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We conducted a long-term monitoring experiment on the Lutuanxilu Bridge located in Changping District of Beijing, employing our recently developed real-time bridge monitoring system based on the Guralp CMG-6TD broadband seismometer. We identified the modal parameters with the stochastic subspace identification( SSI) algorithm,and continuously monitored the temporal velocity variation with coda wave interferometry.The results show that:( 1) the highly sensitive Guralp CMG-6TD broadband seismometer,which records the three-component vibration signal within broad frequency range,is well suited for long-term bridge health monitoring.( 2) With the continuous vibration signal from ambient excitation,the stochastic subspace algorithm can robustly identify the low-order modal parameters and the coda wave interferometry can accurately monitor the tiny velocity variation.( 3) The elastic modulus of bridge materials changes significantly associated with varying temperature,leading to diurnal velocity variation with amplitude of approximately 1%. The velocity variation shows strong negative correlation with temperature fluctuation. Meanwhile,the modal frequencies remain quite stable,suggesting that the velocity variation may be a more sensitive quantitative damage index.( 4) While the modal frequencies reflect the integrated health status of the bridge,the velocity variation can be utilized to monitor the local elastic modulus. Therefore,it is crucial for bridge health monitoring to continuously monitor the two key damage indexes under ambient excitation.
We conducted a long-term monitoring experiment on the Lutuanxilu Bridge located in Changping District of Beijing, employing our recently developed real-time bridge monitoring system based on the Guralp CMG-6TD broadband seismometer. We identified the modal parameters with the stochastic subspace identification ( SSI) algorithm, and continuously monitored the temporal velocity variation with coda wave interferometry. The results show that :( 1) the highly sensitive Guralp CMG-6TD broadband seismometer, which records the three-component vibration signal within broad frequency range, is well suited (2) With the continuous vibration signal from ambient excitation, the stochastic subspace algorithm can robustly identify the low-order modal parameters and the coda wave interferometry can accurately monitor the tiny velocity variation. (3) The elastic modulus of bridge materials changes significantly associated with varying temperature, leading to diurnal veloc畏 variation with amplitude of approximately 1%. The velocity variation shows strong negative correlation with temperature fluctuation. suggesting that the velocity variation may be a more sensitive quantitative damage index. (4) While the modal frequencies reflect the integrated health status of the bridge, the velocity variation can be utilized to monitor the local elastic modulus.