Modal Parameter Identification of Bridge Using Data-driven Stochastic Subspace Algorithm

One certain self-anchored suspension bridge model test is taken as the research background, combination data-driven stochastic subspace identification algorithm with improved stabilization diagram, the modal parameters of bridge structure under ambient excitation are identified effectively. For solving the problems of system order-determination in time-domain method, noise and the identification and elimination of false modal parameters, three-step method is adopted to identify modal parameters of bridge structure more accurately. The proposed method is verified by the experiment of one certain self-anchor suspension bridge model test. The modal parameters of this model bridge are identified from the measurand under different data acquisition, and the identified modal parameters are compared with the result of FEM and DASYLab. The validity, practicability and superiority of the proposal method are verified. The results show that the data-driven stochastic subspace identification algorithm can be used in the real bridge engineering to identify the modal parameters.