Effective early-warning tool in detecting structural anomalies and preventing progressive collapse

Addressing the challenges of structural monitoring, this research introduces a cutting-edge method for Structural Health Monitoring (SHM). The study investigates the correlation between deformation work patterns occurring during random damage scenarios. The method focuses on deformation work and related parameters as key indicators of structural health, showing promising results in the early detection of potential issues. Despite evidence indicating the robust nature of structurally complex systems in parallel arrangements, no specific study has been conducted in the case of mixed systems presenting series and parallel elements configurations . In this study, the structural response of a set of systems made of rods in series and parallel arrangements has been analyzed. Damage to the system, occurring randomly on elements, is considered, and an energy-based metric is employed.The purpose of the study is not only to explore the behaviour of rods working in the coupled mechanism, but also to identify relevant trends in the case of certain load patterns or geometrical configurations in order to design an effective targeted monitoring system. The findings highlight the feasibility of this approach in detecting structural anomalies, underscoring its potential as an effective early-warning system for preemptive maintenance and contributing to the improvement of structural integrity and safety.