Intelligent bridge monitoring system operational status assessment using analytic network-aided triangular intuitionistic fuzzy comprehensive model

The extensive construction of bridge health monitoring (BHM) systems has made it challenging for the authorities to manage them centrally. The reliable operational status of BHM systems is vital to obtaining accurate monitoring data and evaluating the condition of bridges. To evaluate the operational status of these systems, this study established an assessment model that integrates the triangular intuitionistic fuzzy analytic network process (TIFANP) and the triangular intuitionistic fuzzy comprehensive evaluation (TIFCE) method. Firstly, an evaluation index system was established for the operational status of a BHM system. Factors such as system stability, data reliability, system maintenance, early warning, and human-computer interaction were comprehensively considered. Secondly, the evaluation indicator weights were assigned using TIFANP. The system evaluation rating levels were divided into four grades, and the membership and non-membership functions of the evaluation indicators for these rating levels were constructed based on TIFCE. Finally, the effectiveness of the proposed method was verified based on a case study. This is the first time that an operational status assessment method suitable for in-service BHM systems has been proposed. The results show that the TIFANP better accounts for the relationships for non-independence and interactions among the evaluation indicators. Hesitations in the decision-making process were quantified, making the weight allocations more accurate. The proposed method outperforms other comparison methods and can be used to evaluate the operational status of BHM systems in a more scientific and objective manner.