Issue 46

S. Ivorra et alii, Frattura ed Integrità Strutturale, 46 (2018) 203-215; DOI: 10.3221/IGF-ESIS.46.19 210 After the application of this filter, higher accelerations are detected in the N-S than E-W directions under ambient conditions (Fig. 9). In the same situation under bells’ forced excitation, higher accelerations have been detected in the N-S direction and lower accelerations in the E-W direction and it is clearly possible to see the effect of the sinusoidal wave generated by the swing of the bells. The N-S excitation starts when the bells start to swing, but in the E-W direction it starts 35 s later, the time necessary to activate the resonances of the torsional mode. When the bells stop, in the N-S direction it is observed the decay of the acceleration level but this phenomenon is practically delayed of 35 s. The absolute maximum acceleration registered after the application of the filter is 0.0180 g in the N-S direction and 0.0609 g in the E-W direction (Fig. 10). Figure 9. Acceleration recorded at the top of the tower under ambient vibrations after the application of a 0-100 Hz bandpass digital filter. Up: E-W direction. Bottom: N-S direction. Figure 10. Accelerations recorded at the top of the tower when all the bells are swinging after the application of a 0-100 Hz bandpass digital filter. Up: E-W direction. Bottom: N-S direction . O PERATIONAL M ODAL A NALYSIS n order to clearly identify the main frequencies of the tower and the main modes of vibration, the Operational Modal Analysis (OMA) technique has been applied using the ARTEMIS code [19]. This experimental modal analysis (Fig. 11) allows to statistically analyse the frequencies of the tower at each time instant and in each position of the accelerometers. Fig. 11 shows the geometric distribution of sensors and their records and the slave node restrictions to assure modal displacements geometrically compatible. Ambient recordings have been used to introduce the random excitation noise on the tower. Different statistical analyses have been applied, here the results of the stochastic subspace identification (SSI) technique are discussed, but similar results have been achieved by adopting other techniques. The SSI technique provides the following main frequencies: 1.30 Hz, 1.35 Hz and 2.69 Hz. Time [s] 700s 650s 600s 550s 500s 450s 400s 350s 300s 250s 200s 150s 100s 50s 0s Acceleration (g) 0 -0,001 -0,001 -0,002 -0,002 -0,003 -0,003 Time [s] 700s 650s 600s 550s 500s 450s 400s 350s 300s 250s 200s 150s 100s 50s 0s Acceleration (g) 0,004 0,002 0 -0,002 -0,004 Time [s] 420s 400s 380s 360s 340s 320s 300s 280s 260s 240s 220s 200s 180s 160s 140s 120s 100s 80s 60s 40s 20s 0s Acceleration (g) 0,015 0,01 0,005 0 -0,005 -0,01 -0,015 Time [s] 420s 400s 380s 360s 340s 320s 300s 280s 260s 240s 220s 200s 180s 160s 140s 120s 100s 80s 60s 40s 20s 0s Acceleration (g) 0,06 0,04 0,02 0 -0,02 -0,04 -0,06 I