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Article

Supporting Visualization Analysis in Industrial Process Tomography by Using Augmented Reality—A Case Study of an Industrial Microwave Drying System

1
Division of Interaction Design and Software Engineering, Department of Computer Science and Engineering, Chalmers University of Technology, SE-41296 Gothenburg, Sweden
2
Institute for Pulsed Power and Microwave Technology (IHM), Karlsruhe Institute of Technology (KIT), 76133 Karlsruhe, Germany
3
Department of Applied Physics, University of Eastern Finland, FI-70210 Kuopio, Finland
*
Author to whom correspondence should be addressed.
This paper is an extension version of the conference paper: Zhang, Y.; Yadav, R.; Omrani, A.; Fjeld, M. A Novel Augmented Reality System To Support Volumetric Visualization in Industrial Process Tomography. In Proceedings of the 2021 Conference on Interfaces and Human Computer Interaction, Online, 21–23 July 2021.
Academic Editor: Uwe Hampel
Sensors 2021, 21(19), 6515; https://doi.org/10.3390/s21196515
Received: 2 September 2021 / Revised: 24 September 2021 / Accepted: 26 September 2021 / Published: 29 September 2021
(This article belongs to the Special Issue Tomographic Sensors for Industrial Process Control)
Industrial process tomography (IPT) based process control is an advisable approach in industrial heating processes for improving system efficiency and quality. When using it, appropriate dataflow pipelines and visualizations are key for domain users to implement precise data acquisition and analysis. In this article, we propose a complete data processing and visualizing workflow regarding a specific case—microwave tomography (MWT) controlled industrial microwave drying system. Furthermore, we present the up-to-date augmented reality (AR) technique to support the corresponding data visualization and on-site analysis. As a pioneering study of using AR to benefit IPT systems, the proposed AR module provides straightforward and comprehensible visualizations pertaining to the process data to the related users. Inside the dataflow of the case, a time reversal imaging algorithm, a post-imaging segmentation, and a volumetric visualization module are included. For the time reversal algorithm, we exhaustively introduce each step for MWT image reconstruction and then present the simulated results. For the post-imaging segmentation, an automatic tomographic segmentation algorithm is utilized to reveal the significant information contained in the reconstructed images. For volumetric visualization, the 3D generated information is displayed. Finally, the proposed AR system is integrated with the on-going process data, including reconstructed, segmented, and volumetric images, which are used for facilitating interactive on-site data analysis for domain users. The central part of the AR system is implemented by a mobile app that is currently supported on iOS/Android platforms. View Full-Text
Keywords: industrial process tomography; data processing and visualization; microwave tomography; augmented reality; time-reversal imaging; dyadic Green’s function; multilayered media industrial process tomography; data processing and visualization; microwave tomography; augmented reality; time-reversal imaging; dyadic Green’s function; multilayered media
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MDPI and ACS Style

Zhang, Y.; Omrani, A.; Yadav, R.; Fjeld, M. Supporting Visualization Analysis in Industrial Process Tomography by Using Augmented Reality—A Case Study of an Industrial Microwave Drying System. Sensors 2021, 21, 6515. https://doi.org/10.3390/s21196515

AMA Style

Zhang Y, Omrani A, Yadav R, Fjeld M. Supporting Visualization Analysis in Industrial Process Tomography by Using Augmented Reality—A Case Study of an Industrial Microwave Drying System. Sensors. 2021; 21(19):6515. https://doi.org/10.3390/s21196515

Chicago/Turabian Style

Zhang, Yuchong, Adel Omrani, Rahul Yadav, and Morten Fjeld. 2021. "Supporting Visualization Analysis in Industrial Process Tomography by Using Augmented Reality—A Case Study of an Industrial Microwave Drying System" Sensors 21, no. 19: 6515. https://doi.org/10.3390/s21196515

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