Abstract
A fast damage locating approach using digital damage fingerprint data, extracted from rawLamb wave signals and accommodated in a damage parameters database (DPD), wasdeveloped in this study. A new multilayer feedforward artificial neural network wasdesigned and trained with the DPD under the supervision of an error-backpropagationalgorithm. Assisted by an active system for online structural health monitoring, theproposed method was validated by locating actual delamination and through-thicknessholes in quasi-isotropic CF/EP (T650/F584) composite laminates. Compared with aquantitative methodology for evaluating full damage parameters developed in an earlierstudy (Su and Ye 2003 J. Intell. Mater. Syst. Struct. 16 97–111), the present approachperforms damage evaluation much more quickly and cost-effectively by determining damagelocation only.
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