In this paper, a damage diagnostic algorithm based on a null subspace method, considering environmental variability is proposed. The basic idea is that the changes in the measured features due to environmental variations are accounted and that they are different from those due to structural damages. The damage indicator is proposed based on the reconstruction error of the Hankel autocorrelation matrix. Novelty analysis is adopted to decide whether the features indicate a departure from previously estimated normal conditions or not. Numerical studies using ASCE benchmark problem and a beam girder indicate that the proposed algorithm is robust and capable of handling environmental variability and measurement noise.

Keywords: SHM, Damage detection, Null subspace, Environmental variability, ASCE benchmark structure.