the actual environment and the relative importance of fault criteria. Consequently, these causes fails to be considered felicitously in many conventional methods. In this paper, a neutrosophic set based fault diagnosis method based on power average operator is proposed to resolve this matter. The neutrosophic set generated from multi-stage fault sample data would be aggregated via the power average operator, then by using the defuzzification of neutrosophic set, the fault diagnosis results could be obtained. The combination of power average operator and neutrosophic set can be used for handling the relative importance of criteria, and the uncertainty of fault data. Finally, an illustrative example was provided to demonstrate the reasonableness and effectiveness of the proposed method by comparing with the existing methods.