## 5 Discussion and Conclusions  
Nowadays, many dynamic identification techniques are based on the evaluation of changes of structural parameters (frequency, modal shape, equivalent viscous damping) to localize possible damage that has occurred on a monitored structure during a critical event. Mode curvature variations are strictly associated with structural damage; indeed, mode curvature is used as a control parameter for damage localization after an earthquake. Scientific literature shows that most of the methods for structural damage detection require a large number of sensors placed on the monitored structure. This involves high costs if the monitoring system is extended, continuous, and covers many structures. Figure 23: Results for the event that occurred on 9 April 2009 at 02:34: (**a**) ground accelerometric recordings; (**b**) response spectrum; (**c**) curvature differences between the selected time-instants B and A.  
Figure 24: Results for the event that occurred on 9 April 2009 at 03:14: (**a**) ground accelerometric recordings; (**b**) response spectrum; (**c**) curvature differences between the selected time-instants B and A.  
Figure 25: Results for the event that occurred on 9 April 2009 at 04:32: (**a**) ground accelerometric recordings; (**b**) response spectrum; (**c**) curvature differences between the selected time-instants B and A. Most of the vibration-based procedures and methods for damage detection on existing structures are based on the evaluation of just stationary or \"stationarized\" structural modal parameters. The band-variable filter allows for the separation of the variable contributions of each mode of vibration within both linear and nonlinear fields. The capability to isolate each individual contribution allows us to better understand how damage propagates through the structure, and which are the main modes involved within the damage process during the nonlinear behavior of each excited structure. In this paper, the upgrade of an existing procedure for damage detection on framed structures subjected to strong motion earthquakes has been presented. The results show the possibility of localizing structural damage and identifying the most damaged floor(s) after an earthquake through the analysis of the curvature difference between two time-instants (the minimum fundamental frequency time-instant and the reference time-instant before the event). The revised Curvature Evolution Method has been successfully applied both to numerical models and on a real case study. The results retrieved for all of the analyzed case-studies showed that the curvature difference is systematically able to localize the most damaged floor. Moreover, the correlation between maximum inter-story drift and maximum curvature variation has been defined. With reference to the empirical relationship, further studies are necessary to better understand how it could be possible to generalize results and to define new analytical equations to relate modal curvature and inter-story drift. This last step is important to evolve the method towards a third level, according to the Rytter classification of structural damage. Compared with the original version of the CEM method, by analyzing this correlation it could be possible to obtain more accurate information about both the location and severity of any structural damage. The capability of the modified CEM for damage detection on framed damaged structures has been validated using accelerometric data acquired from a real structure (Navelli town hall) monitored during the L'Aquila 2009 seismic sequence. With reference to the Navelli accelerometric dataset, it has been demonstrated that the damaged level identified by using the proposed approach agrees with the damage observed at the first floor of the monitored structure using visual inspection. The proposed method has been applied to structures with a predominantly shear dynamic behavior, representative of European constructions.