Damage detection of structures with parametric uncertainties based on fusion of statistical moments

摘要

This study proposes a fusion of statistical moments of structural dynamic response by combining the fourth-order statistical moment of displacement with the eighth-order statistical moment of acceleration for the damage identification of structures. This fusioned statistical moment is adopted in least-squares-based deterministic and stochastic model updating of a benchmark 12-storey reinforced concrete (RC) building structure in the laboratory. Results obtained compare favorably with observations made on the structure during the experiment. The proposed fusioned statistical moment is numerically found more accurate and robust to noise effect than existing moments. Both the proposed deterministic and stochastic methods based on the fusioned moment can provide accurate and robust predictions for the damage identification of the benchmark structure. (C) 2018 Elsevier Ltd. All rights reserved.