Abstract
In this work, Bayesian inversion framework is tested on synthetic microwave tomography data at a single frequency in X-band (8 GHz to 12 GHz). The imaging modality is applied to estimate the moisture content distribution in a polymer foam. Such estimations are imperative to develop intelligent and efficient industrial drying systems. Three test cases of low, high, and homogeneous wet basis moisture distribution scenarios are considered. In addition, the generalization capabilities of the Bayesian inversion framework for non-smooth moisture distribution case is discussed. Good estimation results are obtained for the given moisture scenarios.
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