Recently, the repair and maintenance of structures has been necessary to prevent these structures’ sudden collapse and to prevent human and financial damage. A natural factor in marine environments that destroys structures and reduces their life is the presence of chloride ions. So regular health monitoring of concrete coastal buildings for on-time repair is essential. This study investigates the performance of the power spectral density (PSD) method as a non-destructive damage-detection method to monitor the location and amount of damage caused by chloride ions during a structure’s life using different approaches according to life-cycle assessment (LCA) and life-cycle cost assessment (LCCA). In this regard, chloride corrosion damage dependent on zone distance from seawater was first calculated to obtain the service life of each part of a coastal concrete bridge according to the conventional method. Based on rebar corrosion each year, the next stage forecasted the bridge’s concrete deterioration. The PSD method monitored the annual loss of reinforcement cross-sectional area, changes in dynamic characteristics such as stiffness and mass, and the bridge structure’s life using sensitivity equations and the linear-least-squares algorithm. Finally, according to the location and quality of damage in each year of bridge life until the end of life, LCC and maintenance and repair costs of the PSD method were compared with the conventional method. The results showed that this strategy was very effective at lowering and optimizing the costs of maintenance and repair caused by chloride corrosion.

Recent catastrophic events have aroused great interest in the scientific community regarding the evaluation and prediction of the structural response along the life cycle of infrastructures. Efforts are put into developing adequate health monitoring systems to help prevent future human life and economic losses. Here, two non-destructive damage detection methods are presented: the Frequency Response Function-based and the Spectral Density Function-based methods. The damage detection performance of both methods is compared through a particular case study, where different damage scenarios are analyzed in a 2D truss bridge. The reliability of each method is studied in terms of different prediction errors. Numerical results show that the PSD method for damage detection on a steel truss bridge structure provides more accurate and robust results when compared to that based on FRF. Keywords: Structural Health Monitoring, Power Spectral Density Function, Frequency Response Function, Construction, Structures, Damage detection, Non-destructive