# Automatic Identification of Bridge Vortex-Induced Vibration Using Random Decrement Method
## 4 Application to the Xhiounen Bridge
### Identification of VIV  
In order to obtain the threshold to identify VIV, the acceleration data without VIV were selected out by visual inspection ofthe data. These data included those on January 1 (wind velocity 2.5\(\sim\)14.5 m/s), January 17 th (wind velocity 0.5-12 m/s), and May 10 (wind velocity 2.5-16 m/s), May 14 (wind velocity 0.5-12 m/s), and August 24 (wind velocity 2-15 m/s). For the data at the two measurement positions of quarter span and half span, the banded filtering process with the range of 0.07-0.7 Hz was performed at first. The data was then processed by the random decrement method, with the 10 min signal as input segment and the output segment length of 300 s. The threshold was calculated from the COV of peak values for each output segment. The thresholds of the two measuring points were shown in Table 4. \begin{table}
\begin{tabular}{c c c} \hline
**Measuring point position** & Quarter span & Half span \\ \hline
**Value of threshold** & 0.0653 & 0.0245 \\ \hline \end{tabular}
\end{table} 
Table 4: COV threshold for automatic identification of Vortex-induced vibration (VIV). Figure 18: Wind rose diagramd XHM Bridge in different months: (**a**) January; (**b**) May; (**c**) August. \begin{table}
\begin{tabular}{c c c c c c c c c} \hline
**Mode Order** & **1 st** & **2 nd** & **3 rd** & **4 th** & **5 th** & **6 th** & **7 th** & **8 th** & **9 th** \\ \hline Simulation (Hz) & 0.101 & 0.133 & 0.184 & 0.229 & 0.274 & 0.324 & 0.375 & 0.428 & 0.482 \\ Measurement (Hz) & 0.098 & 0.134 & 0.183 & 0.232 & 0.275 & 0.324 & 0.378 & 0.433 & 0.494 \\ Deviation (\%) & 2.08 & 0.75 & 0.54 & 1.31 & 0.36 & 0.00 & 0.8 & 1.17 & 2.49 \\ \hline \end{tabular}
\end{table} 
Table 3: Comparison between analytical and identified modal frequencies of XHM Bridge. During the identification stage, all measured acceleration responses in January, May, and August are processed by random decrement method. If the COV for a segment is smaller than the threshold, it is considered as a VIV; otherwise it will be classified as wind buffeting. VIV is found on the first nine vertical modes of the XHM Bridge. By taking the data in January 4 as an example, as shown in Figure 19, it can be seen that VIV occurs at about 02:00 from the acceleration data at quarter span, while the data at half span does not indicate VIV. Another method based on artificial neural network (ANN) and the novelty detection technique is employed for automatic identification of VIV [24; 33]. In this method, the power spectral density of the acceleration response was first used to construct a feature vector, and then a feature vector for random vibration was fed to ANN to train the model. In the test stage, any deviation from the expected output was classified as VIV. The results obtained from the novelty detection technique were shown in Figure 20. Again, the VIV is automatically detected from the acceleration response at quarter span. The acceleration responses and the corresponding power spectrum at 02:00 were shown in Figure 21. In this figure, a single-mode vibration of the steady-state amplitude was observed at quarter span, and the predominant frequency is 0.1831 Hz, which corresponds to the third vertical bending  
Figure 19: Acceleration responses and the identification results on January 4: (**a**) Acceleration at quarter span; (**b**) acceleration at half span; (**c**) COV and threshold at quarter span; (**d**) COV and threshold at half span. Figure 20: Novelty index obtained using artificial-neural-network (ANN)-based novelty detection: (**a**) Quarter span; (**b**) half span. mode of the girder. The vibration of half span behaves as random vibration. It can be seen from Figure 17 that the position of half span is close to the nodal point of the vibration mode, so the VIV of the third mode cannot be detected from the acceleration responses at the position of half span, and that is the reason why the power spectrum of the two points are different.