Fast Tomography: A greedy, heuristic, mesh size–independent methodology for local velocity reconstruction for AE waves in distance decaying environment in semi real-time

Abstract

Tomographic reconstruction is an important step toward visualization, identification and quantification of local damage through of structural elements. We have developed mathematical guiding principles for passive wave tomography. We have then utilized these guiding principles to develop a novel technique: Fast Tomography for computational and information efficiency in tomographic reconstruction with passive stress waves in a distance decaying (sensing) environment. In fast tomography, (i) a node-independent travel path is developed for computational efficiency and (ii) Apriori ranking of AE events using power spectral entropy (PSE) of the AE waveform to distinguish waveforms with high information content for tomographic reconstruction for information efficiency are proposed. Fast Tomography was studied theoretically and experimentally to benchmark the proposed method in terms of computational and information efficiency. Our algorithm provides a significant (>100x) improvement of computational efficiency over an existing approach. And a PSE-based ranking system for AE events enhances information efficiency by 50% as compared to a non-ranked system. Finally, we have validated the application of our method with intractably generated AE events in an accelerated damage test of a steel fiber–reinforced concrete beam.