The use of microwave tomography (MWT) in an industrial drying process is demonstrated in this feasibility study with synthetic measurement data. The studied imaging modality is applied to estimate the moisture content distribution in a polymer foam during the microwave drying process. Such moisture information is crucial in developing control strategies for controlling the microwave power for selective heating. In practice, a reconstruction time less than one second is desired for the input response to the controller. Thus, to solve the estimation problem related to MWT, a neural network based approach is applied to fulfill the requirement for a real-time reconstruction. In this work, a database containing different moisture content distribution scenarios and corresponding electromagnetic wave responses are build and used to train the machine learning algorithm. The performance of the trained network is tested with two additional datasets.

中文翻译：

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使用带神经网络的微波断层扫描估计多孔泡沫中的水分含量分布

本可行性研究使用合成测量数据证明了微波断层扫描 (MWT) 在工业干燥过程中的使用。所研究的成像模式用于估计微波干燥过程中聚合物泡沫中的水分含量分布。这种水分信息对于开发控制选择性加热微波功率的控制策略至关重要。实际上，对于控制器的输入响应，需要少于一秒的重建时间。因此，为了解决与 MWT 相关的估计问题，应用基于神经网络的方法来满足实时重建的要求。在这项工作中，一个包含不同水分含量分布场景和相应电磁波响应的数据库被构建并用于训练机器学习算法。训练后的网络的性能使用两个额外的数据集进行测试。