Enhancing Structural Health Monitoring with Probabilistic Analysis: A Case Study on a Bridge Reclaimer

Resumo

Bridge reclaimers play a crucial role in industrial operations, yet their structural integrity is often threatened by environmental exposure and cyclic loading. Meanwhile, traditional deterministic methods may overlook early signs of degradation, compromising maintenance strategies. In this context, this study introduces a probabilistic approach to structural health monitoring (SHM), emphasizing its advantages over conventional techniques. Visual inspections revealed cracks in critical regions of a bridge reclaimer’s box girder that deterministic simulations failed to predict. In addition, finite element analysis was employed to define key monitoring points, followed by the acquisition of hourly stress and strain data over fifteen days. Using the VibraConf (VcE) software and the Probabilistic Condition-Based Maintenance (PCBM) methodology, failure probabilities and reliability indices were computed. The analysis identified a significantly higher probability of failure in the box girder diaphragms, precisely where physical cracks were observed. These findings highlight the limitations of deterministic assessments and demonstrate the value of probabilistic simulations in forecasting failures and prioritizing maintenance. By integrating field observations with numerical and probabilistic tools, this case study provides a robust framework for proactive asset management and more reliable SHM practices.