Health Evaluation of Box Girder Bridge Based on Intuitionistic Fuzzy Analytic Hierarchy Process and Cloud Model

Vollständiger Abstract

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To improve evaluation methods for assessing the health condition of variable cross-section box girder bridges during the operational phase, this paper proposes an integrated approach that combines the Intuitionistic Fuzzy Analytic Hierarchy Process (IFAHP) with the cloud model. This approach enables a more systematic and objective classification and weighting of evaluation indicators and is particularly suitable for complex, multi-level decision-making problems involving uncertainty and fuzzy information. In addition, it provides a visual representation of the evaluation results for different indicators. To ensure a rigorous and reliable assessment, multi-source information, including technical inspection data, structural inspection results, and automatic monitoring records, was integrated to comprehensively evaluate the overall health condition of the bridge. Indicator weights at all hierarchical levels were determined based on expert scoring and relevant regulatory standards. The results indicate that the three primary indicators exert relatively balanced influences on bridge health. Among the tertiary indicators, the technical condition of the box girder and concrete strength were identified as having the most significant impact on the health assessment. Based on the cloud model-based integration of the evaluation results for all indicators, the overall health condition of the bridge was assessed as slightly better than the “Good” level, indicating a relatively low operational risk. This finding suggests that the bridge is generally in sound condition and can maintain normal operation. Overall, the results confirm the effectiveness and applicability of the integrated IFAHP-cloud model approach for evaluating the health condition of bridges during their service life.