论文标题
使用微波断层扫描与神经网络的微波断层扫描估算多孔泡沫中的水分含量分布
Estimation of moisture content distribution in porous foam using microwave tomography with neural networks
论文作者
论文摘要
这项可行性研究证明了在工业干燥过程中使用微波断层扫描（MWT）的使用，并通过合成测量数据来证明。研究的成像方式用于在微波干燥过程中估计聚合物泡沫中的水分含量分布。这样的水分信息对于制定控制策略来控制微波电源以进行选择性加热。实际上，对于控制器的输入响应，需要小于一秒钟的重建时间。因此，为了解决与MWT相关的估计问题，采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，建立并用于训练机器学习算法的数据库，该数据库包含不同的水分内容分布方案和相应的电磁波响应。训练有素的网络的性能通过两个附加数据集进行了测试。
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.
