PSI - Issue 62

Laura Ierimonti et al. / Procedia Structural Integrity 62 (2024) 832–839 Author name / Structural Integrity Procedia 00 (2019) 000 – 000

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involves summing over the unwanted variables to obtain the marginal distribution of interest (in this case, E and Z). This method is a key step in simplifying computations in BN, especially when dealing with a large number of variables, making the calculations more efficient. Finally, BN allows forward and backword propagation to update the probabilistic information of any node given evidence. 3. The methodology The core of the proposed framework relies on continuously updating the knowledge regarding the health status of the bridge over time, utilizing the outcomes of the DBN. The amalgamation of all risks associated with each node can offer insights into the overall risk assessment and the most probable Damage Model (DM) for the monitored Damage Scenario (DS) within the bridge context. In a broader sense, the suggested framework encompasses the following procedural steps (Fig. 1): 1) Selection of potential Damage Scenarios (DS) and corresponding damage models (node DM) that can be effectively monitored utilizing the existing SHM system. It is noteworthy that the same sensors may have the capability to monitor one or multiple DS. 2) Novelty detection (node NY, with attributes yes or no). Subsequently, the acquired data undergoes a comprehensive analysis and preprocessing stage. This involves removing environmental effects and interferences from the original signals, enabling the anomaly detection (Novelty), i.e., data-driven detection of abnormal or unusual observations.

Fig. 1. The methodology: a schematic representation.

3) Bayesian model class selection for each DS j . In this phase, the most likely DM is determined, leading to evidence or to update conditional probabilities in the DS-dependent DM-SHM node. 4) Establish the severity of damage (low, medium, high) on the basis of the results of the model updating, i.e., node S-SHM. 5) If an on-site inspection is not performed, proceed to step 8. If an on-site inspection is conducted, along the inspected DL, it is essential to establish a correlation between the observed defects and the monitored DM (see Section 2.1). This correlation is based on expert knowledge and may lead to prioritizing DMs by inferring the node DM-VI. 6) Establish the severity of damage (low, medium, high) on the basis of the results of the visual inspection, i.e., node S-VI. 7) Risk evaluation as a consequence of model based SHM and VI evidence (node RI2). A risk index with attributes low, medium and high is evaluated on the basis of the results obtained from steps 4-6. 8) Risk evaluation (Node RI1). A risk index endowed with attributes low, medium and high is evaluated based on the results obtained from steps 1 and 7.