# Dynamic Identification on an Irregular Structure
## 4 Identification Results and Up-Dating Procedure
### Structural Dynamic Identification
The modes relating to the first frequencies all have a flexural-torsional behavior with an evident torsional component, due to the particularity of the analyzed structure, constituted by two main asymmetrical bodies, as widely described above. Figure 11 shows the first mode characterized by a torsional component and a bending component along the x axis, Figure 12 plots the second mode characterized by a torsional component and a bending component along the x axis, and Figure 13 shows the third mode characterized by a torsional component and a bending component along the y  
It is worth noting that the results show a quite high repetitiveness of the frequency values and that the complexity and irregularities of the structure need a high number of sensors to accurately identify the mode shapes. The chosen position for the accelerometers corresponds to the opposite vertices of the polygons, the rectangle, and the rhombus, for each floor. In fact, it was not possible to insert the sensors as described in all the building corners on each floor, due to the impossibility of accessing to some rooms. Several setup configurations have been analyzed by excluding in the identification procedure some sensors and evaluating the frequency values and the mode shapes. In Table 3, the frequency values of first three modes estimated for the effective setup configuration and those established by excluding some sensors are summarized. In detail, Test 1.a has been performed by excluding the sensors installed in nodes 46, 38, 30 and 22 (see Figure 12) and, Test 1.b by excluding the sensors installed in nodes 14, 25, 33, 31, 23, 39 and 41. It has been verified that the 'limited' configurations also allow for the identification of the first frequencies, unless if it has been necessary to reduce the number of reference channels to four. The experimental results obtained for the installed sensors are considered for the updating procedure of the FE model, to obtain an accurate numerical model for the vulnerability evaluation. The experimental acquisitions have been analyzed by means of OMA method by decreasing the number of considered sensors, with the final aim of verifying how the number and location of sensors may influence the identification process for this complex and irregular structure. Thus, three different setups of sensors have been examined; the results show that a reduction in sensors does not significantly influence the identified  
Figure 13: Third experimental mode is a torsional-bending mode along y axis (in green the un-deformed configuration and in blue the mode shape): (**a**) 3D view; (**b**) plan view. \begin{table}
\begin{tabular}{c c c c} \hline \hline \multirow{2}{*}{**Mode**} & \multicolumn{2}{c}{**Frequency Test 1**} & \multicolumn{2}{c}{**Frequency Test 1.a**} & \multicolumn{2}{c}{**Frequency Test 1.b**} \\  & **(Identification with All Sensors)** & **Placed at Nodes 46, 38, 30, 22)** & **(Identification without Sensors Placed at Nodes 41, 33, 25, 14, 39, 31, 23)** [Hz]** \\ \hline
1 & 5.17 & 5.12 & 5.13 \\
2 & 7.68 & 7.66 & 7.69 \\
3 & 8.86 & 8.71 & 8.78 \\ \hline \hline \end{tabular}
\end{table} 
Table 3: Comparison between the identified frequency values for different set-up configurations. frequency values, which manifest very low percentage variations; however, the most significant modification is recorded on the modal shapes. Indeed, the identified modal shapes change by considering a reduced number of accelerometers, and this reduction does not permit us to identify with certainty the shape typology, and thus the comparison with the dynamic FE model behavior worsens.