Efficient reconstruction of corrosion profiles by infrared thermography

In this paper, we propose a novel algorithm to solve the hidden corrosion estimation problem from experimental data produced by infrared thermography. This is therefore a thermal inverse problem. The algorithm is put in a predictor-corrector form and uses an Adaptive Finite Element model as the reference model. The adaptation is done in the (linear) predictor step, while the parameter estimation is done in the (nonlinear) corrector step. An ad-hoc regularization strategy has been developed. Experiments with real data have confirmed the effectiveness of the method. Considerable computational savings have been achieved compared to a standard algorithm formulation.