A fast damage locating approach using digital damage fingerprints extracted from Lamb wave signals

摘要

A fast damage locating approach using digital damage fingerprint data, extracted from raw Lamb wave signals and accommodated in a damage parameters database (DPD), was developed in this study. A new inultilayer feedforward artificial neural network was designed and trained with the DPD under the supervision of an error-backpropagation algorithm. Assisted by an active system for online structural health monitoring, the proposed method was validated by locating actual delamination and through-thickness holes in quasi-isotropic CF/EP (T650/F584) composite laminates. Compared with a quantitative methodology for evaluating full damage parameters developed in an earlier study (Su and Ye 2003 J. Intell. Mater. Syst. Struct. 16 97-111), the present approach performs damage evaluation much more quickly and cost-effectively by determining damage location only.