Modal Parameters Identification Study For Bridge Structure

Bridge Structural Health Monitoring has been getting more and more attention and promotion. Structural modal parameter identification is the prerequisite and basis of health monitoring, and is also one major part of the structural dynamic identification, so it is importance in the whole health monitoring system. As one of the modal parameter identification method under the ambient excitation, stochastic subspace identification can meet the online and real-time monitoring requirements of bridge health monitoring. Taken the bridge structural health monitoring as the research background, the application of data-driven stochastic subspace modal parameters in the bridge structure identification is studied. The main studies are listed as followings:1. The theory and algorithm of stochastic subspace identification are summarized. Both covariance-driven and data-driven stochastic subspace parameter identification methods are systematically described and compared their advantages and disadvantages. Data-driven stochastic subspace identification methods is selected for its fast calculation and any other advantages, and its algorithm and three main steps are also carried out.2. The identified system order is the only one parameter to determine in the data-driven stochastic subspace algorithm. After the study of stability diagram for modal parameters, the stability diagram method is adopted to estimate the system order. Then the classification of the calculating parameters for stability diagram is carried out,, and some suggestions for these parameters setting is put forward.3. A program basing on data-driven stochastic subspace algorithm is compiled on the Matlab platform to identify the bridge structural modal parameters, and it is verified by the experiment of one certain self-anchor suspension bridge model. The modal parameters of this model bridge are identified from the measurand under different testing conditions, 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.