FIR and IIR filtering and data driven stochastic subspace identification for the continuous dynamic modal parameter identification of cable stayed bridge

With the advancement in technology, the need for an effectual health monitoring of structures, specially the long span cable stayed bridges have increased the quest for a continuous monitoring of these cable stayed bridges so that, an accurate and reliable data is collected from these sophisticated instruments installed at these bridges and then analyzed in a very effective way. Therefore in this paper the FIR and IIR filter are introduce one by one, to the dynamic data obtained from real life cable stayed bridge. Then the reconstructed signal obtained after performing the filtering was used for the continuous modal parameters identification such as Frequency and Damping Ratio using the improved Data Driven Stochastic Subspace Identification (DATA-SSI). For this purpose the real life data has been collected form Sutong cable stayed Bridge, and the proposed technique was applied to this real life data. The results shows that the proposed method gives better results and the modal parameters obtained by this technique are more accurate and consistent and provides better representation of real life bridge health monitoring.