Corrosion presents a major challenge for various industries, especially for petrochemical and nuclear industry. Estimating accurate wall thickness maps of pipes or pressure vessels is of great importance for detecting corrosion damage in these structures and assessing its remaining lifetime. Guided wave tomography provides a solution for this problem in which pipe-like structures have a high diameter to thickness ratio, by sending guided waves through the region of interest, then using tomographic imaging [1,2] to reconstruct the thickness map, significantly eliminating the need to take measurements at all points across the surface. The Structural Health Monitoring (SHM) process involves the observation of a structure over time by using measurements from sensors embedded in this structure in order to monitor its current state of health and hence taking at the right time corrective action to prevent further rupture or leakage. It is essential to use a small number of sensors to limit the intrusiveness of SHM system. Consequently, regularization is applied to adapt tomography in the context of the SHM system. The tomographic algorithm is evaluated in experiments. We show that this tomographic algorithm is particularly well adapted to a so-called "passive" solution, where the ambient elastic noise which naturally presents in an operating structure (due to vibrations, aerodynamic turbulence) is exploited to make tomography by cross correlation [3], no need the emission of waves by the system. The complexity of the embedded SHM system is therefore reduced.
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