A three-way decision method with probability dominance relation in interval-valued hesitant fuzzy environment for marine steam turbine fault diagnosis

As an important measure to solve the multi-attribute decision-making (MADM) problems, the establishment of three-way decision (3WD) approach has been adopted not only stay at the theoretical level, but also applied to various practical problems. However, there exists a research gap of employing three-way decision (3WD) approach to enrich fault diagnosis based on interval-valued hesitant fuzzy environment (IVHF). To address these challenges, this paper proposes a neighborhood (δ,η) three-way decision (3WD) approach to solve fault diagnosis under the IVHF environment. First, the relative loss function (RLF) is considered as a wonderful substitution for the loss function, which usually serves as a conventional tool to consider the losses more comprehensively. Furthermore, an interval-valued hesitant fuzzy weight averaging operator is detected when creating the aggregated loss function. Moreover, a neighborhood (δ,η) probability dominance similarity relation is taken instead of the equivalence relation, which is regarded as an effective way to calculate the outranked class. Finally, the proposed method is verified by a marine turbine fault diagnosis case. Results of parameter analysis and comparison analysis show that the proposed approach can diagnose the fault of marine turbine rationality and stability.