A large number of civil structures were designed according to old seismic code that do not meet current safety standards. They may also suffer from ageing and deterioration induced by environmental factors such as corrosive agents and earthquakes. A methodology has been developed to assess the current state of existing structures using vibration-based structural health monitoring. This technique has attracted civil engineering community recently. Vibration-based, non-destructive damage identification uses changes in the dynamic characteristics of the structure to identify damage. Full or large-scale dynamic tests of structural specimens provide unique opportunities to evaluate and validate these methods under realistic conditions, i.e. with the same level of measurement noise, estimation uncertainty and modelling errors, which are observed as in situ conditions. In this paper, we have studied the behaviour of existing structures and the models casted in the lab. Experimental determination of the dynamic characteristics of the model of RCC building under different levels of damage has been used to develop correlation between damage in the models of RCC buildings with its known dynamic characteristics using artificial neural network models.
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