Published October 28, 2021 | Version v1
Journal article Open

System Identification of Conveyor Belt Microwave Drying Process of Polymer Foams Using Electrical Capacitance Tomography

  • 1. Department of Applied Physics, University of Eastern Finland, Kuopio, Finland
  • 2. Mechatronic Department, Electrical Engineering Faculty, K.N. Toosi University of Technology, Tehran, Iran
  • 3. Institute for Pulsed Power and Microwave Technology, Karlsruhe Institute of Technology, Karlsruhe, Germany

Description

The microwave drying process has a wide application in industry, including drying polymer foams after the impregnation process for sealings in the construction industry. The objective of the drying process is to reach a certain moisture in the foam by adjusting the power levels of the microwave sources. A moisture controller can be designed to achieve this goal; however, a process model is required to design model-based controllers.  Since complex physics governs the microwave drying process, system identification tools are employed in this paper to exploit the process input and output information and find a simplified yet accurate model of the process. The moisture content of the foam that is the process output is measured using a designed electrical capacitance tomography (ECT) sensor.  The ECT sensor estimates the 2D permittivity distribution of moving foams, which correlates with the foam moisture. Experiments are conducted to collect the ECT measurements while giving different inputs to the microwave sources. A state-space model is estimated using one of the collected datasets and is validated using the other datasets. The comparison between the model response and the actual measurements shows that the model is accurate enough to design a controller for the microwave drying process.

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Additional details

Funding

European Commission
TOMOCON – Smart tomographic sensors for advanced industrial process control 764902
Research Council of Finland
Seismic full-waveform inversion with application to groundwater exploration 321761
Research Council of Finland
Centre of Excellence of Inverse Modelling and Imaging / Consortium: CoE of Inverse Modelling and Imaging 312344