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Microwave tomography using neural networks for its application in an industrial microwave drying system

Yadav, Rahul; Omrani, Adel; Link, Guido; Vauhkonen, Marko; Lähivaara, Timo

The article presents an application of microwave tomography (MWT) in an industrial drying system to develop tomographic-based process control. The imaging modality is applied to estimate moisture distribution in a polymer foam undergoing drying process. Our Leading challenges are fast data acquisition from the MWT sensors and real-time image reconstruction of the process. Thus, a limited number of sensors are chosen for the MWT and are placed only on top of the polymer foam to enable fast data acquisition. For real-time estimation, we present a neural network-based reconstruction scheme to estimate moisture distribution in a polymer foam. Training data for the neural network is generated using a physics-based electromagnetic scattering model and a parametric model for moisture sample generation. Numerical data for different moisture scenarios are considered to validate and test the performance of the network. Further, the trained network performance is evaluated with data from our developed prototype of the MWT sensor array. The experimental results show that the network has good accuracy and generalization capabilities.

Verlagsausgabe §
DOI: 10.5445/IR/1000139348
Veröffentlicht am 29.10.2021
Cover der Publikation
Zugehörige Institution(en) am KIT Institut für Hochleistungsimpuls- und Mikrowellentechnik (IHM)
Publikationstyp Zeitschriftenaufsatz
Publikationsjahr 2021
Sprache Englisch
Identifikator ISSN: 1424-8220
KITopen-ID: 1000139348
HGF-Programm 38.03.02 (POF IV, LK 01) Power-based Fuels and Chemicals
Erschienen in Sensors
Verlag MDPI
Band 21
Heft 20
Seiten 6919
Nachgewiesen in Web of Science
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