Abstract Summary
A recent large campaign of vibration measurements has been conducted on a hospital building in Italy to perform operational modal analysis of the structure in order to update a representative numerical model. Subsequently, this latter will be used to carry out a vulnerability analysis of the whole structure. The building is composed by 41 structural subsystems separated by technical joints. At the same time, several subsystems are interconnected in different manner especially through a roof sustained by large-span wooden beams. Long acceleration measurements have been acquired by wireless sensors located at the top level of the building in two days testing. During the tests conducted in operational conditions, in different locations of the building air conditioning systems and elevators were functioning affecting the measures in the high frequency content. This work aims to investigate on the structural identification of the complex structure, on the effectiveness of technical joints and on the influence of the wooden roof connection on the dynamic structural behavior. In pursuing these goals, the main challenge is considering the influence of air conditioning and elevator systems on the natural frequency identification of the structure. Therefore, an Artificial Neural Network algorithm trained on numerical model results is implemented to reconstruct the unknown dynamic load which can be considered as white noise smeared in some intervals by external disturbances (colored noise). By this approach, the network should be able to recognize the time ranges in which are operative the external machines.
