Structural damage identification using static test data and changes in frequencies

A structural damage identification algorithm using static test data and changes in natural frequencies is presented in this paper. To locate damage in the structure, the Damage Signature Matching (DSM) technique is improved through a proper definition of Measured Damage Signatures (MDS) and Predicted Damage Signatures (PDS). The effect of damage severity can be eliminated effectively as the result that the first-order approximation of changes in static deformation and natural frequencies are employed jointly in the damage signatures. The damage location, then, can be detected successfully by matching MDS with PDS. After obtaining the possible damage location, an iterative estimation scheme for solving non-linear optimization programming problems, which is based on the quadratic programming technique, is proposed to predict the damage extent. A remarkable characteristic of the present approach is that it can be directly applied in the cases of incomplete measured data. The correctness and the effectiveness of the algorithm are proved by two examples: A planar truss model with the numerically simulated data and a beam with two-fixed ends, of which the static response and the natural frequencies are obtained experimentally. The results show that the proposed algorithm is efficient for the damage identification.