Abstract
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 multilayer 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.
Original language | English |
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Pages (from-to) | 1047-1054 |
Number of pages | 8 |
Journal | Smart Materials and Structures |
Volume | 14 |
Issue number | 5 |
DOIs | |
Publication status | Published - 1 Oct 2005 |
Externally published | Yes |
ASJC Scopus subject areas
- Signal Processing
- Atomic and Molecular Physics, and Optics
- Civil and Structural Engineering
- Materials Science(all)
- Condensed Matter Physics
- Mechanics of Materials
- Electrical and Electronic Engineering