An integrated linguistic Pythagorean fuzzy decision-making approach for risk analysis of offshore wind turbine

Abstract

The evaluation of risk factors within the context of condition-based maintenance (CBM) for offshore wind turbines has been a challenging issue. In this paper, a novel risk analysis method that combines the fuzzy weighted with zero inconsistency (FWZIC) technique and the DEMATEL method under the linguistic Pythagorean fuzzy environment is proposed. Firstly, 75 risk factors linked to offshore wind turbines are identified by leveraging analysis and prior literature, which are modeled using linguistic Pythagorean fuzzy sets (LPFSs) to facilitate the complexity of expert opinions in the face of uncertainty. Then, the hybrid expert weight calculation method and the FWZIC-based criteria weight calculation method are introduced to determine the weights of the experts and the criteria while considering uncertainty. Next, the extended DEMATEL method under the linguistic Pythagorean fuzzy environment is adopted to determine the significance and influence of the pinpointed risk factors, and an illustrative cause–effect diagram is crafted to dissect the interconnections between these factors. Through this intricate analysis, the cause factors and effect factors specific to offshore wind turbines are identified, and the results obtained from the proposed method are validated through sensitivity analysis and comparative analysis. The results of this study could provide valuable recommendations and references for the implementation of CBM in offshore wind turbines.