The development of automatic guided wave interpretation for detecting corrosion in aluminum aircraft structural stringers is described. The dynamic wavelet fingerprint technique (DWFP) is used to render the guided wave mode information in two-dimensional binary images. Automatic algorithms then extract DWFP features that correspond to the distorted arrival times of the guided wave modes of interest, which give insight into changes of the structure in the propagation path. To better understand how the guided wave modes propagate through real structures, parallelprocessing elastic wave simulations using the elastodynamic finite integration technique (EFIT) has been performed. 3D simulations are used to examine models too complex for analytical solutions. They produce informative visualizations of the guided wave modes in the structures, and mimic the output from sensors placed in the simulation space. Using the previously developed mode extraction algorithms, the 3D EFIT results are compared directly to their experimental counterparts.


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    Title :

    Automatic multimode guided wave feature extraction using wavelet fingerprints


    Additional title:

    Automatische Merkmalsextraktion geführter Multimodewellen mittels Wavelet-Fingerabdrücken


    Contributors:


    Publication date :

    2009


    Size :

    8 Seiten




    Type of media :

    Conference paper


    Type of material :

    Storage medium


    Language :

    English




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