Supporting visualization analysis in industrial process tomography by using augmented reality - A case study of an industrial microwave drying system
Artikel i vetenskaplig tidskrift, 2021

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.

Industrial process tomography

Microwave tomography

Multilayered media

Dyadic Green’s function

Augmented reality

Time-reversal imaging

Data processing and visualization

Författare

Yuchong Zhang

Chalmers, Data- och informationsteknik, Interaktionsdesign (Chalmers)

Adel Omrani

Karlsruher Institut für Technologie (KIT)

Rahul Yadav

Itä-Suomen Yliopisto

Morten Fjeld

Chalmers, Data- och informationsteknik, Interaktionsdesign (Chalmers)

Sensors

1424-8220 (ISSN) 1424-3210 (eISSN)

Vol. 21 19 6515

Ämneskategorier

Annan data- och informationsvetenskap

Datavetenskap (datalogi)

Datorseende och robotik (autonoma system)

DOI

10.3390/s21196515

Mer information

Senast uppdaterat

2021-10-14