Multimodal exploitation and sparse reconstruction for guided-wave structural health monitoring

The presence of multiple modes in guided-wave structural health monitoring has been usually considered a nuisance and a variety of methods have been devised to ensure the presence of a single mode. However, valuable information regarding the nature of defects can be gleaned by including multiple modes in image recovery. In this paper, we propose an effective approach for localizing defects in thin plates, which involves inversion of a multimodal Lamb wave based model by means of sparse reconstruction. We consider not only the direct symmetric and anti-symmetric fundamental propagating Lamb modes, but also the defect-spawned mixed modes arising due to asymmetry of defects. Model-based dictionaries for the direct and spawned modes are created, which take into account the associated dispersion and attenuation through the medium. Reconstruction of the region of interest is performed jointly across the multiple modes by employing a group sparse reconstruction approach. Performance validation of the proposed defect localization scheme is provided using simulated data for an aluminum plate.

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