Abstract

Corrosion detection is a critical problem in many research areas. Guided wave tomography provides a powerful tool to estimate the remaining thickness of corroded structures. This article introduces an ultrasonic quantitative tomography method called fast inversion tomography (FIT) for corrosion mapping on plate-like structures. FIT consists of offline training and online inversion. The offline training stage uses the supervised descent method (SDM) to generate a series of average descent directions iteratively by minimizing the waveform misfit function between the fixed initial models and training examples. The minimization of the misfit function is equivalent to solving the linear least-squares problem. In the online inversion stage, we reconstruct the velocity map of testing examples using the learned descent directions in an iterative manner. Then, we convert the velocity map into the thickness map using the dispersive characteristics of a specific guided wave mode. The performance of this technique is evaluated using synthetic datasets which include both training and testing examples with different corrosion depths and shapes on an aluminum plate. We also compare the reconstruction accuracy and computation efficiency between FIT and time/frequency-domain full-waveform inversion. The results indicate that FIT exhibits great performance in the problem of quantitative corrosion imaging.

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