# Development and Field Validation of Wireless Sensors for Railway Bridge Modal Identification
## 3 Field Test on the Bressana Railway Bridge
\begin{table}
\begin{tabular}{c c c} \hline \hline
**Feature** & **Wired Velocimeters** & **Wireless Sensor Nodes** \\ \hline Number of axes & 2 & 2 \\ Maximum tilt & 10\({}^{\circ}\) vertical, 2\({}^{\circ}\) horizontal & Compensated through static \\  & & acceleration measurements \\ Dimensions & 180 \(\times\) 170 \(\times\) 90 mm & 91 \(\times\) 70 \(\times\) 38 mm \\ Weight & 1500 g & 240 g \\ Power supply source & 12 V & Energy harvesting \\ Data transmission & Wired & Wireless \\ Cost & 350 \(\upc\) & Approximately 200 \(\upc\) \\ \hline \hline \end{tabular}
\end{table} 
Table 3: Comparison between main features of wired velocimeters and wireless sensor nodes. Figure 6: Wireless monitoring system mounted on the bridge: (**a**) Wireless sensor positioned in correspondence of a wired velocimeter; (**b**) gateway installed on a balcony of the railway deck. harvesting system is able, in the worst possible scenario of consumption for the board, to balance the consumption and recharge the battery with a current value up to 40 mA. Moreover, it can be noticed that the mean current flowing in the battery in this worst-case scenario is negative considering the whole day, meaning that overall recharging current is always higher than the consumption one. This represents a very significant assessment of the energy harvesting system in providing a long autonomy to the wireless sensor nodes for continuous monitoring activities. The wireless devices collected during the field test on the Bressana bridge showed several acceleration time histories triggered both by the train passages on the railway deck and probably by some passages of heavy vehicles on the upper deck. An example of these is reported, respectively, in Figures 8-10. The time history represented in Figure 8, representing the bridge response to the train passage, is characterized by higher maximum acceleration values with respect to the ones in Figure 10 (related to the traffic excitation) and by a trend from which the structural damping can be readily appreciated. Figure 9 represents a part of the structure-free response contained in the time history of Figure 8. The main excited bridge natural frequency in that case (approximately 9 Hz) can be easily identified. The time history acquisition triggered by the road traffic excitation (Figure 10) is characterized by lower maximum acceleration values, in the order of one tenth of the previous ones. This last result, obtained thanks to the adoption of the very low noise MEMS accelerometer, is significant since it allows the use of the developed system also on conventional highway viaducts (where the bridge excitation is represented only by road traffic) for modal identification purposes. The acquired time histories were then processed offline as explained in Section 4. Figure 7: Exemplary acquired data representing the energy harvesting system charging the sensor node battery during one day (23 February 2023). Figure 8: Exemplary acceleration time histories acquired by the wireless sensors triggered by the train passage on the lower deck. Figure 9: Exemplary acceleration time histories acquired by the wireless sensors triggered by the train passage on the lower deck. Focus on the free response of the structure after the excitation.