<p style="text-align: justify">Accurate defect characterisation has long been an essential yet challenging research issue in non-destructive evaluation (NDE). Current methods mainly include total focusing method (TFM), ray/diffraction tomography and data-driven methods. However, due to limited resolution and sensitivity, the defect images are often vague, and hence accurate defect characterisation can be problematic.&nbsp;Inspired by topology imaging and seismic full waveform inversion (FWI), a hybrid geometrical full waveform inversion (GFWI) method is proposed in this article to significantly improve the accuracy of defect reconstruction.&nbsp;This hybrid GFWI combines two steps: 1) a newly developed multi-mode topological imaging algorithm, to &nbsp;provide a high-resolution image of the volumetric and non-volumetric defects. &nbsp;2) a geometrical full waveform inversion procedure to reconstruct the shapes of the defect. Through iteratively reducing the mismatch in waveforms between the measurement and synthetic data from defect models, the hybrid GFWI is able to output the geometries of the defect directly making best use of the waveform data. Its great high level of accuracy has been validated through various numerical examples, including volumetric voids, straight and complex cracks. Experiment with a phased array system is also performed to further evaluate its accuracy.</p><p>Key words:&nbsp;hybrid geometrical full waveform inversion, multi-mode topological imaging, defect characterization, shape reconstruction</p>

Hybrid Geometrical Full Waveform Inversion for Accurate Defect Characterisation

Paper Proceedings: https://asmedigitalcollection.asme.org/qnde/QNDE2021/volume/85529

ASME 2021 48th Annual Review of Progress in Quantitative Nondestructive Evaluation (QNDE2021)

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