Abstract This present thesis focuses on Structural Health Monitoring (SHM), defined as a process to develop strategies in order to identify an abnormal behavior such as a damage, in structural system. SHM can be considered under two approaches, namely the Inverse and Forward. The first one is associated with numerical models, while the second one with artificial intelligence and pattern recognition. The advantage of computational simplicity motivated the use in this thesis of forward SHM approach. The forward SHM approach was applied to the chosen case study, the Overpass Z24, located in Switzerland, which was subject to a controlled demolition. In this dissertation, methods were used to define relations between the structural actions, such as temperatures, and the responses, acquired from the sensors, such as modal frequencies.