Damage identification based on Baysian fusion of global and local information

The damage identification using both global and local information is a possible method to increase accuracy of damage detection results. In this paper a new method based on Bayesian fusion of global and local information is proposed. The Bayesian probability model associated with frequencies, displacement mode shapes and strain modes are set up. The static strain information also is used as the prior information in the Bayesian model. In order to reduce computational cost of a complex structure, the strain energy damage index is firstly used to find the potential damage ranges. Then the exact damage elements are detected by the sequence elimination method proposed in the paper. The experiment on a 20-bay planar rigid truss structure is carried out to illustrate the damage detection ability of the proposed approach.